Journal article
Worker-cell assignment: The impact of organizational factors on performance in cellular manufacturing systems
Computers & industrial engineering, Vol.127, pp.1101-1114
01/2019
DOI: 10.1016/j.cie.2018.11.050
Abstract
•Worker grouping-assignment is examined in cellular manufacturing configurations.•Knowledge transfer has a significant positive effect on system efficiency.•Highest levels of between-cell heterogeneity result in highest system efficiency.•In serial structures, system dimensionality is significant for system efficiency.•Systems with knowledge transfer and fewer cells shows higher efficiency.
This study addresses worker-cell assignment of heterogeneous workers in various cellular manufacturing structures while considering between-cell heterogeneity, cell size, and system size as organizational factors. Workforce heterogeneity is considered based on individual learning characteristics, which include individual learning by doing and learning by knowledge transfer. Prior research demonstrated the impact of knowledge transfer on system performance as part of the assignment of workers. However, research related to the worker-cell assignment considering workforce heterogeneity and knowledge transfer is scarce. In the current study, different organizational factors are investigated to evaluate their effects on system performance and their relevance for the worker-cell assignment problem. This work contributes to the development of managerial insights to assist organizational managers in workforce management decisions in scenarios where more complex mathematical optimization methods are impractical.
Details
- Title: Subtitle
- Worker-cell assignment: The impact of organizational factors on performance in cellular manufacturing systems
- Creators
- Yaileen M Méndez-VázquezDavid A Nembhard - Oregon State University
- Resource Type
- Journal article
- Publication Details
- Computers & industrial engineering, Vol.127, pp.1101-1114
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.cie.2018.11.050
- ISSN
- 0360-8352
- eISSN
- 1879-0550
- Language
- English
- Date published
- 01/2019
- Academic Unit
- Business Analytics; Industrial and Systems Engineering
- Record Identifier
- 9984187054102771
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