A particular difficulty arises when lean manufacturing principles are applied to temperature dependent processes. Specifically, when an interruption occurs, lean manufacturing advocates stopping the production line to find the “root cause” of the problem. However, interruptions in temperature dependent processes will cause work‐in‐progress and process equipment to cool down and quality problems are likely when production restarts. This difficulty could be countered through a detailed process model, but apart from the difficulty of creating perfect process models with accurate inputs, the use of such a system would separate shop floor operators from the problem‐solving process. Instead, a response to interruptions is sought in the form of a “script” of actions which can be used to train operators. In order to develop an appropriate script, a generic model of a set of temperature dependent processes is defined in which the states of processes and products are time dependent. A hypothetical profit function is defined for the processes and it is shown how this could be optimized by dynamic programming. The dynamic programming process is then translated into a script to guide operators in decision‐making during interruptions. The script is demonstrated with a simulation model of an extrusion process, and the results suggest that the new script will result in improved throughput and reduced scrap in the presence of interruptions.
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1 November 2003
Research Article|
November 01 2003
Lean manufacturing in temperature dependent processes with interruptions
W.L. Lee;
W.L. Lee
Singapore Institute of Manufacturing Technology, Singapore, and
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J.M. Allwood
J.M. Allwood
Institute for Manufacturing, University of Cambridge, Cambridge, UK
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Publisher: Emerald Publishing
Online ISSN: 1758-6593
Print ISSN: 0144-3577
© MCB UP Limited
2003
International Journal of Operations & Production Management (2003) 23 (11): 1377–1400.
Citation
Lee W, Allwood J (2003), "Lean manufacturing in temperature dependent processes with interruptions". International Journal of Operations & Production Management, Vol. 23 No. 11 pp. 1377–1400, doi: https://doi.org/10.1108/01443570310501899
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