Models for cellular manufacturing systems design: matching processing requirements and operator capabilities

Cellular manufacturing systems comprise categorizing machines used in the firm's production system into cells dedicated to part families that have similar requirements in terms of tooling, setups and operations sequences. Although worker assignment to cells has a significant impact on cell effe...

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Veröffentlicht in:The Journal of the Operational Research Society Jg. 61; H. 5; S. 827 - 839
Hauptverfasser: Bhatnagar, R, Saddikuti, V
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Taylor & Francis 01.05.2010
Palgrave Macmillan
Palgrave Macmillan UK
Taylor & Francis Ltd
Schlagworte:
Applied sciences
Business and Management
Cells
cellular manufacturing systems
Coefficients
Datasets
Design
Efficiency metrics
Exact sciences and technology
Heuristics
Integer programming
Inventory control, production control. Distribution
layout
Linear programming
Machinery
Management
Manufacturing cells
Manufacturing processes
Mathematical programming
Modeling
Operational research and scientific management
Operational research. Management science
Operations research
Operations Research/Decision Theory
Optimization
planning
production
Production planning
Skills
Studies
Systems design
Technology
Theoretical Paper
Theoretical Papers
Workers
layout
planning
heuristics
optimization
production
cellular manufacturing systems
Cell formation
Human operator
Similarity
Machine operator
Layout problem
Modeling
Optimization
Tooling
Incidence matrix
Heuristic method
Cellular manufacturing
Sequential machine
Planning
ISSN:0160-5682, 1476-9360
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Cellular manufacturing systems comprise categorizing machines used in the firm's production system into cells dedicated to part families that have similar requirements in terms of tooling, setups and operations sequences. Although worker assignment to cells has a significant impact on cell effectiveness, scant attention has been paid to this issue in previous research. We present two models-sequential and concurrent-for cell formation. The sequential model uses a machine-part incidence matrix (MPIM)-based similarity coefficient while the concurrent model uses a similarity coefficient based on both MPIM and machine-operator incidence matrix (MOIM). Our results show that for 50 problem sets widely reported in literature, the concurrent model outperformed the sequential model in most cases. A measure quantifying the difference in MPIM and MOIM was developed and the relative out-performance of the concurrent model was shown to depend on the value of this measure.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0160-5682
1476-9360
DOI:10.1057/jors.2008.181