RAPS: A Resource Allocation Production Scheduling Algorithm for Hot Food Production Systems

160 Pages·2016·7.3 MB·English

by  William Legree Goodwin

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William Legree Goodwin
University of Tennessee, Knoxville
Follow this and additional works at: https://trace.tennessee.edu/utk_gradthes
Part of the Food Science Commons
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Goodwin, William Legree, "RAPS: A Resource Allocation Production Scheduling Algorithm for Hot Food
Production Systems. " Master's Thesis, University of Tennessee, 1976.
https://trace.tennessee.edu/utk_gradthes/3732
This Thesis is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and
Creative Exchange. It has been accepted for inclusion in Masters Theses by an authorized administrator of TRACE:
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To the Graduate Council:
I am submitting herewith a thesis written by William Legree Goodwin entitled "RAPS: A Resource
Allocation Production Scheduling Algorithm for Hot Food Production Systems." I have examined
the final electronic copy of this thesis for form and content and recommend that it be accepted
in partial fulfillment of the requirements for the degree of Master of Science, with a major in
Food Science and Technology.
Betty L. Beach, Major Professor
We have read this thesis and recommend its acceptance:
Mary Jo Hitchcock, John R. Buchan
Accepted for the Council:
Carolyn R. Hodges
Vice Provost and Dean of the Graduate School
(Original signatures are on file with official student records.)
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RAPS: A -RESOURCE -ALLOCATION -PRODUCTION SCHEDULING ALGORITHM
FOR HOT FOOD PRODUCTION SYSTEMS
A Thesis
Presented for the
Master of Science
Degree
The University of Tennessee
Willtam Legree Goodwin, Jr.
March 1976
ACKNOWLEDGEMENTS
The author expresses his sincere appreciation and gratitude to
Betty L. Beach, Ph9D., Associate Professor of Food Systems Administra­
tion, for her guidance, encouragement, and assistance in developing
this study; to John R. Buchan, Associate Professor of Industrial Engi­
neering, for making available the REST Algorithm and for advice and
)
encouragement during development of this study; and, to Mary Jo Hitch­
cock, Ph.D., Professor of Food Systems Administration, for her influence
and suggestions during the entire course of this study.
Special appreciation is extended to Mr. Norman D. Hil1, Director
of Food Services, University of Tennessee, for making available the
physical facilities needed by this study; to the members of the execu­
tive .committee, Mrs. Sue B. Smith, Manager, and Mrs. Mi 1 dred R.. Smith,
Lead Cook, Morrill Dining Hall, University of Tennessee, who were
responsible for estimating and/or providing essential input data; and�
to members of the executive panel, Mr. Charles G. Brooks, Director,
Dietary Services, University of Tennessee Memorial Hospital and Research
Center, Mrs. Jamesena M. Miller, Assistant Director of Food Services,
University of Tennessee, and Mr. David A. Wyatt, Manager, Presidential
Court Dining Hall, University of Tennessee, who sow illingly rendered
an analysis of the RAPS Algorithm.
The author wishes to express sincere appreciation to his wife
Brenda, whose endless encouragement, understanding, and personal sacri­
fice made possible the accomplishment of this study.
ii
ii;
Appreciation is extended to the United States Army Medical
Department and especially the Army Medical Specialist Co.rps for pro­
viding the author with the opportunity for advanced study in Food
Systems Administration.
ABSTRACT
A procedural model for the scheduling of labor and equipment
in a hypothetical food production system that operated under traditional
constraints was developed, tested and analyzed. The developed model,
the RAPS (Resource Allocation Production Scheduling) Algorithm, was
applied to a five-day menu of hot foods with a forecasted demand per
meal of 5000
Based on forecasted demand and the nature of preparation of the
menu item, specific production quantities were established to simulate
the demands of the meal serving period. Using industrial engineering
techniques of activity analysis and time estimation in conjunction with
a network-based project management system, the 90 sub-projects of the
five-day menu were initially analyzed for 1215 activities, then consoli­
dated into 979 activities.
Scheduling of the 979 activities was performed on a worksheet
which showed resource availabilities for the 14-hour daily operational
period in 10-minute intervals. Generated schedules were in the form
of color-coded bar chartso The optimum schedule was obtained by sched­
uling predecessor and successor activities to a fixed interval according
to Late Start (LS) and Early Complete (EC) times, respectivelya The
optimum schedule, although operationally unrealistic, was used as a
guide in developing a series of logical, systematic steps that would
smooth the most common exaggerated and erratic demand problems while
adhering to resource limitation and simultaniety of production
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constraints--two of the -most significant considerations in the develop­
ment of a scheduling methodology for hot food production.
Comparative resource data were generated showing the optimum
and adjusted schedule requirements. Graphic presentation of personnel
resource profiles demonstrated the peaks and valleys of demand associated
with the use of fixed meal periods. Equipment resource data were pre­
sented in the form of daily utilization rates for each piece of equip­
ment. Such data could be used by the manager in considering and/or
selecting other alternatives to satisfy existing resource limitation
criteria or to impose additional resource limitations.
The RAPS Algorithm was determined, through executive analysis,
to be a systematic and feasible means of collecting resource allocation/
utilization data with specific application in the areas of menu planning
and analysis, facility design, and personnel development, both formally
and informally.
TABLE OF CONTENTS
CHAPTER PAGE
1. INTRODUCTION . . . . • . . . l
Identification of Problem l
Purpose of Study 4
2. REVIEW OF LITERATURE . . . . . . . . . . . . . . . 5
The Theory of Scheduling 6
Basic Considerations for Methodology Application 7
10
Quantitative Techniques for Deriving Data
Network-Based Project Management Techniques 15
The REST Algorithm 20
3. PROCEDURE . . . . . . . . . . . . . . . . . . . . . . . ��2
A Traditional food Production System 22
Description of the Hypothetical System 23
The RAPS Algorithm 35
Analysis of the RAPS Algorithm as a Management Tool 53
4. RESULTS AND DISCUSSION . . . . . . . . . . 54
The Procedural Flowchart Model 54
Application of the RAPS Algorithm to the
Hypothetical Food Production System 60
Analysis of the RAPS Algorithm 105
5. CONCLUSIONS, RECOMMENDATIONS, AND SUMMARY 110
Cone 1 us i ans 110
Recommendations 113
Summary 116
LIST OF REFERENCES 119
APPENDICES . 123
Appendix A 124
Appendix B 136
Appendix C 146
VITA . . . . 149
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LIST OF TABLES
TABLE PAGE
3.1. Major Equipment Used in Hot Food Production 33
3.2. Resource/Work Content Loading Sample . 47
o • • •
4.1. Standard Times Used in Activity Time Estimates for the
Five-Day Hot Food Menu . . . . . . o • • •o • • • • • 65
A.l. Daily Utilization Rates for Equipment Resources of the
Hypothetical Production Facility, Optimum and Adjusted 135
B.1. Menu of Hot Foods with Forecasted Demand to Serve
140
500 Clientele . . . . . . . . . . . . . . . .
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