COVER PAGE FOR PROPOSAL TO THE AIR FORCE OFFICE OF SCIENTIFIC RESEARCH

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Nov 14, 2013 (3 years and 6 months ago)

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COVER PAGE FOR PROPOSAL

TO THE AIR FORCE OFFICE OF SCIENTIFIC RESEARCH


SUBMIT COPIES OF PROPOSAL

TO:

For Consideration by AFOSR Organization Unit(s)

For AFOSR Use Only


(Indicate the most specific unit known, i.e. program, division, etc.)

AFOSR Proposal
Number

AFOSR


Aerospace & Materials Sciences



4015 Wilson Boulevard


Mathematical & Space Sciences



Room 713


Physics & Electronics





Arlington VA

22203
-
1954


Chemistry & Life Sci
ences


Date Received

Number of Copies

Division Assigned



Other (Specify)





Employer Identification Number (EIN) or
Tax Information Number (TIN)


71
-
6003252

Data Universal Numbering System Number (DUNS)

19
-
142
-
9745

Is This Proposal Be
ing Submitted to Another Federal Agency?

YES



NO


If YES, List the Agency or Agencies.

Name of Organization to Which Award Should be Made:

Board of Trustees,
University of Arkansas

Administrative Address of Organization,

Including Zip Code:



120 Ozark Hall, Fayetteville, AR 72701

Institutional Code (If known)






Is Submitting Organization:


Large Business


Small Business


Disa
dvantaged Business


Woman
-
Owned Business



Educational Institution


Historically Black College or University (HBCU)


Minority Institution (MI)


Other Non
-
Profit


Bra
nch/Campus/Other Component (Where work is performed, if different)




Institutional Code (If known)


001108

Title of Proposed Project

Type of Award Requested:

CELDi/AFRL: A Human
-
Centered Approach to Sense and Respond Logistics



GRANT


CONTRACT


AGREEMENT


Other (Specify)


NEW


RENEWAL


Requested Amount

$

962,000.00

Proposed Duration (1
-
60 months)


21

months

Requested Start Date


4/1/05


Proposal Valid Unit:


(minimum of 6 months)

6 mos.

Check Appropriate Box(es) If This Proposal Includes Any of the Items Listed Below
:



Vertebrate Animals


National Environmental Policy Ac
t


Proprietary and Privileged Information


Human Subjects


Historical Places


Group Proposals



PI/PD Department


Edward A. Pohl

PI/PD Postal Address


Department of Industrial Engineeri
ng


4207 Bell Engineering Center, Fayetteville, AR 72701

Typed Names & Signatures

Telephone Number

Facsimile Number

Electronic Mail

PI/PD


Edward A. Pohl

479
-
575
-
6042

479
-
575
-
8431

epohl@engr.uark.edu

Co
-
PI/PD










Administrative Representative Authorized to
Conduct Negotiations:







Primary:


Rosemary Ruff

(479) 575
-
3845

(479) 575
-
3846

rruff@uar
k.edu

Alternate:




( )
-


( )
-




CERTIFICATIONS
: (Not applicable to Contracts) By signing and submitting this proposal, the proposer is providing the certification at Ap
pendix A to 32 CFR
Part 25 regarding debarment, suspension, and other matters; the certification at Appendix C to 32 CFR Part 25 regarding drug
-
free workplace; and the
certification at Appendix A to 32 CFR Part 28 regarding lobbying.

Authorized Representa
tive Title:

Director, RSSP


Typed Name
:

Rosemary Ruff

Date Signed
:




Signature
:

10/98


SUMMARY


PROPOSAL BUDGET FORM

FOR AFOSR USE ONLY

ORGANIZATION

CAGE CODE

Board of Trustees,
University of Arkansas

4B294



DURATION (MONTHS)

21





Proposed

Granted

PRINCIPAL INVESTIGATOR/PROJECT DIRECTOR

Edward A. Pohl

AWARD NO.



A. SENIOR PERSONNEL: PI/PD, Co
-
PI’s, Faculty and Other Senior Associates

AFOSR
-
Funded

Funds

Funds


(List each separately with title
, A.7. Show number in brackets)

Person
-
months

**(Monthly or hourly rate)

Cost
Shared

Requested
from



**RATE

% OF
TIME
TIMETIME
TIME






MOS

Propo
ser

AFOSR


1. (11) PI/ Co
-
PI’s, Faculty







$


$214,120


2.














3.















4. (

) OTHERS (LIST INDIVIDUALLY ON BUDGET EXPLANATION PAGE)














5. (

) TOTAL SENIOR PERSONNEL (1
-
6)













B. OTHER PERSONNEL (SHOW NUMBERS IN BRACKETS)



1. (

) POST DOCTORA
L ASSOCIATES


















2. (

) OTHER PROFESSIONALS (TECHNICIAN, PROGRAMMER, ETC.)













3. (20) GRADUATE STUDENTS (8
-

yr 1, 12
-

yr 2)









204,900


4. (12) UNDERGRADUATE STUDENTS (5
-
6 per yr)









12,040


5. (

) SECRETARIA
L


CLERICAL (IF CHARGED DIRECTLY)












6. (

) OTHER: (PROVIDE EXPLANATION)












TOTAL SALAR
IES AND WAGES (A + B)








431,060

C. FRINGE BENEFITS (IF CHARGED AS DIRECT COSTS) PLEASE PROVIDE
DETAIL OF THE CALCULATION ON AN ATTACHMENT IF NOT APPLIED
DIRECTLY TO THE SALARIES TOTAL
-

REF SECTION 2.12.7.







51,521


TOTAL SALARIES, WAGES AND FRINGE BENEFITS (A + B + C)







482,581

D. EQUIPMENT (LIST ITEM AND DOLLAR AMOUNT FOR EACH ITEM EXCEEDING $5,000.)

8000


(PLEASE ATTACH DETAIL AND VENDOR QUOTES)
-

REF 2.1
2.12



TOTAL EQUIPMENT







E. TRAVEL

1. DOMESTIC (INCL. CANADA, MEXICO AND U.S. POSSESSIONS)





23,300


2. FOREIGN (PROVIDE PER DIEM, DAYS OF STAY, AND PURPOSE)











106,506

F.TUITION REF 2.12.13




.



(

) TOTAL PARTICIPANT COSTS







G. OTHER DIRECT COSTS








1. SUPPLI
ES/MATERIALS




9,250


2. COMPUTER








3. CONSULTANT SERVICES (provide detail)








4. PUBLICATIONS




2,000


5. COMM’S/SHIPPING




6. SUBCONTRACT (provide budget)


99,958


7. O
1
THER (provide detail)








TOTAL OF OTHER DIRECT COSTS



H. TOTAL DIRECT COSTS (A THROUGH G)







I.

FACILITIES AND ADMINISTRATION EXPENSE (overhead)
-

-
specify the rate and base below)

230,406


TOTAL FACILITIES AND ADMINISTRATION EXPENSES







J. TOTAL DIRECT EXPENSES AND
FACILITIES AND ADMINISTRATION
EXPEN
SES(H + I)


Rate (%)


Base ($)


Total ($)













Overhead










G&A










Fringe Benefits










FCCOM









K.

RESIDUAL FUNDS (IF FOR FURTHER SUPPORT OF

CURRENT PROJECT SEE GPG II.D.7.j.)







L. AMOUNT OF THIS REQUEST (J) OR (J MINUS K)




$962,000

M. COST
-
SHARING: PROPOSED LEVEL $


AGREED LEVEL IF DIFFERENT: $


* APPROVED PURCHASING SYSTEM?

YES


NO



IF YES, DATE OF ONR APPROVAL AND EXPIRATION _________________


FOR AFOSR USE ONLY

PI/PD TYPED NAME AND SIGNATURE*

DATE


FACILITIES AND ADMINISTRATION EXPENSES

Edward A. Pohl

2/8/05

VERIFICATION

ORG. REP. TYPED NAME & S
IGNATURE*

Rosemary Ruff

DATE

Date Checked

Date of
Rate Sheet

Initials
-
ORG









SUMMARY






PROPOSAL BUDGET FORM

FOR AFOSR USE ONLY

ORGANIZATION

CAGE CODE

Wright State University 4B991



DURATION (MONTHS)





Proposed

Granted

PRINCIPAL INVESTIGATOR/PROJECT DIRECTOR

Raymond R. Hill

AWARD NO.



A. SENIOR PERSONNEL: PI/PD, Co
-
PI’s, Faculty and Other Senior Associates

AFOSR
-
Funded

Funds

Funds


(List each separately with title, A.7. Show number in bra
ckets)

Person
-
months

**(Monthly or hourly rate)

Cost
Shared

Requested
from



**RATE

% OF
TIME
TIMETIME
TIME






MOS

Proposer

AFOSR


1. Raymond R
. Hill


Principal Investigator

8560



1.0

$


$
8560


2. Sundaram Narayanan


Co
-
Principal Investigator

11370



0.5





5685


3.















4. (

) OTHERS (LIST INDIVIDUALLY ON BUDGET EXPLANATION PAGE)














5. (2) TOTAL SENIOR PERSONNEL (1
-
6)











14245

B. OTHER PERSONNEL (SHOW NUMBERS IN BRACKETS)



1. (

) POST DOCTORAL ASSOCIATES


















2. (

) OTHER PROFESSIONALS (TECHNICIAN, PROGRAMMER, ETC.)











3. (1) GRADUATE STUDENTS










18000


4. (

) UNDERGRADUATE STUDENTS












5. (

) SECRETARIAL


CLERICAL (IF CHARGED DIRECTLY)












6. (

) OTHER: (PROVIDE EXPLANATION)












TOTAL SALARIES AND WAGES (A + B)








32245

C. FRINGE BENEFITS

(IF CHARGED AS DIRECT COSTS) PLEASE PROVIDE
DETAIL OF THE CALCULATION ON AN ATTACHMENT IF NOT APPLIED
DIRECTLY TO THE SALARIES TOTAL
-

REF SECTION 2.12.7.







1453


TOTAL SALARIES, WAGES AND FRINGE BENEFITS (A + B + C)







33698

D. EQUIPMENT (LIST ITEM AND DOLLAR AMOUNT FOR EACH ITEM EXCEEDING $5,000.)



(PLEASE ATTACH DETAIL AND VENDOR QUOTES)
-

REF 2.12.12



TOTAL EQUIPMENT







E. TRAVEL

1.

DOMESTIC (INCL. CANADA, MEXICO AND U.S. POSSESSIONS)





3000


2. FOREIGN (PROVIDE PER DIEM, DAYS OF STAY, AND PURPOSE)












F.TUITION REF 2.12.13




.



(

) TOTAL PARTICIPANT COSTS







G. OTHER DIRECT COSTS








1. SUPPLIES/MATERIALS





225


2. COMPUTER









3. CONSULTANT SERVICES (provide detail)








4. PUBLICATIONS








5. COMM’S/SHIPPING




6. SUBCONTRACT (provide budget)



30000


7. O
2
THER (provide detail)






4250

TOTAL OF OTHER DIRECT COSTS



34475

H. TOTAL DIRECT COSTS (A THROUGH G)





71173

I. FACILITIES AND ADMINISTRATION EXPENSE (overhead)
-

-
specify the rate and base below)



TOTAL

FACILITIES AND ADMINISTRATION EXPENSES





28785

J. TOTAL DIRECT EXPENSES AND
FACILITIES AND ADMINISTRATION
EXPENSES(H + I)


Rate (%)


Base ($)


Total ($)












Overhead

43.5


66173


28785





G&A










Fringe Benefits










FCCOM









K.

RESIDUAL FUNDS (IF FOR FURTHER SUPPORT OF

CURRENT PROJECT SEE GPG II.D.7.j.)







L. AMOUNT OF THIS REQUEST (J) OR (J MINUS K)




$99958

M. COST
-
SHARIN
G: PROPOSED LEVEL $


AGREED LEVEL IF DIFFERENT: $


* APPROVED PURCHASING SYSTEM? YES


NO



IF YES, DATE OF ONR APPROVAL AND EXPIRATION _________________


FOR AFOSR USE ONLY

PI/PD TYP
ED NAME AND SIGNATURE*

DATE


FACILITIES AND ADMINISTRATION EXPENSES




VERIFICATION

ORG. REP. TYPED NAME & SIGNATURE*

DATE

Date Checked

Date of
Rate Sheet

Initials
-
ORG













SUMMARY


PROPOSAL BUDGET FORM

FOR AF
OSR USE ONLY

ORGANIZATION CAGE CODE

University of Dayton Research Institute 50280



D
URATION (MONTHS)




Proposed

Granted

PRINCIPAL INVESTIGATOR/PROJECT DIRECTOR

Laura Militello

AWARD NO.



A. SENIOR PERSONNEL: PI/PD, Co
-
PI
’s, Faculty and Other Senior Associates

AFOSR
-
Funded

Funds

Funds


(List each separately with title, A.7. Show number in brackets)

Person
-
months

**(Monthly or hourly rate)

Cost
Shared

Requested
from




**RATE

% OF
TIME
TIMETIME
TIME






MOS

Proposer

AFOSR


1. Laura Militello, Principal Investigator

7498



0.5

$


$3749


2.
















3.















4. (

) OTHERS (LIST INDIVIDUALLY

ON BUDGET EXPLANATION PAGE)














5. (1) TOTAL SENIOR PERSONNEL (1
-
6)











3749

B. OTHER
PERSONNEL (SHOW NUMBERS IN BRACKETS)



1. (

) POST DOCTORAL ASSOCIATES


















2. (2) OTHER PROFESSIONALS (TEC
HNICIAN, PROGRAMMER, ETC.)

8341


0.75





6256


3. (

) GRADUATE STUDENTS












4. (

) UNDERGRADUATE STUDENTS












5. (

) SECRETARIAL


CLERICAL (IF CHARGED DIRECTLY)












6. (

) OTHER: (PROVIDE EXPLANATION)












TOTAL SALARIES AND WAGES (A + B)








15533

C. FRINGE BENEFITS (IF CHARGED AS DIRECT COSTS) PLEASE PROVIDE
DETAIL OF THE CALCULATION ON AN ATTACHMENT IF NOT APPLIED
DIRECTLY TO THE SALA
RIES TOTAL
-

REF SECTION 2.12.7.







4163


TOTAL SALARIES, WAGES AND FRINGE BENEFITS (A + B + C)







19696

D. EQUIPMENT (LIST ITEM AND DOLLAR AMOUNT FOR EACH ITEM EXCEEDING $5,000.)



(P
LEASE ATTACH DETAIL AND VENDOR QUOTES)
-

REF 2.12.12



TOTAL EQUIPMENT







E. TRAVEL

1. DOMESTIC (INCL. CANADA, MEXICO AND U.S. POSSESSIONS)





500


2. FOREIGN (PROVIDE PER DIEM, DAYS OF

STAY, AND PURPOSE)












F.TUITION REF 2.12.13




.



(

) TOTAL PARTICIPANT COSTS







G. OTHER DIRECT COSTS









1. SUPPLIES/MATERIALS





135


2. COMPUTER








3. CONSULTANT SERVICES (provide detail)








4. PUBLICATIONS








5. COMM’S/SHIPPING




6. SUBCONTRACT (provide budget)




7. O
3
THER (provide detail)








TOTAL OF OTHER DIRECT COSTS



135

H. TOTAL DIRECT COSTS (A THROU
GH G)





20331

I. FACILITIES AND ADMINISTRATION EXPENSE (overhead)
-

-
specify the rate and base below)



TOTAL FACILITIES AND ADMINISTRATION EXPENSES





9669

J. TOTAL DIRECT EXPENSES AND
FACILITIES AND ADM
INISTRATION
EXPENSES(H + I)


Rate (%)


Base ($)


Total ($)













Overhead

47.5


20331


9669





G&A










Fringe Benefits










FCCOM









K.

RESIDUAL FUNDS (IF FOR FURTHER SUPPORT OF

CURRENT PROJECT S
EE GPG II.D.7.j.)







L. AMOUNT OF THIS REQUEST (J) OR (J MINUS K)




$30000

M. COST
-
SHARING: PROPOSED LEVEL $


AGREED LEVEL IF DIFFERENT: $


* APPROVED

PURCHASING SYSTEM? YES


NO



IF YES, DATE OF ONR APPROVAL AND EXPIRATION _________________


FOR AFOSR USE ONLY

PI/PD TYPED NAME AND SIGNATURE*

DATE


FACILITIES AND ADMINISTRATION EXPENSES




VERIFICATIO
N

ORG. REP. TYPED NAME & SIGNATURE*

DATE

Date Checked

Date of
Rate Sheet

Initials
-
ORG





















Budget Justification

The budget outlined for this proposal is to support a minimum of 11 faculty researchers performing a collection

of research tasks in three focused areas.
Graduate and undergraduate personnel will be utilized throughout the duration of the project, Year 1 through Year 2. A signi
ficant amount of tuition is
included to support the student researchers involved. Trav
el to USAF and DoD facilities will require substantial funding.

PI:

Edward A. Pohl, Associate Professor

Co
-
PI:










Scott J. Mason, Assistant Professor









Heather L. Nachtmann, Assistant Professor









Manuel D. Rossetti, Associate Pr
ofessor


Faculty
:

Nebil Buyurgan, Assistant Professor





Justin R. Chimka, Assistant Professor

C. Richard Cassady, Associate Professor




Raymond R. Hill, Associate Professor

Laura Militello, Senior Research Psychologist




Chang S. Nam, Assistant Pro
fessor

John English, Professor and Head


PI/Co
-
PI/Faculty

1)

Faculty 9.29 months, Year 1

2)

Faculty 18.26 months, Year 2

3)

Assumed 3% salary inflation per year



Other Personnel

1)

Graduate Students, 8 Year 1 and 12 Year 2.

a)

MS $1000/month, Ph.D. $1500/month.

2)

UG
Students, 5
-
6 per year, Year 1 and Year 2.

a)

Undergraduate researchers earn $12/hr, working approximately 10 hours/week


Fringe Benefits Detail:


FRINGE BENEFITS




BENEFITS RATE

20,687


Sr Personnel & Non
-
classifieds, summer

17.434%

23,422


Sr Person
nel & Non
-
classifieds, non
-
summer

24.536%

0


Classified




29.410%

7,364


GRA




3.594%

0


Hourly, non
-
student




8.399%

47


Hourly, enrolled student




0.393%

$51,521

Total FB








$482,581

Total Salaries + Benefits









Trave
l

1)

D
omes
tic 11 trips @ approximately $1400 per trip, Year 1

2)

Domestic 6 trips @ approximately $1400 per trip, Year 2


Other Direct Costs

1)

Materials and Supplies

2)

Publication/documentation expenses

3)

Tuition projection for duration of project

a)

$242/credit hour, 21
credit hours per year, assumed 10% increase per year




Title:

CELDi/AFRL: A Human
-
Centered Approach to Sense and Respond Logistics

Investigators:

Dr. E
. P
ohl, Dr. N
.

Buyurgan, Dr. R
.

Cassady, Dr. J
.

Chimka, Dr. J
.

English, Dr. R
.

Hill, Dr. S
.

Mason, Ms.

L
.

Militello, Dr. H
.

Nachtmann, Dr. C
.

Nam, Dr. M
.

Rossetti

Project Summary

The Center for Engineering Logistics and Distribution (CELDi) at the University of Arkansas is a multi
-
campus,
industry/university cooperative research center sponsored in part by

the National Science Foundation. This proposal, in
cooperation with NSF, has been formulated to provide the United States Air Force (USAF) and specifically the Air Force
Research Laboratory (AFRL) with long term, basic research, through CELDi. In order to

provide the agile combat material
support necessary to sustain our warfighters and weapons systems in future contingencies and crises, new technologies and
processes for logistics need to be developed. Today’s approach to “just in time” logistics has prov
en inefficient and
inadequate in current conflicts. The DoD is working to eliminate these deficiencies by advocating a new, more dynamic
logistics support system, as outlined in the Office of Force Transformation Concept Document on Operational Sense and
R
espond Logistics (S&RL) [OSD/OFT, 2004]. As described, the future joint force will operate in a complex and
unpredictable environment due to changes in the security environment. Therefore, the logistics system of the future must be
adaptive and flexible in

supporting the joint fighting force across services and with cross
-
organizational and even cross
-
cultural capability.

The development of new technologies and processes that support an S&R capability requires the creation of a network of
individuals, orga
nizations, and tools all working together to develop innovative techniques including continuous development
and refinement of concepts, processes, technologies, and organizations in order to influence change and drive military agilit
y.
The goal of this res
earch effort is to develop
quantitative and scientific methods

that will assist researchers and military
logisticians in the analysis of the effectiveness of logistics technology and processes in an S&RL environment that incorpora
te
both a
human
-
centered

a
nd a
system
-
based

perspective.

Because of the complexities involved with S&RL concepts, it is imperative that scientific and engineering approaches
based on a
holistic

and
systems engineering

perspective be utilized to improve logistics support and respons
iveness within this
evolving defense logistics archetype. The logistics support function should be treated as a socio
-
technical system where
human elements, technology, and software/algorithms interact to develop solutions that can impact the entire system
. To this
end, with the assistance of the Logistics Readiness Branch of AFRL, we have developed a
human
-
centered

research initiative
designed to investigate and support the tenants of an S&RL paradigm for the USAF. The three major areas of this research
in
itiative are 1)A Modeling & Simulation Based Framework for S&RL Concepts, 2)Adaptive Military Logistics Network
Design and Optimization, 3)Cognitive Decision Support in an S&RL Environment. To develop innovative solutions to
problems in these areas, a mult
i
-
year, multi
-
investigator, multi
-
university, center
-
based research approach has been
formulated.

The
intellectual merit

of this proposal is the fundamental research performed in support of the proposed goals. Specific
expected contributions include: 1) Ne
w modeling paradigms for supply chain simulation, 2) New simulation methodologies,
mathematical models and techniques for the optimization, performance evaluation, and improvement of future military
logistics support networks, 3) New methods of modeling an
d incorporating human performance issues and collaborative
decision making within an S&RL environment. These contributions will provide basic research and enhanced understanding
of the human aspects of the S&RL archetype for AFRL’s product development effo
rts. Parallel developments at AFRL/HEAL
under the Technology Applications for S&RL Program and AFRL/IF under the Joint Battlespace Infosphere will be integrated
under this effort to assure maximum technology transition and research payoff in military appli
cations. In terms of the
proposed research’s
broader impact
, we believe that technology transfer activities with the USAF will emplace new
information tools in organizations so as to promote rapid, adaptive, and flexible business processes to gain competit
ive
advantage. The human
-
centered aspects of collaboration within the infosphere seem to have special significance for dual
-
use
application. As Arkansas is an NSF
-
designated EPSCOR state, th
is proposal’s
funding will directly benefit the state’s research
i
nfrastructure. The funding will directly support graduate students in each of these areas and will thus increase the producti
on
of qualified scientists and engineers available in the US.




In order to support such an effort, a cohesive team of competent
and established researchers in the areas of logistics,
operations research, reliability, maintainability, human factors/ergonomics, and decision support systems is required. The
participants for this effort consist of faculty members from the University o
f Arkansas (UofA), Wright State University
(WSU), and the University of Dayton Research Institute (UDRI). Participants include
:

Nebil Buyurgan, Ph.D.

Dr. Buyurgan is an Assistant Professor in the Industrial Engineering Department at the University of Arka
nsas. He
received his BS degree in Industrial Engineering from Istanbul Technical University, his MS and PhD degrees in Engineering Ma
nagement
with emphasis on manufacturing engineering from the University of Missouri
-
Rolla. In August 2004, he joined the U
ofA as a tenure
-
track
assistant professor. Dr. Buyurgan’s research interests include flexible manufacturing systems, computer integrated manufactur
ing, web
-
based manufacturing system control, modeling and analysis of automated manufacturing systems, and in
tegration of process planning with
scheduling. He is a member of the Institute of Industrial Engineers (IIE), Society of Manufacturing Engineers (SME), America
n Society for
Engineering Education (ASEE), and Institute of Electrical and Electronics Engineer
s (IEEE).

Justin R. Chimka, Ph.D.
Justin Chimka is an assistant professor in the Department of Industrial Engineering at the University of Arkansas.
He received his Ph.D. in Industrial Engineering from the University of Pittsburgh. Justin's research and te
aching interests include
production, optimization, statistics and quality, design and education. Justin is a member of ASEE, ASA, IIE and the Psychome
tric Society.

C. Richard Cassady, Ph.D., P.E.

Richard Cassady is an associate professor in the Department
of Industrial Engineering at the University
of Arkansas. Prior to his service at the UofA, he served on the industrial engineering faculty at Mississippi State Universit
y. He received his
B.S. summa cum laude, M.S. and Ph.D., all in industrial and systems
engineering, from Virginia Tech.
He has extensive research experience
in the modeling and analysis of maintainable systems, as well as the optimization of maintenance policies. This experience in
cludes 13
funded projects totaling more than $1.1 million in
expenditures and has resulted in 6 journal articles, 19 conference papers and 7 graduate
student theses. He is a Senior Member of IIE, and a member of ASEE, ASQ, INFORMS and SRE. He is also a member of the Manageme
nt
Committee of the Annual Reliability and

Maintainability Symposium.

Raymond R. Hill, Ph.D.,

is an Associate Professor of Industrial & Human Factors Engineering at the Wright State University. He holds a
BS degree in mathematics from Eastern Connecticut State University, a MS in Operations Resea
rch from the Air Force Institute of
Technology, and a PhD in Industrial and Systems Engineering from The Ohio State University. Dr. Hill retired from the United

States Air
Force in 2003 in the grade of Lieutenant Colonel having served in a variety of staf
f and analytical roles. Dr. Hill is an Associate Editor for
Military Operations Research and the Journal of Defense Modeling and Simulation. His research interests are in the area of h
euristics and
optimization applications, modeling and simulation for d
ecision support, and issues associate with humans and complex systems. Dr. Hill
has published over 50 technical works in journals, conferences, and as defense technical reports. He is a member of INFORMS,

MORS,
IIE, SCS, and WSEAS.

Scott J. Mason, Ph.D.,

P.E.

is an Assistant Professor and Associate Department Head of Industrial Engineering at the University of
Arkansas. He received his BSME and MSE (Operations Research) degrees from The University of Texas at Austin and his PhD (Ind
ustrial
Engineering) f
rom Arizona State University. His research and teaching interests include production planning and scheduling;
semiconductor manufacturing; and manufacturing and transportation applications of operations research. He is a member of INF
ORMS and
a Senior Me
mber of IIE.

Laura Militello, M.A.,

is a senior research psychologist in the UDRI Human Factors Group and an adjunct faculty member in the
Department of Psychology at the University of Dayton. She has conducted over 15 cognitive task analyses in domains as

diverse as B
-
2
piloting, oncology, weapons directing, and website navigation for the blind. Ms. Militello has experience as a user
-
interface designer for
devices with both hardware and software components. She has experience designing for a range of use
r groups and has published in the
area of multinational usability

testing. She has published on the topic of team coordination and is currently leading a project to study team
coordination and decision making in the context of emergency response logistics
.

Heather Nachtmann, Ph.D.

Dr. Nachtmann is an assistant professor of Industrial Engineering at the University of Arkansas. She received
her Ph.D. in Industrial Engineering from the University of Pittsburgh in 2000. Her research interests include economi
c decision analysis,
intermodal transportation, and decision
-
making under uncertainty. Her research efforts have secured more than $1 million in external
research funds and resulted in nine journal articles and 29 refereed conference papers. She is a me
mber of AACE International, IIE, and
INFORMS.

Chang S. Nam, Ph.D., AHFP.
Dr. Nam is an assistant professor in the Department of Industrial Engineering at the University of Arkansas.
He received his Ph.D. in Industrial and Systems Engineering from Virgini
a Polytechnic Institute and State University. Prior to joining the
University of Arkansas, he has also served as a postdoctoral research associate at Virginia Tech. His research and teaching i
nterests include
cognitive ergonomics, adaptive and intelligent
human
-
computer interaction, groupware and computer
-
supported cooperative work, cognitive
architectures, and ubiquitous computing. He is a member of HFES.

Edward A. Pohl, Ph.D., CRE.
Dr. Pohl is an Associate Professor in the Department of Industrial Engine
ering at the University of
Arkansas. Dr. Pohl retired from
United States Air Force in the grade of Lieutenant Colonel and served in a variety of engineering, analysis
and academic positions during his career. Dr. Pohl received his Ph.D. in systems and in
dustrial engineering from the University of Arizona,
an M.S. in reliability engineering from the University of Arizona, an M.S. in systems engineering from AFIT, an M.S. in engin
eering
management from the University of Dayton, and a B.S.E.E. from Boston Un
iversity. His primary research interests are in repairable systems

modeling, reliability, decision analysis, engineering optimization, and probabilistic design. Dr. Pohl has published over 40

technical works
in journals, conferences, and as defense techn
ical reports Dr. Pohl is a Senior member of IIE, a member of ASQ, IEEE, INFORMS,
INCOSE and MORS. Ed is an ASQ certified reliability engineer. Dr. Pohl serves as an Associate Editor for Military Operation
s Research,
the IEEE Transactions on Reliability,

and as a Department Editor for IIE Transactions Focus Issues on Quality and Reliability.

Manuel D. Rossetti, Ph.D., P.E.

Dr. Rossetti is an Associate Professor of Industrial Engineering. Dr. Rossetti has published over thirty
journal and conference ar
ticles in the areas of transportation, manufacturing, health care and simulation and he has obtained over $1.75
million dollars in extra
-
mural research funding. His research sponsors have included the Pine Bluff Arsenal, The Arkansas Science and
Technolog
y Authority, the Defense Logistics Agency, the Naval Systems Supply Command, the Air Force Research Laboratory, Wal
-
Mart
Stores Inc., the Transportation Research Board, and the US Department of Transportation. His research interests include the
design,
an
alysis, and optimization of manufacturing, health care, and transportation systems using stochastic modeling, computer simula
tion, and
heuristic techniques.

John English, Ph.D., P.E.

is Professor and Head of Industrial Engineering at the University of Arka
nsas. He holds BSEE and MSOR
degrees from the University of Arkansas and a Ph.D. in Industrial Engineering and Management from Oklahoma State University.

His
research interests include all aspects of engineering logistics and quality and reliability engi
neering. He is a registered Professional
Engineer in the State of Arkansas. He has recently served as an Editor for the IEEE Transactions on Reliability, VP for Syst
ems Integration
in IIE, Senior VP for Publications for IIE, and General Chair of Chairman

of the Board for the Annual Reliability and Maintainability
Symposium.. He currently serves as the Editor of the Quality and Reliability Engineering Issue of the IIE Transactions and i
s a member of
the Management committee for the Ann. Reliability & Main
tainability Symposium. Dr. English serves as the executive director and project
evaluation coordinator for the Center for Engineering Logistics and Distribution (CELDi), a National Science Foundation
Industry/University Cooperative Research Center at the
University of Arkansas.

Additional participants may be included depending on research interests and project requirements. In the following
sections, each of the focused research efforts is briefly described to indicate the motivation for the effort, the b
asic research
approach to be taken, and the anticipated outcomes.
________________________________________________________________________

1.

Introduction

The Center for Engineering Logistics and Distribution (CELDi) is a multi
-
campus, industry/universi
ty
cooperative research center sponsored in part by the National Science Foundation. The University of
Arkansas, University of Oklahoma, University of Louisville, Oklahoma State University, University of
Florida, and Lehigh University have joined together
to merge unique research strengths that allow CELDi to
surpass traditional research centers that offer a compartmentalized approach to research. The research of the
center focuses on the art and science of obtaining, producing and distributing material and

product in the
proper place and in the proper quantities. Logistics systems require the planning and coordination of the
physical movement aspects of an organization’s operation such that the flow of raw materials, parts and
finished goods is achieved in
a manner that minimizes total costs for the levels of services desired. CELDi
research teams and business partners are dedicated to advancing distribution technology, education, and
practice. CELDi provides solutions to real
-
world problems with business pa
rtners taking an active role in
assuring the relevancy of the center’s research agenda and educational activities.

Current research focus areas include logistics supply chain management which focuses on issues related
to supply integration, supply managem
ent and transportation and shop floor logistics which includes
expertise in material handling as well as other scheduling and inventory management issues on the shop or
warehouse floor. Other CELDI research focuses on enterprise performance measurements, i
ntegrated
software systems, and distribution management. In addition, CELDi has a long history of supporting military
related research. In particular, the University of Arkansas (UofA) has performed research for the Defense
Logistics Agency, Naval Systems
Supply, the U.S. Army’s Pine Bluff Arsenal, and the Air Force Research
Laboratory (AFRL). This research history has uniquely positioned the UofA and CELDi to assist the United
States Air Force (USAF) with scientific and strategic guidance in support of new

logistics initiatives that
support the Department of Defense (DoD) transition to an Operational Sense and Respond Logistics (S&RL)
paradigm. This proposal, in cooperation with NSF and AFRL, has been formulated to provide the USAF and
specifically the AFRL
/HEAL, Logistics Readiness Branch, with long
-
term, basic research, to improve
logistics support and responsiveness within this evolving defense logistics archetype.


2.

Background

The General Accounting Office (GAO) has reported that there were substantial

logistics support
problems in Operations Iraqi Freedom. As stated in GAO
-
04
-
305R, there was a backlog of hundreds of
pallets and containers due to transportation constraints and inadequate asset visibility, a discrepancy of $1.2B
between the amount of mat
eriel shipped to Army activities and amount of materiel acknowledged received,
cannibalization of vehicles due to unavailability of parts, and duplication of requisitions due to inadequate
asset visibility [Solis, 2003]. Retired Navy Vice Admiral Arthur Ce
browski, director of the Pentagon’s Office
of Force Transformation, has stated that today’s “just
-
in
-
time” supply delivery systems are “wholly irrelevant
to what actually goes on at the point of the spear” [Gilmore, 2004]. Lt Gen Claude Christianson, the A
rmy
Staff’s Logistics chief, has stated that the current logistics support system is too rigid and not flexible enough
to respond to today’s constantly evolving battlespace [Gilmore, 2004].

The DoD is working to eliminate these deficiencies by advocating
a new, more dynamic logistics
support system, as outlined in the Office of Force Transformation Concept Document on Operational S&RL
[OSD/OFT, 2004]. As described, the future joint force will operate in a complex and unpredictable
environment due to change
s in the security environment. Adversaries will be multi
-
dimensional, flexible,
distributed, information
-
aware, and they will have the capability to rapidly adapt to US strategies and tactics.
As a result, the logistics system of the future must be adaptiv
e and flexible in supporting the joint fighting
force across services and with cross
-
organizational and cross
-
cultural capability. The S&RL concept as
envisioned by the DoD will “lead the transformation of changing the joint forces from a basic, linear sup
ply
chain to a networked, mosaic approach” [OSD/OFT, 2004]. The culture within the DoD will become more
anticipatory in nature and therefore the supply network must become robust and flexible to support the future
war
-
fighter.

The USAF recognizes that the
future battlespace will utilize an unprecedented level of autonomous and
semi
-
autonomous ground, sea, and air platforms linked through a coordinated control system. In order to
provide the agile combat material support necessary to sustain our war
-
fighters

and weapons systems in a
variety of contingencies and crises, new technologies for logistics need to be developed. The development of
new technologies and processes that support an S&RL capability requires the creation of a network of
individuals, organiz
ations, and tools working together to develop innovative techniques including continuous
development and refinement of concepts, processes, technologies, and organizations in order to influence
change to drive military agility. CELDi and the UofA are posit
ioned to investigate the application and
integration of the following S&RL concepts for the USAF:

1.

Networked adaptive logistics

2.

Real
-
time logistics management through Total Asset Visibility and In
-
Transit Asset
Visibility

3.

Logistics management of information
, communications and processing resources

4.

Logistics
-
related cognitive decision aids

5.

Anticipatory proactive logistics

The goal of this research effort is to develop
quantitative and scientific methods

that will assist
researchers and military logisticians i
n the analysis of the effectiveness of logistics technology and processes
in an S&RL environment that incorporate both a
human
-
centered

and a
system
-
based

perspective.


3.

Project Approach

In this section, we outline our general research approach for an in
tegrated examination of S&RL
technologies and processes and their impact on the future of human
-
centered and technology
-
based logistics
efforts in the USAF. A specific set of concrete activities and their context for the basic research are
developed. In ad
dition, a top
-
level project plan is presented, including our plans for interaction with the
USAF/AFRL and subsequent dissemination of this work. Finally, we discuss the intellectual merit and
broader impacts of the proposed research.

Logistics is the appli
cation of scientific principles to the design, construction, and operation of efficient
and economic systems that facilitate the flow and storage of people, products, and information from point of
origin to point of consumption in order to meet customer re
quirements. Industrial and military organizations
have recognized the need to implement quicker, more agile logistics systems which to reduce logistics costs
while maintaining service requirements, through both the implementation of technology and through
the
improved productivity of the people involved within the logistics value chain. Because of the complexities
involved with the S&RL concepts, it is imperative that scientific and engineering approaches based on a
holistic

and
systems engineering

perspect
ive be utilized to improve the logistics support and responsiveness
within this evolving defense logistics archetype. The logistics support function should be treated as a socio
-
technical system where the human elements, the technology, and the software an
d algorithms interact to
develop solutions that can impact the entire system. To this end, with the assistance of AFRL/HEAL, we
have developed a
human
-
centered

research initiative designed to investigate and support the tenants of a
S&RL paradigm in the US
AF. The three major areas of this research initiative are:



Modeling and Simulation
-
Based Framework for Sense and Respond Logistics Concepts



Adaptive Military Logistics Network Design and Optimization



Cognitive Decision Support in a Sense and Respond Enviro
nment

In order to support such an effort, a cohesive team of competent and established researchers in the areas
of logistics, operations research, reliability, maintainability, human factors/ergonomics, and decision support
systems is required. The partici
pants for this effort consist of faculty members from the UofA, Wright State
University (WSU), and the University of Dayton Research Institute (UDRI). Participants include:

Nebil Buyurgan, Ph.D.

Dr. Buyurgan is an Assistant Professor in the Industrial Engi
neering Department at
the UofA. He received his BS degree in Industrial Engineering from Istanbul Technical University, his MS
and PhD degrees in Engineering Management with emphasis on manufacturing engineering from the
University of Missouri
-
Rolla. In Au
gust 2004, he joined the UofA as a tenure
-
track assistant professor. Dr.
Buyurgan’s research interests include flexible manufacturing systems, computer integrated manufacturing,
web
-
based manufacturing system control, modeling and analysis of automated man
ufacturing systems, and
integration of process planning with scheduling. He is a member of the Institute of Industrial Engineers (IIE),
Society of Manufacturing Engineers (SME), American Society for Engineering Education (ASEE), and
Institute of Electrical

and Electronics Engineers (IEEE).

Justin R. Chimka, Ph.D.
Justin Chimka is an assistant professor in the Department of Industrial Engineering
at the UofA. He received his Ph.D. in Industrial Engineering from the University of Pittsburgh. Justin's
research

and teaching interests include production, optimization, statistics and quality, design and education.
Justin is a member of ASEE, ASA, IIE and the Psychometric Society.

C. Richard Cassady, Ph.D., P.E.

Richard Cassady is an associate professor in the Depa
rtment of Industrial
Engineering at the UofA. Prior to his service at the UofA, he served on the industrial engineering faculty at
Mississippi State University. He received his B.S. summa cum laude, M.S. and Ph.D., all in industrial and
systems engineering
, from Virginia Tech.
He has extensive research experience in the modeling and analysis
of maintainable systems, as well as the optimization of maintenance policies. This experience includes 13
funded projects totaling more than $1.1 million in expenditure
s and has resulted in 6 journal articles, 19
conference papers and 7 graduate student theses. He is a Senior Member of IIE, and a member of ASEE,
ASQ, INFORMS and SRE. He is also a member of the Management Committee of the Annual Reliability and
Maintainab
ility Symposium.

John English, Ph.D., P.E.

is Professor and Head of Industrial Engineering at the UofA. He holds BSEE and
MSOR degrees from the UofA and a Ph.D. in Industrial Engineering and Management from Oklahoma State
University. His research interests

include all aspects of engineering logistics and quality and reliability
engineering. He is a registered Professional Engineer in the State of Arkansas. He has recently served as an
Editor for the IEEE Transactions on Reliability and as the VP for Systems

Integration in IIE. He currently
serves as the Editor of the Quality and Reliability Engineering Issue of the IIE Transactions and is a member
of the Management committee for the Ann. Reliability & Maintainability Symposium. Dr. English will be
serving as

director as CELDi and project evaluation coordinator.

Raymond R. Hill, Ph.D.,

is an Associate Professor of Industrial & Human Factors Engineering at the Wright
State University. He holds a BS degree in mathematics from Eastern Connecticut State University
, a MS in
Operations Research from the Air Force Institute of Technology, and a PhD in Industrial and Systems
Engineering from The Ohio State University. Dr. Hill retired from the United States Air Force in 2003 in the
grade of Lieutenant Colonel having se
rved in a variety of staff and analytical roles. Dr. Hill is an Associate
Editor for Military Operations Research and the Journal of Defense Modeling and Simulation. His research
interests are in the area of heuristics and optimization applications, modeli
ng and simulation for decision
support, and issues associate with humans and complex systems. Dr. Hill has published over 50 technical
works in journals, conferences, and as defense technical reports. He is a member of INFORMS, MORS, IIE,
SCS, and WSEAS.

S
cott J. Mason, Ph.D., P.E.

is an Assistant Professor and Associate Department Head of Industrial
Engineering at the UofA. He received his BSME and MSE (Operations Research) degrees from The
University of Texas at Austin and his PhD (Industrial Engineering)

from Arizona State University. His
research and teaching interests include production planning and scheduling; semiconductor manufacturing;
and manufacturing and transportation applications of operations research. He is a member of INFORMS and
a Senior Me
mber of IIE.

Laura Militello, M.A.,

is a senior research psychologist in the UDRI Human Factors Group and an adjunct
faculty member in the Department of Psychology at the University of Dayton. She has conducted over 15
cognitive task analyses in domains as

diverse as B
-
2 piloting, oncology, weapons directing, and website
navigation for the blind. Ms. Militello has experience as a user
-
interface designer for devices with both
hardware and software components. She has experience designing for a range of user
groups and has
published in the area of multinational usability testing. She has published on the topic of team coordination
and is currently leading a project to study team coordination and decision making in the context of
emergency response logistics.

H
eather Nachtmann, Ph.D.

Dr. Nachtmann is an assistant professor of Industrial Engineering at the UofA.
She received her Ph.D. in Industrial Engineering from the University of Pittsburgh in 2000. Her research
interests include economic decision analysis, in
termodal transportation, and decision
-
making under
uncertainty. Her research efforts have secured more than $1 million in external research funds and resulted in
nine journal articles and 29 refereed conference papers. She is a member of AACE Internationa
l, IIE, and
INFORMS.

Chang S. Nam, Ph.D., AHFP.
Dr. Nam is an assistant professor in the Department of Industrial Engineering
at the UofA. He received his Ph.D. in Industrial and Systems Engineering from Virginia Polytechnic Institute
and State University
. Prior to joining the UofA, he has also served as a postdoctoral research associate at
Virginia Tech. His research and teaching interests include cognitive ergonomics, adaptive and intelligent
human
-
computer interaction, groupware and computer
-
supported c
ooperative work, cognitive architectures,
and ubiquitous computing. He is a member of HFES.

Edward A. Pohl, Ph.D., CRE.
Dr. Pohl is an Associate Professor in the Department of Industrial
Engineering at the UofA. Dr. Pohl retired from
United States Air Forc
e in the grade of Lieutenant Colonel
and served in a variety of engineering, analysis and academic positions during his career. Dr. Pohl received
his Ph.D. in systems and industrial engineering from the University of Arizona, an M.S. in reliability
enginee
ring from the University of Arizona, an M.S. in systems engineering from AFIT, an M.S. in
engineering management from the University of Dayton, and a B.S.E.E. from Boston University. His primary
research interests are in repairable systems modeling, reliab
ility, decision analysis, engineering optimization,
and probabilistic design. Dr. Pohl has published over 40 technical works in journals, conferences, and as
defense technical reports Dr. Pohl is a Senior member of IIE, a member of ASQ, IEEE, INFORMS, INCO
SE
and MORS. Ed is an ASQ certified reliability engineer. Dr. Pohl serves as an Associate Editor for Military
Operations Research, the IEEE Transactions on Reliability, and as a Department Editor for IIE Transactions
Focus Issues on Quality and Reliability
.

Manuel D. Rossetti, Ph.D., P.E.

Dr. Rossetti is an Associate Professor of Industrial Engineering. Dr.
Rossetti has published over thirty journal and conference articles in the areas of transportation,
manufacturing, health care and simulation and he has

obtained over $1.75 million dollars in extra
-
mural
research funding. His research sponsors have included the Pine Bluff Arsenal, The Arkansas Science and
Technology Authority, the Defense Logistics Agency, the Naval Systems Supply Command, AFRL, Wal
-
Mart
Stores Inc., the Transportation Research Board, and the US Department of Transportation. His research
interests include the design, analysis, and optimization of manufacturing, health care, and transportation
systems using stochastic modeling, computer sim
ulation, and heuristic techniques.

Additional participants may be included depending on research interests and project requirements. In the
following sections, each of the focused research efforts is briefly described to indicate the motivation for the
eff
ort, the basic research approach to be taken, and the anticipated outcomes.

To make satisfactory progress in such complex and important research areas requires that long term
funding be available. The suggested duration of each research topic should be tw
o years. We are requesting
approximately $1 million in funds to be expended over a two year period. Initial funding of approximately $1
million has been approved by AFRL and will be transferred to NSF for the first two years of this effort.
Additional fund
ing will be contingent upon availability. In addition to supporting faculty time, travel and
administrative functions, the majority of the requested funds will be used to support graduate students who
will be working toward theses and dissertation topics s
temming from the basic research proposed in this
project.


3.1

Modeling and Simulation Based Framework for Sense and Respond Logistics Concepts
(
Rossetti,
Cassady, Pohl
)

Better models and techniques are required in order to be able to evaluate and optimize

the new dynamic
demand and support networks required by the S&RL concept. In addition to the evaluation and optimization
of these new adaptive networks, we must be able to better understand the decision support requirements for
humans that are embedded in

this complex and rapidly changing environment. Force transformation is
creating a modular, highly mobile military that can make decisions across a distributed battlefield and that
can apply adaptive (and sometimes autonomous) decision making techniques as

force multipliers. These
transformations are creating new requirements for logistics capabilities including the ability to dynamically
allocate and prioritize sources of supply and the ability to react to commander’s intent given missions, tasks,
and desi
red effects. The concept of S&RL has envisioned the need to rapidly design responsive demand and
support networks that can anticipate, predict, and coordinate actions at the strategic, operational, and tactical
levels.

In order to better understand the cha
llenges created by this new doctrine, we propose to develop a
simulation
-
based framework for:



Evaluating adaptable demand and supply networks



Evaluating new metrics for optimizing and controlling these networks



Evaluating the new decisions required in such

networks, and



Evaluating the human cognitive capabilities within these networks.

The core of the framework will be an object
-
oriented, agent
-
based, discrete
-
event logistics and supply chain
simulation modeling architecture. This architecture will be based

on the work of Rossetti and Chan (2003),
Rossetti and Thomas (2004) and an investigation of the COUGAAR project to provide a test bed for the
development, testing, and evaluation of algorithms, heuristics, devices, and cognitive decision
-
making
requiremen
ts within sense and respond logistical networks.

According to Booch et al. (1999), a design framework is “an architectural pattern that provides an
extensible template for applications within a domain.” An object
-
oriented framework provides a set of
abstra
ct and concrete classes that can be extended via sub
-
classing or used directly to solve a particular
problem within a particular domain. The benefits of using an object
-
oriented approach include 1) object
-
oriented methods are specifically useful in modelin
g complex systems through hierarchical decomposition, 2)
object
-
oriented methods describe behavior, 3) object
-
oriented methods improve software reusability and cut
development time. Frameworks have been developed for graphical editors, drawing, CAD, and si
mulation.
The proposed framework will facilitate the evaluation of logistics modeling.

Because of the importance and complexity of logistic network modeling, numerous organizations have
developed simulation models for dynamically evaluating their logistics

networks. CNF Transportation, CSX
Transportation, and SABRE Technology Solutions all use simulation to analyze new designs, evaluate
existing operations within networks and traffic control, and for understanding the impact of scheduling and
dispatching ru
les. [Carson et al. (1997)] Ingalls (1998) discusses the value of simulation modeling in
analyzing supply chains. In particular, he argues that because of the stochastic nature of supply chains,
simulation can and should be used at operational (scheduling
), tactical (resource and capacity planning), and
strategic (evaluation of network and inventory performance) planning levels. He concludes that simulation is
the key to finding robust as opposed to optimal designs within a stochastic environment. Ingalls
and Kasales
(1999) discuss the development of Compaq Computers’s Supply Chain Analysis Tool (CSCAT) based on the
Arena simulation modeling environment. The tool is able to analyze the profitability of a product for a given
supply chain scenario and is able

to predict the customer service levels.

Umeda and Jones (1998) present an architecture for integrating supply chain simulation with enterprise
information systems and decision support systems through a communication data interface. The approach
taken fo
r the supply chain simulation is hierarchical and allows modeling at the operational, tactical, and
strategic levels. Swaminathan (1988) discusses using a multi
-
agent approach to investigate supply chain
dynamics. He indicates that simulation does provide
an effective practical approach to modeling supply chain
dynamics; however, the customized simulation models are specific on a particular problem and have a limited
reuse. In addition, it takes a long time to build a new simulation model. Hence, he propose
s a multi
-
agent
approach to overcome these two problems. The multi
-
agent system is a software component
-
based system
which contains a number of supply chain software agents such as retailers, manufacturers, transporters,
inventory policy, etc. These agent
s will be activated if certain events in the supply chain system occur. Thus,
each agent has the self
-
reactor behaviors to respond to the event occurring. Because of these advantages, our
framework will support an agent approach.

Under the Advanced Logist
ics Process and Ultralog programs, DARPA has been investigating
technologies for integrating distributed applications based on agent
-
based computing. COUGAAR is one the
results of this effort and provides an agent
-
based architecture for distributed computi
ng. COUGAAR
facilitates applications that are “large
-
scale, complex, and data intensive and must be efficient, distributed
and secure.” COUGAAR has been tested by utilizing it to build and test an “automated military logistics
planning and execution system
.” “COUGAAR problems are in general far too difficult to solve on a single
computer. These problems require user visibility into system operations, and occasional human feedback.
While important for policy direction and exception handling, human input must

not be a required part of
application performance: COUGAAR applications are typically autonomous and may not depend on timely
response from a human operator to produce timely results.” Essentially, COUGAAR was designed such that
autonomous computing agent
s can interact across a distributed computing infrastructure. While future sense
and respond
computing architectures
may rely on distributed operating systems such as that provided by
COUGAAR, COUGAAR does not provide the inherent capabilities found in tra
ditional simulation modeling
frameworks, i.e. it is not a simulation framework per se. Certainly, performance simulations of planned
agents can be performed with COUGAAR, but these types of simulations are quite different than traditional
operations resear
ch oriented simulations. Thus, we do not expect to utilize COUGAAR for the current effort,
but we may investigate whether or not COUGAAR can be exploited for the types of simulations that must be
performed and to help develop an understanding of how agents

should work within logistics systems.

We plan to build upon the traditional military supply chain simulations. For example, in military logistics
systems modeling, the Supply Chain Operational Performance Evaluator (SCOPE) simulation model was
developed f
or the review and evaluation of readiness based sparing models for the Navy and for the review of
efficient management and transportation policies for the Defense Logistics Agency. SCOPE models the
entire logistics support for spare parts from the retail e
chelon to the whole sale echelon of weapon systems by
monitoring the failures of the spare parts through four levels of indenture (Culosi 2001). SIMLOX is a
Systecon’s discrete event Monte
-
Carlo simulation model developed for simulating operational, mainte
nance
logistics, and their interactions for any technical systems (Systecon 2001). SIMLOX models features such as
full system and sub
-
system modeling capability without indenture constraints, data driven, modeling of
lateral re
-
supply and various repair ph
ilosophies (repair versus replacement). LogSAM modeling architecture
simulates critical aircraft generation functions based on known and verifiable aircraft
-
specific reliability and
maintainability statistics and can be used to test alternative supply and
maintenance processes under a wide
variety of resource
-
constrained situations. Despite these efforts, no comprehensive simulation framework
exists that encapsulates the new paradigm of S&RL.

Rossetti and Chan (2003) built a supply chain modeling framework
which contains logistics elements
like facility, warehouse, product etc. This Supply Chain Simulation Framework (SCSF) facilitates the
dynamic analysis of multi
-
echelon supply chain systems. The SCSF consists of 29 classes representing the
various elements

within a supply chain network. The most important of all relationships in the SCSF is the
Relationship Network. A Relationship Network is defined as a complex system of interconnected network
nodes that exchange material and information in order to provid
e material, products or services to the end
-
users (Rossetti and Chan 2003). Rossetti and Thomas (2004) built upon the SCSF to develop a modeling
architecture for spare parts supply chain networks, especially those related to multi
-
indentured weapon
systems
. This framework expands the notion of a facility to a behavioral agent
-
based plug
-
in architecture that
allows customization of facilities through user define behaviors. Within the first funding cycle of this multi
-
year effort, Rossetti is expanding upon t
his framework to model autonomous data collection elements within
supply chains. The goal of that effort is to provide modeling primitives that will encapsulate the behavior of
automatic data collection devices within logistics systems to enable analysts t
o evaluate their usefulness to
decision making within a military logistical context. These types of devices will become increasingly
important as our military is transformed by the concept of S&RL.


3.1.1

Anticipated Approach

This effort will build upon th
e work in Rossetti and Chan (2003), Rossetti and Thomas (2004), and
McGee, Rossetti, and Mason (2004). The design of the simulation framework will be implemented in Java.
This will include JavaDoc documentation. Simulation models will be implemented using
the framework that
represent an idealized problem scenario in S&RL. The models will serve as a test
-
bed for verification and
validation of the framework’s capabilities. Since this project involves extensive software development, we
will follow the iterativ
e software development process described in Larman (1998). The initial stage of the
process will involve the development of the software requirements and system specification through the use
of object
-
oriented analysis techniques and the Unified Modeling L
anguage, see Rumbaugh et al. (1999). This
will produce a language independent model of the system to be developed. The first software prototype will
then be developed to implement the basic simulation framework. Subsequent iterations of the development
pro
cess will evolve the prototype into a full
-
featured simulation framework. While the project will be
iterative in nature, the project is expected to roughly follow the following tasks and timeline.


Task 1: Background and Literature Review
-

This task will
involve the review of literature relevant to
military supply chain simulation. Each of the above
-
mentioned military simulation models (SCOPE,
SIMLOX, LOGSAM, LCOM, etc.) will be reviewed for the purpose of developing lists of classes of objects,
their attr
ibutes, their behaviors, and associations. In addition, recent commercial and academic supply chain
simulation solutions will be examined for functionality and for the identification of the fundamental supply
chain elements. These elements will be compared

with the current work by the authors in the Supply Chain
Simulation Framework, Object
-
Oriented Spare Parts Supply Chain Framework, and TIME. In addition,
relevant literature will be reviewed that integrates simulation and optimization. The deliverables fo
r this task
will be a section of the final report detailing the findings and the UML class diagrams related to the object
-
oriented design. This task is expected to take approximately 4 months.


Task 2: Problem Scenario Development
-

A key to this effort wi
ll be the development of a realistic problem
scenario from which the classes, their attributes, and their behaviors can be derived. This problem scenario
should be a military logistics problem involving the supply and re
-
supply of geographically disbursed
units
and involve transportation, inventory, and repair functions for multiple end
-
items and their support products.
The problem should be rich enough to contain questions of optimization and resource allocation over time. In
addition, the performance metr
ics for the problem should be clearly defined. Finally, the decision context
should involve human beings on an operational and tactical level. The key deliverable for this task will be a
section of the final report that details the problem scenario and dev
elops a plan for analyzing the key
components of the scenario. This task is expected to take 6 months and to run concurrently with task 1.


Task 3: Object
-
Oriented Design and Analysis


During this task we will develop and document the object
-
oriented desi
gn using UML diagrams possibly including class diagrams, interaction diagrams, and state
diagrams. The object
-
oriented models will be augmented and transformed into a form that can be
implemented on the computer. The focus will be in the data structures an
d algorithms needed to implement
the object models in Java. The designs will be evaluated on small test cases relevant to the problem scenario.
The key deliverable for this task will be a section of the final report that details the object models and
devel
ops a plan for implementing the design within the selected problem context. This task is expected to
take 4 months and occur after Task 2.


Task 4: Implementation
-

During this task, we expect to implement the problem scenario in a simulation
model for test
ing and evaluation by this project sub
-
team and then by the other teams. The key deliverable for
this task will be a section of the final report that details the use of the simulation model and develops a plan
for evaluating and experimenting with the fram
ework. This task is expected to take 10 months.


Task 5: Evaluation and Documentation


During this task, the framework will be evaluated within the context
of the problem scenario and additional implementation may be performed to facilitate the use by the

optimization team and the human decision making team. The framework will also be documented in the final
report and via standard software documentation mechanisms. The key deliverable for this task will be a
section of the final report that summarizes the

findings of the evaluation of the framework. This task is
expected to take approximately 10 months.


3.2


Adaptive Logistics Network Design and Optimization (
Mason, Chimka, Cassady, Pohl
)

The modeling and analysis of
traditional

military logistics network
s is based on the paradigm of nodes
and arcs. Nodes in this network typically represent manufacturers, warehouses, depots, and bases that exist at
fixed locations. The relationship of each node with respect to the other nodes in the network collectively
de
fines the echelon structure of the overall supply chain (Figure 1). Each base may use several depots, and
each base usually acts independently of one another. Further, each depot, as well as each warehouse, often
acts independently of their counterparts.

Manufacturer
Manufacturer
Manufacturer
Warehouse
Warehouse
Depot
Depot
Base

Base
Base
Base





Figure 1. Example of a Traditional Military Logistics Network


The arcs connecting the nodes represent transportation links between locations. Network flow occurs
when an item is transported from one echelon to an adjacent (typically downstream) echelon.
These items
(entities) are often considered to be either non
-
repairable (i.e., consumable) or repairable. The driving force
behind entity flow is base
-
level demand. This demand is often assumed to be static and either deterministic or
probabilistic with a
known underlying stationary distribution. In addition, item lead times are considered to
be static in most traditional military logistics network analyses. Demand fill rate and inventory levels
(position) are the two most frequently considered performance
metrics of interest.

With the evolving notion of S&RL, the structure of the traditional military logistics network, while still
being based primarily on nodes and arcs, will become both dynamic and adaptable. While some network
nodes will continue to follo
w the traditional role of a fixed supply chain location, other nodes representing
infantry units, maritime vessels, and so on, may “move.” Other nodes may be “temporary,” such as those
relating to contingencies that are only active/probable for some finite

amount of time. While some adaptable
network nodes can be thought of as “potential nodes,” other nodes can be “lost” with some non
-
zero
probability due to opportunities/missions that are no longer viable.

Recent and future developments in sensing technolo
gies will provide better/improved access to real
-
time
node locations and their status. The military’s vision of total asset visibility creates the potential for lateral
supply between nodes in the adaptable network. This, in turn, leads to increased networ
k connectivity and
hopefully reduced item lead times. In fact, arcs in an adaptable network can be permanent or temporal, added
or removed, created or lost. While current bases will be characterized by dynamic, but less variable demand,
potential bases/dem
and locations are sources of uncertainty in an adaptable network. Although traditional
performance metrics such as fill rate and inventory levels still apply, newer, more appropriate performance
metrics, some of which may be evaluated simultaneously within

the framework of a multi
-
objective problem,
must be developed for adaptable networks. For example, performance metrics such as network
responsiveness, vulnerability, and position may help to properly evaluate possible decision options in
adaptable network
s.


3.2.1

Proposed Research Approach

We propose to
create a framework that can be used to construct mathematical and logical models of
sense and respond (S&RL) military logistics networks
. We envision three “scenarios” of research focus that
correspond to
the Department of Homeland Security’s threat level warning scale:


Yellow Threat Level Scenario
: Under this scenario, the majority of network nodes and arcs are known and
fixed, and demand requirements are primarily deterministic. The primary focus here is

to transport items
to/from various supply chain echelons in the course of conducting “normal” military operations. Our research
efforts will involve the
development of a suite of mathematical optimization models that can assist in the
definition of logist
ics management policies that optimize S&RL military logistics network “day
-
to
-
day”
operational performance and maximize network responsiveness.


Orange Threat Level Scenario
: This scenario results when an apparent threat appears to be
growing/developing at

one or more locations encompassed by the S&RL military logistics network. A
primary research focus here involves the probability of a given node becoming active within the network, as
well as the effect of this potential node’s activity on transportation
network connectivity and item (inventory)
placement/staging decisions (i.e., contingency planning). We propose here to
create a suite of mathematical
optimization models that can assist in the definition of logistics management policies that maximize netwo
rk
responsiveness and maximize network robustness in the face of contingencies.


Red Threat Level Scenario
: Under this highest level of threat, the S&R military logistics network’s structure
and connectivity may be unstable, as we are primarily acting/reac
ting to an actual threat or attack on one or
more network nodes/locations. Our research focus here is to
develop a suite of mathematical models that can
help to determine appropriate means of restoring S&R military logistics network infrastructure connecti
vity,
thereby minimizing future network vulnerability and maximizing network responsiveness to dynamically
changing conditions.


For all three scenarios of interest, we must also
define appropriate performance metrics for S&RL
military logistics networks

t
hat properly characterize the stated objective functions of interest. These metrics
include those associated with traditional analyses, as well as new measures of responsiveness, vulnerability,
and position. Through the course of our model development effo
rts, we will determine the input parameter
requirements for our mathematical models, as well as establish both the source of each required model input
and the frequency with which each parameter is/should be updated in our modeling efforts. The potential
e
xists here to leverage on
-
going research in sensing technologies (such as RFID and Auto
-
ID) and
information fusion to automatically and dynamically obtain/update model input parameters.


3.2.2

Potential Solution Methodologies

The set of mathematical optimi
zation models formulated in this effort will include deterministic and
stochastic optimization models. The tractability of our formulated mathematical optimization models will
directly affect the selection of potential solution methodologies for analyzing
each model. The deterministic
models that we will develop will most likely contain one or more discrete variables in addition to non
-
linear
constraints and/or objective functions. Attempts will be made to increase the tractability of these models
through t
he linearization of non
-
linear constraints/objectives, thereby resulting in mixed
-
integer linear
programs that can be analyzed using traditional branch
-
and
-
bound solutions approaches. However, less
tractable, non
-
linear formulations will most probably be a
nalyzed using a combination of decomposition
-
based approaches, greedy heuristics, and metaheuristic approaches such as genetic algorithms and Tabu
search. In addition, some new heuristics may need to be developed to analyze our suite of optimization
proble
ms. In the stochastic models that we will develop, we will utilize (to the extent possible) stationary
stochastic processes and assume independence between system elements to maintain reasonable tractability.

Because each of our optimization models will be

based on some set of simplifying assumptions, we will
utilize the simulation test
-
bed created in other aspects of this effort to evaluate the quality of our solution
approaches. In some cases, we will pursue the use of simulation
-
based optimization heuris
tics as an
alternative to our mathematical modeling approach. We will also explore the use of the simulation test
-
bed as
an experimental tool that can be used to create approximate mathematical models of some aspects of network
performance.


3.3


Cognitive

Decision Support in a Sense and Respond Environment
(
Nachtmann, Buyurgan,
Chimka, Hill, Militello, Nam, Pohl
)

Information architectures for network
-
centric logistics rely heavily on automation for achieving the goals
of adaptive, rapid response to support

operations. S&RL as envisioned by the OSD Office of Force
Transformation, emphasizes total asset visibility, automated planning through agents, and flexible supply and
transportation to achieve these goals. What is missing in this architecture is the rol
e of the human actor, or
team of actors, at the edge of the logistics infosphere. The logisticians who will operate the S&RL network
must collaborate from multiple locations, and they will need carefully crafted tools and procedures to do their
work effect
ively. For example, human interaction with agent societies and other networked artifacts present
special challenges for coherent decision making and coordinated action. The classic problem of evaluating
the proper assignment of functions between human bein
gs and machines have special resonance in the S&RL
context because of the complexity of the emerging net
-
centric planning problem, the requirement to support
rapid re
-
planning, and the uncertainty of logistics needs in the dynamic modern battlefield.

It i
s well understood that automated technologies that fail to inform users of agent actions and system
state increase risk, particularly in novel, unpredictable situations (Billings, 1996; Woods, Tittle, Feil, &
Roessler, 2004). While many logistics activitie
s may be routine and predictable, the S&RL of interest for this
research are not. Logistics planning in the context of war must be very flexible. Plans must be adapted
quickly and in response to unexpected events. This generally happens in the context of
distributed teams
facing many coordination challenges including geographical distance, disparate time zones, and the
transmission of sensitive and classified information. Successful S&RL depends not only on effective agent
technologies, but also on smooth
coordination between agent technologies and human teams.

This portion of the research effort focuses on the transformational military objective of information
superiority through enhanced dynamic decision support. Specifically we will integrate course of
action
analysis, knowledge management and mining, and pattern recognition and learning into the network.
Enhanced cognitive decision support will improve the logistician’s ability to convert data and information
into relevant knowledge and understanding. I
mpact analysis of enhanced decision support will be measured
through the observation of system performance. Here we focus on the human side of the S&RL network
through the development and study of efficient and effective decision models, a realistic artifi
cial intelligence
agent, improved human computer interaction, and empirical research on distributed decision
-
making and
collaboration within this new computing context.

We have broken this portion of the research effort into four distinct components. Firs
t, flexible and
adaptive decision models need to be developed and tested within an S&RL network. Second, since we will
not have the ability to interact with all levels of human decision makers involved in the true S&RL
environment, we will develop and impl
ement an artificial intelligence agent to interact with and interpret data
and information from the other system components in order to emulate this new and complex human decision
process. Third, we will study the human computer interaction in this dynamic

environment in order enhance
the information superiority necessary for successful network operations. Finally, the fourth component of this
research will produce frameworks for understanding the human implications of candidate S&RL networks
and unified te
st
-
beds using empirical research on distributed decision
-
making and collaboration within this
new computing context. The following sections provide relevant background and the anticipated approach
for each of the four components.


3.3.1

Decision Model Dev
elopment

(Nachtmann, Chimka)

The main objective associated with this subcomponent is to understand and model human decision
processes with respect to the overarching goal of obtaining a S&RL organizational model for the United
States Air Force. How will pr
eferences and information be used by people to choose actions? How should
past experience be used to anticipate the future? Answers to these questions, and the understanding of human
expectation processes which comes with them, should improve the programmi
ng of prediction models or,
more generally, autonomic logistics.

Theories produced by cognitive science research make available knowledge of the discovery process:
"New alternatives are discovered by heuristic search through problem spaces (Simon, 1997, p.

322)." An
important component of these procedures is some way of deciding when a satisfactory alternative has been
found. Standards of satisfaction tend to fall as it proves difficult to find improved alternatives, and criterion
for deciding when a decisi
on should be made can be many
-
sided. These same issues are of course relevant to
software design for operations research, making them even more important to modeling a Sense
-
and
-
Respond
Air Force.

Further, some mechanism should attend to needs both periodi
c and real
-
time which can be met with the
aid of sensors that detect external threats. Here are opportunities to consider remote diagnostics and data
mining tools such as neural networks: "An excellent S&RL leader is also a decision
-
maker who makes
organiz
ational decisions that are based on recognizing emerging patterns faster than others (Menotti, 2004)."


Major Tasks
-

Decision Model Development



Explore human preferences and information sources being used by decision makers (Data
collection)



Examine how p
ast experience should be used to anticipate the future (Data synthesis)



Develop understanding of human expectation processes (Modeling)



Develop prediction models (Anticipated outcome)


3.3.2

Artificial Intelligence Agent
(Buyurgan, Chimka )

The artificial
intelligence agent will be developed in order to sustain a knowledge
-
driven specialized
decision support system and help to create knowledge for real
-
time decision models. The agent will have the
intrinsic ability to handle the complexity of the human deci
sion process as well as analyzing voluminous data
from the other system components, extracting knowledge from the data, intelligently realizing and
distinguishing the existing status, and rationally supporting the decisions made. It will interact with the
data
sources by monitoring the inputs from other components,
recommend
actions and explain the reasons for
adopting an action. It will help to discover the hidden relationships and patterns in data. The agent will also
act as a
brain

in foreseeing decision

support models in order to emulate the humanlike thinking and reacting
in every levels of decision making process.

The intelligence of the developed agent will consist of three components: 1) knowledge of symptoms and
indicators related to decision makin
g process and the environment under different circumstances, 2)
understanding of the relations among symptoms and of problems and solutions within the process and
environment, and 3)
skill

or methods for solving some of the problems. The agent will be in i
nteraction with a

human expert who has expertise in different levels of decision making process in order to capture the expert’s
knowledge and rule and relationship information (
expertise
).


Major Tasks
-

Artificial Intelligence Agent




Obtain knowledge of

symptoms and indicators related to decision making process and the
environment under different circumstances (Data collection)



Develop understanding of the relations among symptoms and of problems and solutions within the
process and environment (Data syn
thesis)



Analyze methods for solving above problems (Modeling)



Develop expert system to capture the expert’s knowledge and rule and relationship information
(Anticipated outcome)


3.3.3

Human Computer Interaction
(Nam)

As the amount of information available

to logistics teams grows exponentially, much attention has been
paid to intelligent assistance to filter and coherently organize unrelated and scattered information, and finally
help logistics teams respond effectively. Such rapid growth of the agent tech
nology applications has
generated a need for methods to systematically design interactions between human users and agents. When
agents are used to support the delegated information processing on behalf of the human user, one major
challenge is to identify
the appropriate form of interaction between agents and the human user (Bradshaw,
1997).

Specifically, the human
-
agent interaction objectives are two
-
fold. First, to systematically examine the
appropriate form of interactions between the human user and age
nt teams, including the way that the human
user instructs and controls the agent(s), the nature of the feedback from the agent to the user, and the manner
by which the agent provides the user with information. Second, we will design intelligent user interf
aces
specifically targeted to the needs of agent
-
based logistics team decision aiding systems. These new intelligent
interfaces will lead to significantly higher productivity and reduced cognitive workload for logisticians. This
research will have a fundam
ental impact on all agent
-
assisted collaboration efforts, because of the focus on
the human
-
agent interaction. The design principles and guidelines produced in this research will apply to
many other categories of human
-
agent collaboration.


Major Tasks
-

Human Computer Interaction



Examine interactions between the human user and computer interfaces (Data collection)



Develop understanding of the way that the human user instructs and controls the (Data
synthesis)agent(s), the nature of the feedback from the a
gent to the user, and the manner by which
the agent provides the user with information



Translate this knowledge into practical interface changes (Modeling)



Design intelligent user interfaces (Anticipated outcome)


3.3.4

Collaborative Decision Making in a S
ense and Respond Environment
(Hill, Militello)

The research will be keyed to the other elements of the Cognitive Decision Support segment of the S&RL

research effort and will derive requirements for team experiments and evaluation studies from it. We expec
t
that a small number of problem sets with significant scope for examination of human performance in S&RL
networking scenarios will emerge for detailed analysis either in controlled laboratory simulations and/or
applied evaluation studies. We also expect t
hat a common test
-
bed and experimental scenario for team/group
collaboration and decision
-
making will be used in order to leverage related research from multiple locations.
The research will draw from recent developments in "distributed cognition," collabo
rative decision making,
and coordination science. An interdisciplinary approach will be used, ultimately aimed at refining user/group
interfaces and work procedures that will reduce the risk and improve the effectiveness of S&RL capabilities
as they emerge
. Requirements for empirical research on the human aspects of S&RL deployment will also be
forthcoming from the various experiments and demonstrations planned for S&RL over the next year.

The work will be carried out in three phases. First, requirements f
or human
-
centered aspects of S&RL
capability will be identified from subject matter experts, guidance documents, and analyses of relevant
research literature within the domain. Subject matter experts will include logistics planners at the wing and
theater

levels of operation as well as owners and champions of S&RL in government, industry, and academia.
Technologists producing S&RL capabilities will be surveyed to identify technologies deployable in the short
term (e.g., existing tools) and long term (e.g.,

emerging tools). Experiments and demonstrations for S&RL
will be monitored to validate and refine specific requirements, emphasizing the role of the distributed
logistics team in net
-
centric operations. Second, research strategies aimed at exhibiting the
problems,
potential solutions, and opportunities of selected S&RL solutions will be defined. We can expect to
document problems of incomplete and rapidly changing information, ambiguous command and control
procedures, and inadequate feedback on the effects

of logistics support strategies on operational outcome,
among others. For the most significant problem sets, we will derive experiments to illustrate potential
workarounds or direct solutions (such as a common operating picture) or evaluation studies show
ing how
S&RL solutions might fail or produce unwanted effects. In the third phase, we will implement a series of
experiments, either in controlled laboratory conditions or in applied settings, to illustrate these solutions or
workarounds. The results wil
l be used to reduce risk and/or increase the utility of S&RL solutions that might
be deployed for real world use. The outgrowth is effective deployment, considering both the human actor and
S&RL technology in a socio
-
technical context and rooted in real wo
rld applications.

Dr. Ray Hill of the Advanced Modeling, Optimization, and Systems (AMOS) laboratory, WSU, will be
PI on this portion of the effort. Cooperative arrangements will be established with the WSU Department of
Psychology for experimental desig
n support and research implementation as required. Test subjects will be
drawn from student populations at the UofA, WSU and the Air Force Institute of Technology. The UDRI will
conduct user analysis in the first two phases of this research to inform exper
iments conducted in Phase III.
User analysis will include key players likely to be present in challenging sense and respond situations such as
war planning, dynamic logistics re
-
planning, or re
-
tasking to accommodate loss of resources. User analysis
will e
mploy knowledge elicitation methodologies aimed at analyzing team coordination.


3.4


Project Integration and Timelines

The focused research efforts provide comprehensive coverage of the S&RL concepts from a
human
-
centered
perspective as specified by the U
SAF/AFRL. Each of the research teams supporting the three major
efforts are constructed in such a way as to provide synergy between the efforts. Each research team has at
least one collaborator who is a member of each of the other teams. In addition, Dr. P
ohl will serve as an
integrator and facilitator for each of the research teams. The Wright State and University of Dayton activities
will be handled through a subcontract from the UofA. Table 1 indicates this coverage:


Table
1
: Res
earch Area Coverage


S&RL
Concepts



Research Projects

1

2

3

4

5

Researchers

3.1 Modeling and Simulation
Framework











Rossetti, Cassady, Pohl

3.2 Adaptive Logistics Network
Optimization









Mason, Cassady, Chimka, Pohl

3.3 Cognitive Decision

Support








Nachtmann, Buyergan, Chimka, Hill, Militello,
Pohl


The initial two years of the project is divided into tasks associated with each of the initial problem
statements. Table 2 presents the expected activities for the initial set of research

problem statements. Each
task will have two required milestones, a presentation review at the end of year 1 and a report at the end of
year 2. Future funded tasks will have similar requirements. The investigators involved in the tasks may set
other milest
ones as necessary for the completion of the tasks. Standard NSF reporting requirements will also
be met for the project as a whole.


Table 2: Project Area Timeline


Months after award

Research Area

2

4

6

8

10

12

14

16

18

20

22

24

3.1 Modeling and Simulat
ion Framework













Literature Review













Scenario Development













Object Oriented Design and Analysis













Implementation













Evaluation and Documentation













3.2 Adaptive Logistics Network Optimization













Literature Review













Scenario Development













Model Formulation













Data Collection













Model Analysis and Documentation













3.3 Cognitive Decision Support













Literature Review













Experimental Design and Data Collection













Data Synthesis













Modeling and Analysis













Documentation














3.5


Related Work and Project Dissemination Plan

In addition to the partnerships discussed in this proposal, w
e will explore the potential for a wider
collaborative effort on the human aspects of S&RL technologies. By linking our work with related work at
Penn State University, North Carolina A&T, Air Force Office of Scientific Research (AFOSR), and AFRL,
we hope
to multiply the payoff from this investment. Penn State is developing visualization tools for
distributed decision
-
making aimed at the crisis response problem. North Carolina A&T is developing similar
tools to support heterogeneous team in the same problem

domain. AFOSR has sponsored a variety of
universities for development of tools to support coordinated crisis response, also including the theme of
cross
-
cultural decision
-
making. The Cognitive Interfaces Branch (AFRL/HECS) is establishing a group
decisio
n
-
making laboratory at WSU (Department of Psychology) for empirical research on similar group
decision
-
making problems. In addition, AFRL/HEAL is studying emergency response logistics through the
University of Dayton Research Institute using real
-
world exe
rcises in the local area to uncover opportunities
for applied research and training solutions.

The project dissemination plan includes a project website, publications, presentations, publicity, reports,
and technology transfer. A project website within th
e current CELDi web
-
site will be developed to
disseminate the findings and will include this proposal, working reports, conference papers, journal papers,
and any applicable prototype software that implements the procedures developed within the project. Th
e
results will also be published in traditional peer reviewed journals such as
IIE Transactions, Journal of
Defense Modeling and Simulation, Naval Research Logistics,
and
Military Operations Research..

The results
will also be presented at conferences such

as the
Industrial Engineering Research Conference, INFORMS,
RAMS, MORSS, Winter Simulation Conference,
and the

Annual International Occupational Ergonomics and
Safety Conference.


4.


Intellectual Merit and Broader Impacts

The
intellectual merit

of this p
roposal will be based on the fundamental research performed in support of
the proposed goals. This research will advance the state of knowledge concerning the performance prediction
of future military logistical networks. Specific expected contributions in
clude:

1.

New modeling paradigms for supply chain simulation will be developed and implemented in useful
software. This research will further the application of simulation methods in general and possibly
become a standard framework for modeling future militar
y supply chains.

2.

New simulation methodologies, mathematical models, and techniques for the optimization,
performance evaluation, and improvement of future military logistics networks.

3.

New methods of modeling and incorporating human performance issues and c
ollaborative decision
making within an S&RL environment.
The results will be used to reduce risk and/or increase the
utility of S&RL solutions that might be deployed for real world use.



These contributions will provide basic research and enhanced underst
anding of the human aspects of the
S&RL archetype for AFRL’s product development efforts. Parallel developments at AFRL/HEAL under the
Technology Applications for S&RL Program and AFRL/IF under the Joint Battlespace Infosphere will be
integrated under this

effort to assure maximum technology transition and research payoff in military
applications. Thus, the
broader impact

of this basic research will be magnified through these technology
transfer activities with the United States Air Force. S&RL will emplace

new information tools in
organizations so as to promote rapid, adaptive, and flexible business processes to gain competitive advantage.
We believe that the technologies underlying the information technology aspects of S&RL will find
application in the com
mercial sector as well. The human
-
centered aspects of collaboration within the
infosphere seem to have special significance for dual
-
use application
.

In addition, Arkansas is a NSF designated EPSCOR state; therefore, the funding for this proposal will
di
rectly benefit the State of Arkansas’ research infrastructure. The funding will directly support graduate
students in each of these areas and will thus increase the production of qualified scientists and engineers
available in the United States. CELDi has
access to state of the art computing and laboratory facilities, which
will be more than sufficient for the scope of the proposed work. The UofA is an equal opportunity employer
and values diversity within its faculty and students. Every effort will be made

to staff the project with
graduate students who represent the diversity of the United States and especially minority and under
represented socio
-
economic groups.


5.


Results from Prior NSF Support


John English has served as PI and Executive Director for

the NSF
-
sponsored multi
-
university I/UCRC
Grant #0214478, Collaborative: Center for Engineering Logistics and Distribution. In the first two years of
the Center’s existence a total of 48 publications have resulted with a significant number being published

in
partnership with an industrial sponsor. The Center supported more than 23 undergraduate students and more
than 30 graduate students in research activities. At least four graduates involved in Center research have been
hired by sponsor organizations.


R
ichard Cassady served as co
-
PI on an NSF
-
sponsored project involving human reliability modeling


An Investigation of the Effects of Total Body Fatigue on Human Reliability (EEC
-
9725904, June 15, 1997
-

May 31, 1999, $67,807). This grant was a Research Opp
ortunity Award for establishing Mississippi State
University as part of the NSF Center for Ergonomics. His role in this project was to develop the human
reliability models and to supervise the human reliability data collection and analysis phases. Multiple

conference publications and a Masters thesis resulted from this project.

_______________________________________________________________________









References

1. Solis, William M., GAO
-
04
-
305R, “Defense Logistics: Preliminary Observations on

the Effe
ctiveness of Logistics Activities during Operation Iraqi Freedom”, 18

December 2003.

2. Gilmore, Gerry, “Military’s Logistics Systems Found Wanting in Iraq War”,

American Force Information Service, 21 January 2004.

3. Operational Sense and Respond Logistic
s: Coevolution of an Adaptive Enterprise

Capability, Office of Force Transformation, Concept Document (Long Version), 6

May 2004.

4. Bagchi, S., S. J., Buckley, and G. Lin. 1998. Experience using the IBM supply chain

simulator. In the
Proceedings of the 19
99 Winter Simulation Conference
, ed.

Medeiros, D.J.; Watson, E.F.; Carson, J.S.; Manivan
-
nan, M.S, 1387
-
1394,

Piscataway, New Jersey: Insti
-
tute of Electrical and Electronic Engineers.

5. Booch, G. and Rumbaugh, J., and Jacobson (1999)
The Unified Modeling

Language

User Guide
, Addison
-
Wesley, Reading Massachusetts.

6. Carson, J.C., Manivannan, M.S., Miller, E., Brazier, M., and Ratliff, H.D. 1997.

“Panel on transportation and logistics modeling”, In the
Proceedings of the 1997

Winter Simulation Conference
,
ed. S. Andradóttir, K. J. Healy, D. H. Withers, and B.

L. Nelson, 1997, pp. 1244
-
1250, Piscataway, New Jersey: Institute of Electrical and

Electronic Engineers.

7. Culosi, S. 2001. “A Simulation for Evaluating the Operational Readiness of the

Supply Chain:

Analyst Manual”, Logistics Management Institute.

8. Helsinger, A., Thome, M., and Wright, T. 2004. “Cougaar: A Scalable, Distributed

Multi
-
Agent Architecture”,
International Conference on Systems, Man and

Cybernetics
, October 10
-
13, The Hague, The Netherl
ands.

9. Ingalls, R.G. “The value of simulation in modeling supply chains”, In the

Proceedings of the 1998 Winter Simulation Conference
, ed.
D.J. Medeiros, E.F.

Watson, J.S. Carson and M.S. Manivannan, pp. 1371
-
1375, Piscataway, New Jersey:

Institute of El
ectrical and Electronic Engineers.

10. Ingalls, R.G., and C. Kasales, 1999. “CSCAT: The Compaq supply chain analysis

tool”, In the
Proceedings of the 1999 Winter Simulation Conference
, ed. Farrington,

P.A.; Black Nembhard, H.; Sturrock, D.T.; Evans, G.W, 1
201
-
1206, Piscataway, New

Jersey: Institute of Electrical and Electronic Engineers.

11. Gamma, E., Helm, R., Johnson, R., and Vlissides, J. (1995)
Design Patterns

Elements of Reusable Object
-
Oriented Software
, Addison
-
Wesley Publishing

Company.

12. McGee,
J., Rossetti, M. D., Mason, S. (2004) “Simulating Transportation Practices in

Multi
-
Indenture Multi
-
Echelon (MIME) Systems”, to appear in the
Proceedings of

the 2004 Winter Simulation Conference
, R .G. Ingalls, M. D. Rossetti, J. S. Smith,

and B. A. Peters
, eds., Piscataway, New Jersey: Institute of Electrical and Electronics

Engineers.

13.
Rossetti, M. D. and Chan, H. T., 2003. “A Prototype Object
-
Oriented Supply Chain

Simulation Framework”, In the
Proceedings of the 2003 Winter Simulation

Conference
, eds.

S. Chick, P. J. Sanchez, D. Ferrin, and D. J. Morrice, New Orleans,

________________________________________________________________________







Louisiana, 2003, 1612
-
1620, Institute of Electrical and Electronic Engineers,

Piscataway. New Jersey.

14. Ro
ssetti, M. D. and Thomas, S. 2004. “Object
-
Oriented Multi
-
Indenture Multi
-

Echelon Spare Parts Supply Chain Simulation Model” submitted to the
International

Journal of Modeling and Simulation.

15. Swaminathan, J.M. 1998. “Modeling supply chain dynamics: A
multi
-
agent

approach”,
Decision Sciences
, Vol. 29 No. 3, Summer, 607
-
632.

16. Systecon 2001, , SIMLOXv2 logistics simulation from Systecon [Homepage of

Systecon], [Online]. Available:
http://www.systecon.co.uk/simlox.htm [2002
].

17. Umeda, S. and Jones, A.

1998. “An Integration Test
-
Bed System for Supply Chain

Management,”
Proceedings of the 1998 Winter Simulation Conference
(ed. D.J.

Medeiros, E.F. Watson, J.S. Carson and M.S. Manivannan), ACM/SIGSIM, ASA,

IEEE/CS, IEEE/SMCS, IIE, INFORMS/CS, NIST and SCS,

pp. 1377
-
1385.



Biographical Sketch

Edward A. Pohl

University of Arkansas

Department of Indust
rial Engineering




479
-
575
-
6042

(of
fice
)

4207 Bell Engineering Center





479
-
575
-
8431 (fax)

Fayetteville, AR 72701






epohl@engr.uark.edu

Professional Preparation


Academic:
University of Arizona


Systems and Industrial Engineer
ing


Ph.D.


1995



University of Arizona


Reliability Engineering



MS


1993



A
ir Force Institute of Tech.

Systems Engineerin
g



MS


1988



University of Dayton


Engineering Management



MS


1988



Boston University


Electrical Engineering



BS


1984


Military:


Air Command and Staff College


1998



Squadron Officers School

1990

Professional History

Associate Professor,
University of Arkansas
, Department
of Industrial Engineering, 2004


Present

Deputy Director, Operations Research Center of Excellence, United States Military Academy, June 2003
-

Dec 2003

Associate Professor, United States Military Academy, Department of Systems Engineering, Aug 2003


Dec

2003

Assistant Professor, United States Military Academy, Department of Systems Engineering, 2001


2003

Operations Research Analyst, Office of the Secretary of Defense, Program Analysis & Evaluation, 1998
-

2001

Assistant Professor, Air Force Institute o
f Technology, Department of Aeronautics and Astronautics, 1995


1998

Logistics Analysis Manager, Air Force Operational Test and Evaluation Center, 1989


1991

Training Systems Engineer, B
-
2 System Program Office, 1984
-

1987



Publications


Most Relevant


Pohl, E.A., Cassady, C.R., Kwinn, M., “A Selective Maintenance Model for Serial Manufacturing Systems Involving
Multiple Maintenance Actions”,
Proceedings of the 17th International Conference on Production Research
, Blacksburg,

VA, Aug 2003.


Cassady, C
.R., Pohl, E.A., Murdock, W.P., “Selective Maintenance Modeling for Industrial Systems”
Journal of Quality
in Maintenance Engineering,
Vol 7 No. 2, pp 104
-

117, 2001.


Cassady, C.R., Murdock, W.P., Pohl, E.A., “Selective Maintenance for Support Equipmen
t Involving Multiple
Maintenance Actions”
European Journal of Operations Research.,
Vol 129 No. 2 pp 252
-
258, 2001
.


Reineke, D.M., Pohl, E.A., Murdock, W.P., “Maintenance Policy Cost Analysis for a Series System with Highly
Censored Data”
IEEE Transaction
s on Reliability,

Vol. 48, No. 4, pp. 413
-

419, 1999.


Kramer, S.C., Neher, RE., Pohl, E.A., Smith, E.P., “Surveillance Plan for Monitoring the Shelf Life of Systems with
Degradation,”
Quality Engineering
, Vol. 11(2), pp. 309
-
316, (1998
-
1999)


Publicatio
ns


Other Significant


Cassady, C.R., Pohl, E.A., Jin, S., "Managing Availability Improvement Efforts with Importance Measures and
Optimization", Accepted for publication in the
IMA Journal of Management Mathematics on Maintenance, Replacement
and Reliab
ility,
2003
.


C
assady, C.R., Takashi, I.G., Pohl, E.A., “Reliability Analysis for Intermittently Used Products”,
International Journal
of Modeling and Simulation,

Vol 23, No. 4 pp 234
-
239, 2003.


Vanden Bosh, P.M., Dietz, D.C,.
Pohl, E.A., “Moment Matching

Using a Family of Phase
-
Type Distributions”,
Communications in Statistics: Stochastic Models
, Vol. 16 No. 3
-
4, pp. 391
-

398, 2000.


Pohl E.A., and Dietrich, D.L. “Optimal Stress Screening Strategies for Multi
-
Component Systems Under Warranty: The
Case o
f Phase
-
Type Lifetimes”,
Annals of Operations Research Special Volume on Reliability and Maintainability in
Production Control
, Vol. 91, pp. 137
-
161, 1999.


Durkee, D.P, Pohl, E.A., Mykytka, E.F., “Sensitivity Analysis of Availability Estimates to Input Da
ta Characterization
Using Design of Experiments,”
Quality and Reliability Engineering International,

Vol. 14, pp. 311
-
317, 1998.


Synergistic Activities


Associate Editor, Journal of Military Operations Research, 2002


Present

Associate Editor, IEEE Trans
actions on Reliability, 2003


Present

Department

Editor, IIE Transactions

Focus Issue on Quality and Reliability
, 2003


Present

GOAL Team, Continued Intellectual Development, United States Military Academy, 2001, 2002

Wright
-
Step Volunteer; Taught Introd
uctory Engineering and Math Classes to Minority Students interested in the science
and engineering during summer. (1995, 1996, 1997, 1998)

Lincoln Elementary School Mentor, Served as a mentor to a group of 6th Grade Students interested in science and
en
gineering, introduce the students to the profession. 1996, 1997, 1998




Collaborators & Other Affiliations


Collaborators:

Royce Bowden (Mississippi State University), Bee Carlton (Presbyterian College), C.R. Cassady (The
University of Arkansas, UA), J.W
. Chrissis, (Air Force Institute of Technology, AFIT), D. Dietz (Quest), Patrick Driscoll
(United States Military Academy, USMA), Bobbie Foote (USMA), Michael Kwinn (USMA), Scott Mason (UA),
Michael McGinnis (USMA), Paul Murdock (Air Force Research Labs),
Edward Mykytka (University of Dayton), H.
Nachtmann (UA), Gregory Parnell (USMA), Dave Reineke (University of Wisconsin
-
Lacrosse), M.L. Shelly (AFIT),
Pete Vanden Bosch (USAF)
Graduate Advisor:

Duane Dietrich (Professor Emeritus, University of Arizona),
Th
esis
Advisees:

Neher, R.E (USAF), Mumford D .A. (Air Mobility Command),, Durkee, D.P. (USAF), Rummer, M.(USAF),
Tran, Thuan (USAF), Ruflin, Scott (USAF), Payne, Mike (AFSAA) Boerrigter, Dean (USAF) Schriver, Todd (AFIT),
Number of Graduate Students Advise
d:

9







Biographical Sketch

Scott J. Mason


University of Arkansas

Department of Industrial Engineering





479
-
575
-
5521 (office)

4207 Bell Engineering Center






479
-
575
-
8431 (fax)

Fayetteville, AR 72701






mason@uark.edu


Professional Preparatio
n


Arizona State University

Industrial Engineering

Ph.D. 2000

The University of Texas at Austin

Operations Research

M.S. 1995

The University of Texas at Austin

Mechanical Engineering

B.S. 1993



Appointments


University of Arkansas


Associate Department He
ad


Aug. 2004


Present

University of Arkansas


Assistant Professor



Aug. 2000


Present

Arizona State University

Graduate Research Assistant


Aug. 1997


July 2000

Wright Williams & Kelly

Software Applications Engineering

Aug. 1999


Mar. 2000

Intel Corp
oration

Research Assistant

Apr. 1998


Feb. 1999

Abbie Gregg, Inc.

Senior Modeling Engineer

Mar. 1997


Aug. 1999

Advanced Micro Devices

Operational Modeling Engineer

May 1995


Mar. 1997


Publications


Most Closely Related


Mason, S.J., Fowler, J.W., Car
lyle, W.M., 2002, A modified shifting bottleneck heuristic for minimizing total
weighted tardiness in complex job shops,
Journal of Scheduling
, 5 (3), 247
-
262.

Mason, S.J.,
Oey, K.
, 2003, Scheduling complex job shops using disjunctive graphs: a cycle elim
ination
procedure,
International Journal of Production Research
, 41 (5), 981

994.

Mason, S.J., Qu, P.
, Kutanoglu, E., Fowler, J.W., 2004, The single machine multiple orders per job
scheduling problem,
IIE Transactions on Scheduling and Logistics
, in review
.

Qu, P., Mason, S.J., 2004, Metaheuristics for multi
-
order jobs formation and scheduling in 300
-
mm wafer
fabs,
IEEE Transactions on Semiconductor Manufacturing
, in review.

Tovia, F., Mason, S.J., Ramasami, B., 2004, A scheduling heuristic for maximizing w
irebonder throughput,
IEEE Transactions on Electronics Packaging Manufacturing
, to appear.


Publications


Other Significant


Fowler, J.W., Hogg, G.L., Mason, S.J., 2002, Workload control in the semiconductor industry,
Production,
Planning, and Control
, 13

(7), 568
-
578.

Kurz, M.E., Mason, S.J., 2004, Minimizing total weighted tardiness on a batch
-
processing machine with
incompatible job families and job ready times,
Journal of Heuristics,
in review.

Mason, S.J., Fowler, J.W., Carlyle, W.M., Montgomery, D.C.
, 2004, Heuristics for minimizing total weighted
tardiness in complex job shops,
International Journal of Production Research
, in review.

Mason, S.J., Jin, S., Wessels, C., 2004, Rescheduling strategies for minimizing total weighted tardiness in
complex jo
b shops,
International Journal of Production Research
, 42 (3), 613
-
628.

Pfund, M.E., Balasubramanian, H., Fowler, J.W., Mason, S.J., Rose, O., 2004, A multi
-
objective approach to
scheduling complex job
-
shops,
Journal of Scheduling
, in review.


Synergistic
Activities


Funded Research in Military Logistics



Quantifying the Effect of Commercial Transportation Practices in Military Supply Chains, Air Force
Research Laboratory



Commercial Practices as Applied to Total Asset Visibility (TAV), Air Force Research La
boratory



Multi
-
State Selective Maintenance Decisions, Air Force Research Laboratory



Fleet
-
Level Selective Maintenance and Aircraft Scheduling, Air Force Research Laboratory


Collaborators & Other Affiliations


Collaborators:



W. Matt Carlyle, Naval Postgr
aduate School

Michael H. Cole, Montana State University

John W. Fowler, Arizona State University

Gary Hogg, Arizona State University

Song Jin, University of Arkansas

Mary E. Kurz, Clemson University

Erhan Kutanoglu, The University of Texas at Austin

Doug M
ontgomery, Arizona State University

Kasin Oey, University of Arkansas

Michele Pfund, Arizona State University

Peng Qu, Advanced Micro Devices

Oliver Rose, University of Wuerzburg

Chris Wessels, ABF Freightways


Graduate Advisor:


John W. Fowler (Professor,

Arizona State University)


Thesis Advisees:


K
asin

Oey

P. M
auricio

Ribera

Peng

Qu

Song

Jin

T
ze
-
C
hen

Hau

T
homas

Yeung

Chris Wessels

Vishnu Erramilli

Jun Jia

Joo Hyoung Kim

Eray Cakici


Dissertation Advisees
:


P
eng Qu

G
hazi

Magableh

Thomas Yeung

Bashyam Ram
asami

Jagadish Jampani


Graduate Students Advised:

15


BIOGRAPHICAL SKETCH

Heather Nachtmann

University of Arkansas

Department of Industrial Engineering 479
-
575
-
5857 (ofc)

4207 Bell Engineering Center 479
-
575
-
8431 (fax)

Fayetteville, AR 72701 hln@uark.edu

Professional Preparation

University of Pittsburgh Industrial Engineering B.S. April 1994

University of Pittsburgh Industrial Engineering M.S. December 1997

University of Pittsburgh Industrial Engineering Ph.D. August 2000

Appointments

University of Arkans
as, Fayetteville, AR

Assistant Professor August 2000 to present

University of Pittsburgh, Pittsburgh, PA

Research and Teaching Assistant September 1996
-

August 2000

Publications


Most Closely Related

Andres Angulo, Heather Nachtmann, and Matthew Waller,
“Supply Chain Information Sharing

in a Vendor Managed Inventory Partnership,” Journal of Business Logistics, Vol. 25,

No. 1 (2004), pp. 101
-
117.

Nachtmann, Heather and Kim LaScola Needy, “Methods for Handling Uncertainty in Activity

Based Costing,” The Eng
ineering Economist, Vol. 48, No. 3 (2003), pp. 259
-
282.

Li, Zhe, Heather Nachtmann, and Manuel D. Rossetti, “WebShipCost


Quantifying Risk in

Intermodal Transportation,”
Industrial Engineering Research Conference Proceedings
,

May 16
-
19, 2004.

Angulo, Andr
es, Heather Nachtmann, and Matthew Waller, “Use of Shared Information in a

Vendor
-
Managed Inventory (VMI) Supply Chain,”
Industrial Engineering Research

Conference Proceedings
, May 19
-
21, 2002.

Nachtmann, Heather and Kim LaScola Needy, “Fuzzy Activity Base
d Costing: A Methodology

for Handling Uncertainty in Activity Based Costing Systems,” The Engineering

Economist, Vol. 46, No. 4 (2001).

Publications


Other Significant

Needy, Kim LaScola, Heather Nachtmann, Narcyz Roztocki, Rona Colosimo, and Bopaya

Bidan
da, “Implementing Activity Based Costing Systems in Small Manufacturing Firms:

A Field Study,” Engineering Management Journal, Vol. 15, No. 1 (2003), pp. 3
-
10.

Gattis, Carol, Heather Nachtmann, and Alisha D. Youngblood, “The Students
-
Recruiting
-

Students U
ndergraduate Engineering Recruiting Program,” European Journal of

Engineering Education, Vol. 28, No. 1 (2003), pp. 71
-
82.

Needy, Kim LaScola, Jerome P. Lavelle, Heather Nachtmann and Ted G. Eschenbach, “An

Empirical Analysis of Engineering Economy Pedagog
y,” The Engineering Economist,

Vol. 45, No. 1 (2000), pp. 74
-
92.

Atman, Cynthia J., Justin R. Chimka, Karen M. Bursic and Heather L. Nachtmann, “A

Comparison of Freshmen and Senior Engineering Design Processes,” Design Studies,

Vol. 20, No. 2 (March, 1999)
, pp. 131
-
152.

Nachtmann, Heather and Kim LaScola Needy, “Fuzzy Activity Based Costing: A Methodology

for Handling Uncertainty in Activity Based Costing Systems,” The Engineering

Economist, Vol. 46, No. 4 (2001).



Synergistic Activities

Principal Investig
ator, $141,652; “Maintenance Prognostics Decision Aiding,” Air Force

Research Laboratory, August 2004


September 2005.

Principal Investigator, $119,696; “Quantification of Logistics Capabilities,” United States Air

Force Research Laboratories, September 2
003


January 2005.

Co
-
Principal Investigator, $120,906; “Maintenance Decision
-
Making under Prognostic and

Diagnostic Uncertainty,” United States Air Force Research Laboratories, September 2003



January 2005.

Co
-
Principal Investigator, $97,027; “Multi
-
Mis
sion Selective Maintenance Decisions,” United

States Air Force Research Laboratories, July 2003


June 2004.

Collaborators & Other Affiliations

Cynthia J. Atman (University of Washington), Karen M. Bursic (University of Pittsburgh), C.

Richard Cassady (Uni
versity of Arkansas), Justin R. Chimka (University of Oklahoma), David I.

Cleland (University of Pittsburgh), Terry R. Collins (University of Arkansas), Ted G.

Eschenbach (University of Alaska, Anchorage), Joseph C. Hartman (Lehigh University), Jerome

P. L
avelle (North Carolina State University), Scott J. Mason (University of Arkansas), Robert

Martinazzi (University of Pittsburgh, Johnstown), Kim LaScola Needy (University of

Pittsburgh), Manuel Rossetti (University of Arkansas), Narcyz Roztocki (State Unive
rsity of

New York, New Paltz), Peter Shull (University of Pennsylvania, Altoona), Dennis P. Slevin

(University of Pittsburgh), G. Don Taylor (University of Louisville), John S. Usher (University

of Louisville)
Thesis Advisor
: Kim LaScola Needy

BIOGRAPHICA
L SKETCH

Manuel D. Rossetti, Ph.D., P. E.

University of Arkansas

Department of Industrial Engineering 479
-
575
-
6756 (office)

4207 Bell Engineering Center 479
-
575
-
8431 (fax)

Fayetteville, AR 72701 rossetti@uark.edu

Professional Preparation

University of Cinc
innati Industrial Engineering B.S. June 1985

The Ohio State University Industrial & Systems Engineering M.S. June 1988

The Ohio State University Industrial & Systems Engineering Ph.D. December 1992

Appointments

University of Arkansas Associate Professor Au
g 2003 to present

University of Arkansas Assistant Professor Aug. 1999


Aug 2003

University of Virginia Assistant Professor Sept. 1993


Aug. 1999

The Ohio State University Research Assistant Sept. 1989


Sept. 1992

The Ohio State University Teaching Assi
stant Sept. 1986


June 1989

Electronic Data Systems Systems Engineer July 1985


May 1986

Publications


Most Closely Related

McGee, J., Rossetti, M.D., Mason, S. (2004) “Simulating Transportation Practices In

Multi
-
Indenture Multi
-
Echelon (Mime) Systems”
, submitted to
The Proceedings of

the 2004 Winter Simulation Conference,
R .G. Ingalls, M. D. Rossetti, J. S. Smith,

and B. A. Peters, eds., ACM/SIGSIM, ASA, IEEE/CS, IEEE/SMCS, IIE,

INFORMS/CS, NIST and SCS.

Rossetti, M. D., and H. T. Chan. (2003) “A Prot
otype Object
-
Oriented Supply Chain

Simulation Framework”, in
The Proceedings of the 2003 Winter Simulation

Conference,
S. Chick, P. J. Sánchez, D. Ferrin, and D. J. Morrice, eds,

ACM/SIGSIM, ASA, IEEE/CS, IEEE/SMCS, IIE, INFORMS/CS, NIST and SCS.

Rossetti,

M. D., Sloan, N., Tee, Y. S. (2003) “Methods for Military Stock Positioning

Analysis”,
The Proceedings of the 2003 Industrial Engineering Research

Conference
, M. Dessouky, S. Stettles, S. Bukkapatnam, S. Thompson, (editors), May

17
-
21, 2003, Portland, Ore
gon.

Sloan, N., Rossetti, M. D. (2002) “Examining Stock Positions in Military Logistics”,
The

Proceedings of the 2002 Industrial Engineering Research Conference
, J. Fowler and

D. Montgomery (editors), Orlando, Florida.

Rossetti, M.D., and Y. Tee, (2002) “A

Robustness Study of a Multi
-
Echelon Inventory

Model via Simulation”,
International Journal of Production Economics
, No. 80, 265
-

277.

Publications


Other Significant

Rossetti, M. D., Aylor, B., Jacoby, R., Prorock, A., White, A. (2000) “Simfone

: An

object
-
oriented simulation framework”,
The Proceedings of the 2000 Winter

Simulation Conference,
ed. J. Joines, R. Barton, P. Fishwick, and K. Kang,

ACM/SIGSIM, ASA, IEEE/CS, IEEE/SMCS, IIE, INFORMS/CS, NIST and SCS,

pp. 1855
-
1864

Rossetti, M. D., an
d Seldanari, F. (2001) “Multi
-
objective analysis of Hospital Delivery

Systems”,
Computers and Industrial Engineering
, Vol. 41, pp. 309
-
333.

Rossetti, M. D., Kumar, A., and Felder, R. (2000). “Simulation of Mid
-
Size Hospital

Delivery Processes”,
Health Care

Management Science
, Vol. 3, pp. 201
-
213

Rossetti, M. D. and Clark G. M. (1999) “Moment Solutions for the State Exiting

Counting Processes of a Markov Renewal Process”,
Methodology and Computing in

Applied Probability,
Vol. 1, No. 3, pp. 247
-
275.

Rossetti,

M. D. and Clark G. M. (1998) “Estimating Capacity Loadings From Arrival

and Departure Events”,
Journal of Manufacturing Systems
, Vol. 17, No. 1, 1998, pp.

65
-
76.

Synergistic Activities

Funded Research in Military Logistics



A Constrained Clustering Algor
ithm for Spare Parts Segmentation , Naval Systems

Supply Command



Readiness
-
Based Customer
-
Wait
-
Time Sparing within Advanced Planning Systems,

Naval Systems Supply Command



Quantifying the Effect of Commercial Transportation Practices in Military Supply

Chains, Air Force Research Laboratory



Analysis of Military Processing Centers, Defense Logistics Agency



Design of a Performance Measurement System to Enhance Systems Level Logistics

Management, Defense Logistics Agency



Inventory Integrity Modeling an
d Benchmarking, Defense Logistics Agency



The Analysis of Inter
-
modal Choice Combinations and Pre
-
Positioning Strategies for

Military Supplies and Materiel, Defense Logistics Agency

Collaborators & Other Affiliations

Collaborators:
L. Ackart (U.S. Navy),
B. Aylor, R. Cassady (UA), H. T. Chan, M. Cole (Univ. of

Wyoming), T. Collins (Texas Tech), R. Felder (University of Virginia, UVA), Jacoby, R., E.

Kutanogulo (UT at Austin), H. Nachtmann (UA), S. Mason (UA), J. Oldham, A. Prorock, F.

Seldanari, N. Sloan (
UA), D. Taylor (Univ. of Louisville), Y. S. Tee (Intel), A. White,
Coeditors:

R. G. Ingalls, J. S. Smith, B. A Peters,
Graduate Advisor:
Gordon Clark (Professor

Emeritus, The Ohio State University),
Thesis Advisees:
(H. Chan, K. Chittoori, R. Daniels, F.

S
eldanari, M. Kincannon (UA), D. Mettenberg (UA), T. Sang (UA), Y. Tee (UA), S. Thomas

(UA), G. Trzcinski, T. Turitto, J. Watson (UA)).
Number of Graduate Students Advised:
19

BIOGRAPHICAL SKETCH

Nebil Buyurgan

University of Arkansas

Department of Industri
al Engineering 479
-
575
-
7423 (office)

4207 Bell Engineering Center 479
-
575
-
8431 (fax)

Fayetteville, AR 72701
nebilb@uark.edu


Professional Preparation

Academic: University of Missouri
-
Rolla Engineering Management Ph.D. 2004

University of Missouri
-
Rolla Engi
neering Management MS 2000

Istanbul Technical University Industrial Engineering BS 1998


Professional History

Assistant Professor, University of Arkansas, Department of Industrial Engineering, 2004
-

Present

Graduate Teaching Assistant, University of Misso
uri
-
Rolla, Engineering Management, 1998
-

2004

Group Coordinator, Integrated Systems Facility, UMR, Engineering Management, 1998
-

2004

Graduate Research Assistant, Computer Integrated Manufacturing, UMR, Engineering Management, 1998
-

2000


Publications


Most Relevant

Meyyappan, L., Buyurgan, N., Dagli, C.H., and Saygin, C., "Intelligent Path Planning and Scheduling for

Automated Guided Vehicles Using Evolutionary Algorithm,"
Artificial Neural Networks in Engineering
(Annie)
,

November 7
-
10, 2004, St. Loui
s

Buyurgan, N. and Saygin, C., “An Integrated Control Framework for Flexible Manufacturing Systems,”

International Journal of Advanced Manufacturing Technology
(in print for 2005).

Buyurgan N., Saygin, C., and Kilic, S.E., “Tool Allocation in Flexible Manu
facturing Systems with Tool

Alternatives,”
Robotics and Computer Integrated Manufacturing,
20(2004), pp. 341
-
349.


Publications


Other Significant

Saygin, C., Buyurgan, N., and Siwamogsatham, T., “Creating an Interactive Learning Environment for
Distance

Education in Integrated Manufacturing Systems: A Web
-
based Approach,”
36th American Society for
Engineering

Education (ASEE) Midwest Section Conference
, March 7
-
9,2001.

Saygin, C., Siwamogsatham, T., and Buyurgan N., “A Laboratory Environment for Manufactu
ring Systems

Education: Integrated Systems Facility,”
36th American Society for Engineering Education (ASEE) Midwest
Section

Conference
, March 7
-
9, 2001

Buyurgan N. and Saygin, C., “Tool Management in Flexible Manufacturing Systems: A Simulation Study,”

Pr
oceedings of the
Society of Engineering Science SES 2002, Simulation Based Control Session
, page 17.4,
October

13
-
16, 2002, State College, Pennsylvania.


Collaborators & Other Affiliations

Collaborators:
Can Saygin (UMR), Kevin Hubbard (Southern Illinois S
tate University) Yildirim Omurtag
(Robert

Morris University), Cihan Dagli (UMR), Justin Chimka (UA), Earnest Fant (UA), Thananun Siwamogsatham

(UMR), Engin Kilic (Middle East Technical University),
Thesis Advisees:
Ahmet Soylemezoglu (UMR),
Burak

Arasli (U
MR),
Number of Graduate Students Advised:
1

BIOGRAPHICAL SKETCH


C. Richard Cassady, Ph.D., P.E.

University of Arkansas

Department of Industrial Engineering 479
-
575
-
6735 (ofc)

4207 Bell Engineering Center 479
-
575
-
8431 (fax)

Fayetteville, AR 72701 cassady@
engr.uark.edu


Professional Preparation

Virginia Tech Industrial and Systems Engineering B.S. August 1992

Virginia Tech Industrial and Systems Engineering M.S. December 1993

Virginia Tech Industrial and Systems Engineering Ph.D. August 1996


Appointments

U
niversity of Arkansas, Fayetteville, AR

Associate Professor of Industrial Engineering August 2000 to present

Mississippi State University, Starkville, MS

Assistant Professor of Industrial Engineering August 1996 to August 2000

Virginia Tech, Blacksburg, VA

Instructor of Industrial and Systems Engineering May 1994 to August

1996


Publications


Most Closely Related

Cassady, C.R., E.A. Pohl and S. Jin. “Managing Availability Improvement Efforts with

Importance Measures and Optimization”,
IMA Journal on Manage
ment

Mathematics
(accepted for publication).

Cassady, C.R. and E. Kutanoglu (2003). “Minimizing Job Tardiness using Integrated

Preventive Maintenance Planning and Production Scheduling”,
IIE Transactions
,

Vol. 35, No. 6, pp. 505
-
513.

Cassady, C.R., E.A. Po
hl and W.P. Murdock (2001). “Selective Maintenance Modeling

for Industrial Systems”,
Journal of Quality in Maintenance Engineering
, Vol. 7,

No. 2, pp. 104
-
117.

Cassady, C.R., W.P. Murdock and E.A. Pohl (2001). “Selective Maintenance for Support

Equipment I
nvolving Multiple Maintenance Actions”,
European Journal of

Operational Research
, Vol. 129, No. 2, pp. 252
-
258.

Cassady, C.R., R.O. Bowden, L. Liew and E.A. Pohl (2000). “Combining Preventive

Maintenance and Statistical Process Control: A Preliminary Inves
tigation”,
IIE

Transactions
, Vol. 32, No. 6, pp. 471
-
478.


Publications


Other Significant

Cassady, C.R., I.G. Takahashi and E.A. Pohl (2003). “Reliability Analysis of

Intermittently
-
Used Products”,
International Journal of Modelling and

Simulation
, Vol.
23, No. 4, pp. 234
-
239.

Ormon, S.W., C.R. Cassady and A.G. Greenwood (2002). “Reliability Prediction Models

to Support Conceptual Design”,
IEEE Transactions on Reliability
, Vol. 51, No. 2,

pp. 151
-
157.


Synergistic Activities

Funded Research Projects Invo
lving System Maintainability


Maintenance Decision
-
Making under Prognostic and Diagnostic Uncertainty, The

Logistics Institute (TLI), Air Force Research Laboratory (AFRL)


Multi
-
State Selective Maintenance Decisions, TLI, AFRL


Quantifying the Impacts o
f Improvements to Prognostic and Diagnostic

Capabilities, TLI, AFRL Multi
-
Mission Selective Maintenance Decisions, TLI,

AFRL


Quantifying the Impact of Aircraft Cannibalization, TLI, AFRL


Fleet
-
Level Selective Maintenance and Aircraft Scheduling, TLI, A
FRL


Equipment Availability Modeling under Imperfect Maintenance, SILO Advisory

Council


Incorporating Lean Thinking into Grenade Line Maintenance, TLI, Pine Bluff

Arsenal


Grenade Line Reliability and Maintainability Performance, TLI, Pine Bluff

Arsena
l


Cost of Ownership Modeling for Support Equipment at Intermodal Transportation

Terminals, National Center for Intermodal Transportation


Development of Productivity
-
Based Selective Maintenance Strategies, TLI, Pine

Bluff Arsenal


Determining Optimal T
railer Duty as a Function of Use and Age, Mack
-

Blackwell Transportation Center (MBTC)


Quantifying the Impact of Refrigerated Unit Failures, MBTC

Collaborators & Other Affiliations

J.R. Chimka, J.R. English, E.W. Fant, S.J. Mason, H.L. Nachtmann, D.W. Nu
tter, E.A.

Pohl (U. of Arkansas); E. Kutanoglu (U. of Texas); G.D. Taylor (U. of Louisville); R.O.

Bowden, S.F. Bullington, A.G. Greenwood, S.A. LeMay, (Miss. State U.); W.P.

Murdock (US Air Force); J.E. Kobza (Texas Tech U.); L.L. Crumpton (U. of Central

Florida); L.M. Maillart (Case Western Reserve U.)

Thesis Advisor: J.A. Nachlas

Justin Chimka

4207 Bell Engineering Center

Fayetteville, Arkansas 72701

(479) 575
-
7392 (voice)

(479) 575
-
8431 (fax)

jchimka@uark.edu


Professional Preparation

University of Pit
tsburgh Industrial Engineering BS 1995

University of Pittsburgh Industrial Engineering MS 1998

University of Pittsburgh Industrial Engineering PhD 2001


Appointments

Assistant Professor

University of Arkansas; Department of Industrial Engineering; 2003


p
resent

Adjunct Assistant Professor

University of Arkansas; Department of Industrial Engineering; 2002, 2003

Visiting Assistant Professor

The University of Oklahoma; School of Industrial Engineering; 2001, 2002


Publications most closely related

Yeung, TG,
Mason, SJ, Chimka, JR and Greiner, MA, 'Recommendations for

automatic identification technology in the Air Force supply chain,' to appear in

Air Force Journal of Logistics

Atman, CJ, Chimka, JR, Bursic, KM and Nachtmann, HL (1999), 'A comparison of

freshma
n and senior design processes,'
Design Studies
, 20: 131
-
152

Nachtmann, H and Chimka, JR (2003), 'Fuzzy reliability in conceptual design,'

Reliability and Maintainability Symposium

Nachtmann, H, Chimka, JR and Youngblood, AD (2003), 'Investigating

engineeri
ng student estimation processes,'
American Society for Engineering

Education Conference

Chimka, JR (2002), 'Proportional hazards models of graduation,'
Joint Statistical

Meetings


Other significant publications

Cassady, CR, Chimka, JR and Yu, P (2003), 'Ex
ploring the impact of repair time

variability on equipment performance,'
17
th
International Conference on Production

Research

Chimka, JR (2003), 'A proposal for an ordinal alternative to demerits,'
Industrial

Engineering Research Conference

Chimka, JR and
Wolfe, H (2002), 'Test accuracy measured for midsize ordinal

samples,'
Industrial Engineering Research Conference

Rhoads, TR, Chimka, JR and Moore, M (2002), 'Balanced scorecard for

engineering education,'
American Society for Engineering Education Confere
nce

Chimka, JR (2001), 'An introduction to the observation of graduation as survival

data,'
Frontiers in Education Conference











Synergistic Activities

Reviewer for NSF grant proposals

Research on Learning and Education (ROLE) 2003

Department
-
Level
Reform of Undergraduate Engineering Education (DLR) 2004

Refereeing: Journal of Engineering Education (2001, 2002, 2004), IIE Transactions

(2004), Computers & Industrial Engineering (2003), International Journal of

Production Research (2003)

Collaborators

Mary Besterfield
-
Sacre (University of Pittsburgh), Richard Cassady (University

of Arkansas), Scott Mason (University of Arkansas), Jack McGourty (Columbia

University), Heather Nachtmann (University of Arkansas), Teri Reed
-
Rhoads

(The University of Oklahoma
), Larry Shuman (University of Pittsburgh), Harvey

Wolfe (University of Pittsburgh), Alicia Youngblood (The University of Alabama

in Huntsville)

Graduate Advisor

Harvey Wolfe (University of Pittsburgh)

BIOGRAPHICAL SKETCH

J
OHN
R
OY
E
NGLISH

University of Ar
kansas

Department of Industrial Engineering 479 575 6029 (office)

4207 Bell Engineering Center 479 575 8431 (fax)

Fayetteville, AR 72701
jre@uark.edu

Professional Preparation

Ph.D., Industrial Engineering and Management Oklahoma State University 1988

M.S.,

Operations Research University of Arkansas 1982

B.S., Electrical Engineering University of Arkansas 1981

Appointments

Jun 02
-
Present
Executive Director
, Center for Engineering Logistics and Distribution

(CELDi), NSF Industry/University Cooperative Researc
h Center,

Partnering Universities: Lehigh University, Oklahoma State University,

University of Florida, University of Louisville, University of Oklahoma,

Department of Industrial Engineering, University of Arkansas,

Fayetteville, AR

Apr 00
-
Present
Departme
nt Head
, Department of Industrial Engineering, University of

Arkansas, Fayetteville, Arkansas

Feb 00
-
Mar 00
Interim Department Head
, Department of Industrial Engineering,

University of Arkansas, Fayetteville, Arkansas

Feb 00
-
Jun 02
Director
, The Logistics
Institute, NSF Industry/University Cooperative

Research Center.

Oct 99
-
Jan 01
Economic Development Officer
, College of Engineering, University of

Arkansas, Fayetteville, Arkansas

Oct 99
-
Jan 01
Director
of GENESIS Technology Incubator, College of Engineerin
g,

University of Arkansas, Fayetteville, Arkansas

Aug 99
-
Present
Professor
(Tenured), Department of Industrial Engineering, University of

Arkansas, Fayetteville, Arkansas

Aug 94


Jul 99 Associate Professor (Tenured), Department of Industrial Engineering,

U
niversity of Arkansas, Fayetteville, Arkansas

Jan 01


Jul 94 Assistant Professor, Department of Industrial Engineering, University of

Arkansas, Fayetteville, Arkansas

Aug 88


Dec 90 Assistant Professor, Department of Industrial Engineering, Texas A&M

Uni
versity, College Station, Texas

Publications


Most Closely Related

J.T. Fite, G.D. Taylor, J. Usher, J.R. English, and J.N. Roberts, “Forecasting Freight Demand

Using Economic Indices,”
International Journal of Physical Distribution and Logistics

Manageme
nt
, Vol. 32, No. 4, pp. 299
-
308, 2002.

T.S. Meinert, G.D. Taylor and J.R. English, “A Modular Simulation for Automated Material

Handling Systems,”
Simulation Practice and Theory
, Vol. 7, pp. 15
-
30, 1999.

J.R. English, G. Petrina and M. Roy, “Group Metrics
for Quality Monitoring of Logistics

Systems,”
Progress in Material Handling Research: 1998
, R.J. Graves, L.F. McGinnis,

D.J. Medeiros, R.E. Ward, M.R. Wilhelm, Editors, Braun
-
Brumfield, Inc., Ann Arbor,

MI, pp. 173
-
188.

J.R. English, T.L. Landers, L. Yan,
and S.Y. Choy, “Failure Modeling of Material Handling

Equipment,”
Progress in Material Handling Research: 1996,
R.J. Graves, L.F.

McGinnis, D.J. Medeiros, R.E. Ward, M.R. Wilhelm, Eds., Braun
-
Brumfield, Inc., Ann

Arbor, MI, 1997.

G.D. Taylor, S. Harit, J.R
. English, and G. Whicker, “Hub and Spoke Networks in Truckload

Trucking: Configuration and Operations Concerns,”
The Logistics and Transportation

Review
, Vol. 31, No. 3, pp. 209
-
238, Sept. 1995.

Publications


Other Significant

E.A. Elsayed, M. Gultekin,
and J.R. English, “Cross
-
correlation and
X
-
Trend control charts for

processes with linear shift,”
International Journal of Production Research
, Vol. 40, No.

5, pp. 1051
-
1064, 2002.

E.A. Elsayed, M. Gultekin, J.R. English and A.S. Hauksdottir, “Monitoring
Automatically

Controlled Processes Using Statistical Control Charts,”
International Journal of

Production Research
, Vol. 40, No. 10, pp. 2303
-
2320, 2002.

J.R. English and J. Alam, “Modeling and Process Disturbance Detection of Autocorrelated

Data,”
Nonline
ar Analysis
, Vol. 47, pp. 2103
-
2111, 2001.

G.O. Tolley and J.R. English, “Cost Surface Exploration in Economic Design of Control

Charts,”
IIE Transactions
, Vol. 33, No. 6, pp. 429
-

436, 2001.

J.R. English, S.C. Lee, T.W. Martin and C. Tilmon, “Monitoring
Time
-
dependent Data with

Xbar and EWMA Charts,”
IIE Transactions
, Vol. 32, No. 12, pp. 1103
-
1114, 2000.

Synergistic Activities

Recent Professional Service:
2003
-
Present, Fellow, Institute of Industrial Engineers (IIE); 2003
-

2004 Chairman of the Board of D
irectors, 2004 Reliability and Maintainability Symposium;

2002
-
2003 General Chair, 2004 Reliability and Maintainability Symposium; 2002
-
2004, Senior

VP Publications, IIE; 2002
-
2004, Board of Trustees, IIE; 2001
-
2002, Vice General Chair,

Reliability and Mai
ntainability Symposium; 2001
-
Present, Editor,
IIE Transactions on Quality

and Reliability Engineering

Administrative Roles having Impact on this Project:
2000
-
Present, Professor and Department

Head of Industrial Engineering at the University of Arkansas; 2
000
-
Present, Executive Director,

Center for Engineering Logistics and Distribution (National Science Foundation I/UCRC)

Collaborators and Other Affiliations

G. Don Taylor (Virginia Tech), Tom Landers (University of Oklahoma), Mustafa Pulat

(University of O
klahoma), Rikki Ingals (Oklahoma State University), Elsayed Elsayed (Rutgers

University), David Coit (Rutgers Oklahoma), Ken Case (Oklahoma State University), David Wu

(Lehigh University), Joe Gueness (University of Florida), Terry Collins (Texas Tech Univ
ersity),

Muge Gultekin, Tim Meinert (University of Missouri, Rolla), John Usher (University of

Louisville), Gil Tolley (Red River Army Depot)

Ph.D. Thesis Advisees:
Jerry Peek (UA), Gilbert Tolley (UA), Li Yan (UA), Niki Deliman

(TAMU)

MS Students:
Mee Chi
ng Chou (UA), Beatrice Laura (UA), Felicia Zakaria (UA), Jose Del Rio

(UA), Alejandro Mendoza (UA), Mohammed Alsein (UA), Charles E. Tilmon, III (UA), Sen
-

Chin Lee (UA), Rahul Kakar (UA), Ross Tompkins (UA), Kerry Melton (UA), Tom Sargent

(UA), Nick Faddo
ul (UA), Shrenivasan Chandrasekaran (TAMU)



Raymond R. Hill

Department of Biomedical, Industrial & Human Factors Engineering

Wright State University

Professional Preparation:

Eastern Connecticut State University, Mathematics,
B.S.
, 1983.

Air Force Instit
ute of Technology, Operations Research,
M.S.
, 1988.

The Ohio State University, Industrial and Systems Engineering,
Ph.D.
, 1996..

Appointments:

Associate Professor
, Department of Biomedical, Industrial & Human Factors Engineering,

Wright State University, D
ayton, OH, 2003


Present.

Associate Professor
, Department of Operational Sciences, Air Force Institute of Technology,

Wright
-
Patterson AFB, OH, 2001
-
2002.

Assistant Professor
, Department of Operational Sciences, Air Force Institute of Technology,

Wright
-
P
atterson AFB, OH, 1997
-
2001.

Air Force Officer, Scientific Analyst
, United States Air Force, 23 years retired.

Selected Publications: (5 most related)

N. L. Schneider, S. Narayanan, C. Patel, T. Carrico, and R. Hill. 2004. Integration of genetic

algorithms

with airbase simulations for repair time analysis.
International Journal of Industrial

Engineering
11(3), 231
-
240.

Hill, R. R., S. Mahadevan, and S. Narayanan. May 2004. Examining Real
-
Time Scheduling

Exceptions in Complex Planning Domains Using Decision
Support Systems
. WSEAS

Transactions on Systems
, Vol. 3, No. 3, pp: 1213
-
1220.

Johnstone, D. P., R. R. Hill, and J. T. Moore. March 2004. Mathematically Modeling Munitions

Pre
-
Positioning and Movement
. Mathematical and Computer Modeling
, Vol. 39, No. 6
-
8, p
p.

759
-
772.

MacKenna, J., W. Cunningham, and R. R. Hill. 2002. Determining AGE Levels.
Air Force

Journal of Logistics
, Vol. XXV, No. 4, Winter 2001. (
selected by International Society of

Logistics Engineers (SOLE) as best paper in 2001)

O' Fearna, F. C., R
. R. Hill and J. O. Miller. 2002. A Methodology to Reduce Aerospace Ground

Equipment Requirements for an Air Expeditionary Force.
International Journal of Logistics:

Research and Applications
, Vol. 5, No. 1.

Five Other Publications:

Kinney, G. W., R. R. Hi
ll and J. T. Moore. 2004. Devising a Quick
-
Running Heuristic for an

Unmanned Aerial Vehicle (UAV) Routing System. To appear
Journal of the Operational

Research Society
.

O' Rourke, K. P. , T. G. Bailey, R. R. Hill., and W. B. Carlton. 2001. Dynamic Routing
of

Unmanned Aerial Vehicles Using Reactive Tabu Search.
Military Operations Research,
Vol. 6,

No. 1, pp. 5
-
30

Hill, R. R. and C. H. Reilly. 2000. Multivariate Composite Distributions for Coefficients in

Synthetic Optimization Problems.
European Journal of
Operational Research
. Vol. 121, pp. 64
-

77.

Hill, R. R. and C. H. Reilly. 2000. Multivariate Composite Distributions for Coefficients in

Synthetic Optimization Problems.
European Journal of Operational Research
. Vol. 121, pp. 64
-

77

Hill, R. R., G. A. McIn
tyre, T. R. Tighe, R. K. Bullock. 2003. Some Experiments with Agent
-

Based Combat Models.
Military Operations Research,
Vol. 8, No. 3, September 2003.

Examples of Synergistic Activities:

Principle Investigator,
Models, Web
-
Based Simulations, And Integrated

Analysis Techniques For

Improved Logistical Performance
, with participation from the Wright State University and

the University of Dayton, 1999
-
2000.

Principle Investigator, Coordination and Control of Cooperative Swarms of Unmanned Aerial

Combat Vehicles

via a Virtual Testbed Environment, Air Force Office of Scientific

Research, 2004
-
2006.

Co
-
Investigator, Modeling Sortie Generation, Maintenance, and Inventory Interactions for Unit

Level Logistics, with University of Arkansas in support of Northrop
-
Grumma
n Information

Technology, 2003
-
2005.

AFIT associate investigator for
Application of Metaheuristics to Air Force Problem,
a University

of Texas at Austin
-
led consortium of University of Texas at Austin, Air Mobility

Command, and Air Force Institute of Techn
ology. Separate AFOSR funding to AFIT and to

University of Texas.

Military Track Coordinator, nine sessions, for Winter Simulation Conference, 2003
-
2005.

Collaborators in past four years:

James T. Moore, Air Force Institute of Technology

Charles H. Reilly,

University of Central Florida

Wesley Barnes, University of Texas at Austin

Manuel D. Rossetti, University of Arkansas

Section 2f. Biographical Sketches, Page 3

Laura G. Militello

University of Dayton Research Institute & Department of Psychology

300 Coll
ege Park, Dayton, Ohio 45469
-
0110

Professional Preparation:

Year Degree Major Institution

1987 B.S. Psychology University of Dayton, Dayton, OH

1995 M.A. Human Factors Psychology University of Dayton, Dayton, OH

Appointments:

Dates Position Organization Lo
cation

2002
-

Senior Research Psychologist UDRI Human Factors Dayton, OH

2004
-

Adjunct Professor Department of Psychology Dayton, OH

2000
-
2002 Sr. Research Associate Klein Associates Mountain View, CA

1999
-
2000 Sr. User Interface Designer Acuson Corp Mounta
in View, CA

1991
-
1999 Research Associate Klein Associates Fairborn, OH

Selected Publications: (5 most related)

Klein G. & Militello, L.G. (2005). The knowledge audit as an approach for cognitive task

analysis. In B. Brehemer, R. Lipshitz, & H. Montgomery,
(Eds.).
How professionals make

decisions
(pp. 335
-
342). Mahaw, NJ: Erlbaum.

Militello, Patterson, Tripp
-

Reimer, Asch, Fung, Glassman, Anders, Doebbeling (2004).

Clinical reminders: Why don’t they use them? Proceedings of the 48
th
Human Factors and

Ergono
mics Society Meeting. Santa Monica, CA: HFES.

Snead, A.E., Militello, L.G., & Ritter, J.A. (2004). Electronic Checklists in the Context of B
-
2

Pilot Decision Making.
Proceedings of the 48
th
Human Factors and Ergonomics Society

Meeting
. Santa Monica, CA: HF
ES.

Baeck, A. & Militello, L. (2003). Going Global: The challenges of designing a medical device

for a global marketplace. User Experience, Spring/Summer, 30
-
35.

Militello, L.G., Kyne, M.M., Klein, G., Getchell, K., & Thordsen, M.L. (1999). A synthesized

m
odel of team performance. International Journal of Cognitive Ergonomics 3 (2),131
-
158.

Five other publications

Militello, L.G. (2001). Representing Expertise. In Linking Expertise and Naturalistic Decision

Making, Eds. Salas. & Klein. Mahway, NJ: Lauwrence

Erlbaum.

Klein, G., & Militello, L.G. (2001).
Some guidelines for conducting cognitive task analysis. In

E. Salas (Ed.),
Advances in human performance and cognitive engineering research
(Vol. 1,

pp. 163
-
197: JAI, Press.

Militello, L.G. & Hutton, R.J.B. (1
998). Applied Cognitive Task Analysis (ACTA): A

practitioner’s toolkit for understanding cognitive task demands. Ergonomics Special Issue:

Task Analysis, 41 (11), 1618
-
1641.

Militello, L.G. (September/October 1998). Learning to think like a user: Using co
gnitive task

analysis to meet today’s health care design challenges. Biomedical Instrumentation and

Technology.

Militello, L. (1995). A cognitive task analysis of NICU nurses’ patient assessment skills.

Proceedings of the Human Factors and Ergonomics Socie
ty 39th Annual Meeting, 2, 733
-

737. San Diego, CA: Human Factors Society.

Section 2f. Biographical Sketches, Page 4

Examples of Synergistic Activities:

Ms. Militello has extensive experience conducting cognitive task analysis (CTA), developing CTA

methods
, and training others to conduct CTA studies. She led a project sponsored by the Navy

Personnel Research and Development Center which resulted in a of suite of three methods called

Applied Cognitive Task Analysis aimed at adapting labor intensive research
methods into applied

tools for use by educational practitioners. She conducted an evaluation study of the methods to

assess their reliability and validity, and led the development of a multimedia instructional package

housed on CD
-
ROM to allow for inexpens
ive and easy dissemination of methods throughout the

Navy. She has since conducted 20+ workshops on the topic of CTA worldwide.

While working for Acuson Corporation, Ms. Militello conducted cognitive task analysis

interviews with ultrasound technologists a
nd physicians in the United States, Europe, and Asia in

order to better understand workflow and the use of ultrasound technology in different cultures.

This effort resulted in the design of an ultrasound device intended to accommodate a range of

users work
ing within different health care contexts, scanning different body types, and

diagnosing different pathology.

Ms. Militello has been an active member in the Naturalistic Decision Making (NDM)

community. The NDM community first met in 1989 in Dayton, OH to
bring together researchers

from disparate disciplines to discuss and share findings about complex decision making in real

world settings. This community of researchers has since grown to include hundreds of

researchers around the globe. Ms. Militello has b
een involved in the planning and organization

of the three of the six NDM conferences, and has contributed to two edited volumes on the topic.

Collaborators & Other Affiliations

a) Collaborators and Co
-
Editors

Shilo Anders, Miami University Brian Moon, Kle
in Associates

Steve Asch, Veterans Health Administration Emily Patterson, The Ohio State University

Aline Baeck, Intuit Emilie Roth, Roth Cognitive Engineering

Peter Doebbeling, Veterans Health Admin. Laurie Quill, University of Dayton Res. Inst.

Connie Fu
nd, Veterans Health Administration Erica Rall, Vanderbilt University

Peter Glassman, Veterans Health Admin. Jill Ritter, Air Force Research Laboratory

Megan Gorman, Univ. of Dayton Res. Inst. Andrea Snead, University of Dayton Res. Inst.

Danyele Harris, Kl
ein Associates Lt. Mona Stilson, Air Force Research Lab.

Robert Hoffman, Institute for Human and

Machine Cognition, University of West Florida

Sarah Swierenga, University of Dayton

David Kancler, University of Dayton Res. Inst. Kelly Vinson, KLSS

Gary Klei
n, Klein Associates Jesse Walker, University of Dayton Res. Inst.

b) Graduate and Postdoctoral Advisors

Greg Elvers, University of Dayton

c) Thesis Advisor and Postgraduate
-
Scholar Sponsor

Not applicable

BIOGRAPHICAL SKETCH

Chang S. Nam, Ph.D., AHFP

Unive
rsity of Arkansas

Department of Industrial Engineering 479
-
575
-
2563 (office)

4207 Bell Engineering Center 479
-
575
-
8431 (fax)

Fayetteville, AR 72701 cnam@uark.edu

Professional Preparation

Sungkyunkwan University Industrial Engineering B.S. February 1994

Sog
ang University Business M.A. February 1996

State University of New York at Buffalo Industrial Engineering M.S. August 2000

Virginia Polytechnic Institute & State University Industrial & Systems Engineering Ph.D. December 2003

Virginia Polytechnic Institute

& State University Human Factors Engineering Dec. 2003


April 2004

Appointments

University of Arkansas Assistant Professor Aug. 2004


Present

Virginia Polytechnic Institute & State University Postdoctoral Research Associate Dec. 2003


April 2004

Virgin
ia Polytechnic Institute & State University Research Assistant Jan. 2001


Dec. 2003

Virginia Polytechnic Institute & State University Teaching Assistant Jan. 2001


May 2002

State University of New York at Buffalo Research Assistant Jan. 2000


June 2000

Sogang University Research Assistant Jan. 1994


Aug. 1995

Publications


Most Closely Related

Nam, C. S., Thomas, C., & Smith
-
Jackson, T. L. (2004). Effects of individual differences and task

environments on users’ interactions with Web resource seeking.
(in press:
Computers in

Education Journal
)

Nam, C. S., Kim, H. N., Smith
-
Jackson, T. L., & Nussbaum, M. A. (2003). Development of a

guidelines tool for mobile phone interfaces
. Proceedings of the Human Factors and

Ergonomics Society’s 47th Annual Meeting
(
pp. 792
-
796). Santa Monica, CA: Human Factors

and Ergonomics Society.

Publications


Other Significant

Nam, C. S., & Bisantz, A. M. (2002). A lens model analysis of confidence judgments: Beyond calibration

measures.
Proceedings of the Human Factors and Erg
onomics Society 46
th
Annual Meeting
(pp. 506
-

510). Santa Monica, CA: Human Factors and Ergonomics Society.

Thomas, C., Nam, C. S., & Smith
-
Jackson, T. L. (2003). The significance of behavior type on Web

information retrieval and academic success.
Proceedi
ngs of the 2003 American Society for

Engineering Education Annual Conference & Exposition
(Session 2793; Section 612). American

Society for Engineering Education.

Synergistic Activities

Workshop Instructor:
Human
-
Computer Interaction/Assessment and Cogniti
ve Ergonomics Laboratory,

Virginia Polytechnic Institute and State University, August 2003


Designed and taught a supplemental course on experimental designs and statistical analyses for human

factors research using the SAS system for human factors graduate students.

Collaborators & Other Affiliations

Collaborators:
A. M. Bisantz (SUNY at Buffa
lo), T. E. Lockhart (Virginia Tech), M. A Nussbaum (Virginia

Tech), T. L. Smith
-
Jackson (Virginia Tech), R. C. Williges (Virginia Tech), H. Hexmoor (University of

Arkansas), S. L. Johnson (University of Arkansas)

Graduate Advisor:
Tonya L. Smith
-
Jackson (V
irginia Tech), Ann. M. Bisantz (SUNY at Buffalo)

Thesis Advisees
: 0

Number of Graduate Students Advised:
0

S. Narayanan
, Ph.D., P.E.

Professor and Chair

Department of Biomedical, Industrial & Human Factors Engineering

Wright State University

Education

Regi
onal Institute of Technology, India Mechanical Engineering B.S., 1987

The University of Alabama, Tuscaloosa Industrial Engineering M.S., 1989

Georgia Institute of Technology, Atlanta Industrial & Systems Engineering M.S., 1991

Georgia Institute of Technolo
gy, Atlanta Industrial & Systems Engineering Ph. D., 1994

Experience

Institution Position Dates

Wright State University, Dayton Professor and Chair Fall 2002
-

Present

Wright State University, Dayton Interim Chair, Dept. of BIE Summer 01


Summer 02

Wright

State University, Dayton Associate Professor (with tenure) Fall 1999


Summer 02

Wright State University, Dayton Assistant Professor Fall 1994


Summer 1999

Georgia Tech, Atlanta Graduate Research Assistant Fall 1989


Summer 1994

Georgia Tech, Atlanta Gr
aduate Teaching Assistant Fall/Winter 1990 & 1991

The University of Alabama, Tuscaloosa Graduate Research Assistant Fall 1988


Summer 1989

The University of Alabama, Tuscaloosa Graduate Teaching Assistant Fall 1987


Fall 1988

Tata Engineering and Locomot
ive Summer Intern Summer 1986

Company, Jamshedpur, India

Selected Publications

[1] S. Narayanan, W. Bailey, J. Tendulkar, R. Daley, D. Pliske, & K. Wilson. (2002). Design of modelbased

interfaces for a real world information system
. IEEE Transactions on Sy
stems, Man, &

Cybernetics Part A: Systems and Humans
, 32 (1), 11


24.

[2] L. Rothrock, S. Kantamneni, C. Harvey, S. Narayanan. (In Press). A Re
-
Configurable Telerobotics

System for Human Factors Engineering Education.
International Journal of Modelling an
d Simulation
.

[3] M. McNeese, H. Bautsch, & S. Narayanan.
(1999). A framework for cognitive field research.

International Journal of Cognitive Ergonomics
, 3(4), 307
-
332.

[4] A. Ram, S. Narayanan, & M. T. Cox. (1995). Learning to troubleshoot: Multistrategy

Learning of

Diagnostic Knowledge for a Real
-
World Problem solving Task.
Cognitive Science
, Vol. 19, No. 3, July

-

September, 289
-
340.

[5] H. A. Ruff, S. Narayanan, & M. Draper. (2002). Human interaction with levels of automation and

decision aid fidelity
in the supervisory control of multiple simulated teleoperated air vehicles.

Presence: Teleoperators and Virtual Environments
,11 (4), 335


351

[6] S. Narayanan, D. A. Bodner, U. Sreekanth, T. Govindaraj, L. F. McGinnis, & C. M. Mitchell. (1998).

Research i
n object
-
oriented manufacturing simulations: An assessment of the state of the art.
IIE

Transactions
, 30(9), 795
-
810.

[7] K. Maynard, P. Moss, M. Whitehead, S. Narayanan, M. Garay, N. Brannon, R. Prasad Kantamneni,

and T. Kustra, (2001). Modeling expert pr
oblem solving in a game of chance: A Yahtzee case study.

Expert Systems:
The International Journal of Knowledge Engineering and Neural Networks
, May, 18

(2), 88


98.

[8] S. Narayanan, H.A. Ruff, N.R. Edala, J.A. Geist, K. Patchigolla, M. Draper, & M. Haas
. (2000).

Human
-
integrated supervisory control of uninhabited combat aerial vehicles.
Journal of Robotics and

Mechatronics, Special Issue on "Intelligent Control in Coming New Generation."
Vol. 12, No. 6, 1
-

12.

[9] S. Narayanan, W. D. Bailey, J. Tendulka
r, K. Wilson, R. Daley, & D. Pliske. (1999). Modeling realworld

information seeking in a corporate environment.
International Journal of Human Factors and

Ergonomics in Manufacturing
, 9(2), 1
-
31.

[10] N. L. Schneider, S. Narayanan, C. Patel, T. Carrico, an
d R. Hill. (In Press). Integration of genetic

algorithms with airbase simulations for repair time analysis.
International Journal of Industrial

Engineering
.

Synergistic Activities


Associate Editor,
IEEE Transactions on Systems, Man, & Cybernetics
, 2000


Present.


Associate Editor,
International Journal of Modelling and Simulation
, 2000


Present.


Associate Vice President of Academic Activities,
Society for Computer Simulation

International
, 1999


2002.


Administrative Committee (ADCOM) member, IEEE Systems, Man, & Cybernetics Society,

2000


2003.


Member, Fundamentals of Engineering (FE) Exam Item Writers Committee on Industrial

Engineering, National Council of Examiners fo
r Engineering and Surveying (NCEES),

Clemson, SC, 1996


Present.

Collaborators

Richard Koubek (Penn State University), Ling Rothrock (Penn State), Craig Harvey (Louisiana State

University), Douglas Bodner (Georgia Tech), Nathan Brannon (Sandia National La
b), Mike Haas (USAF)

Graduate and Postdoctoral Advisors

Christine Mitchell (Georgia Tech), T. Govindaraj (Georgia Tech), Leon McGinnis (Georgia Tech)

Thesis Advisor and Postgraduate
-
Scholar Sponsor

1. Mike Patzek (PhD, Graduated 2003), US Air Force Research Laboratory

2. Patrick Moss (MS), Kantamneni Rajgopal Prasad (MS), Sriram Mahadevan (MS), Matthew

Garay (MS), Subhashini Ganapathy (MS), Heath Ruff (MS), Todd Kustra (MS), William

Bailey (MS), Holl
y Bautsch (MS), N.L. Schneider (MS)