Optimal Allocation of Work in Assembly Systems

We investigate how to allocate work in stochastic assembly systems so as to maximize throughput. We use Markov models for systems with exponential processing times and simulation-based methods for other probability distributions. We find that assembly systems should be unbalanced in the direction of...

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Bibliographic Details
Published inManagement science Vol. 39; no. 1; pp. 101 - 106
Main Authors Baker, Kenneth R, Powell, Stephen G, Pyke, David F
Format Journal Article
LanguageEnglish
Published Linthicum, MD INFORMS 01.01.1993
Institute of Management Sciences
Institute for Operations Research and the Management Sciences
SeriesManagement Science
Subjects
Applied sciences
assembly line
Assembly lines
Exact sciences and technology
Feeder lines
Markov analysis
Markov processes
Operational research and scientific management
Operational research. Management science
Parallel lines
Process engineering
Production efficiency
Production planning
production system design
Production systems
Production technology
Scheduling, sequencing
Systems design
throughput
Time & motion studies
Work stations
Production system
Assembly line
Work load
Balancing
Exponential distribution
Processing time
Scheduling
Markov model
Design
Production rate
Simulation
Optimal allocation
Curve fitting
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Summary:We investigate how to allocate work in stochastic assembly systems so as to maximize throughput. We use Markov models for systems with exponential processing times and simulation-based methods for other probability distributions. We find that assembly systems should be unbalanced in the direction of assigning less work to assembly and more to component stations. We also find that greater parallelism offers greater opportunity for improvement.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0025-1909
1526-5501
DOI:10.1287/mnsc.39.1.101