Complexity analysis of an operation in demand-based manufacturing

In demand-based production systems with stochastic demand arrival times, operations often take place in random and long-time intervals. Therefore, traditional learning curve models may not be a good fit for estimating the operation time (OT) in such production environments. Moreover, the complexity...

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Bibliographic Details
Published inInternational journal of production research Vol. 49; no. 17; pp. 5303 - 5315
Main Authors Shafiei-Monfared, S., Jenab, K.
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis Group 01.09.2011
Taylor & Francis
Taylor & Francis LLC
Subjects
Applied sciences
Arrivals
Comparative analysis
Complexity
Complexity theory
Demand
demand-based production systems
Exact sciences and technology
human cognitive
Inventory control, production control. Distribution
learning curve
Learning curves
Manufacturing
Marketing
Mathematical models
Operational research and scientific management
Operational research. Management science
Segments
stochastic demand times
Stochasticity
Studies
Breakpoint
complexity
Statistical analysis
Task complexity
Human operator
Make to order
demand-based production systems
Complex system
Cognition
Complexity measure
stochastic demand times
Modeling
Demand factors
Human factor
Arrival time
Time interval
human cognitive
learning curve
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Summary:In demand-based production systems with stochastic demand arrival times, operations often take place in random and long-time intervals. Therefore, traditional learning curve models may not be a good fit for estimating the operation time (OT) in such production environments. Moreover, the complexity of an operation is another influential factor in OT that is not quantified. In this article, human cognitive and complexity factors in demand-based production systems with stochastic demand arrival time are studied. Performing statistical analysis, a double segment learning curve is developed that is a best fit for OT with breakpoint feature. The breakpoint indicates the required number of orders received to reach the mastery level of performing a certain operation. A comparative analysis among existing and the double segment learning curve models is performed and the operation complexity measure is derived from the model.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2010.518993