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Imperfect production process with learning and forgetting effects

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  • M. Jaber
  • Z. Givi

Abstract

Wright’s learning curve (WLC) assumes every unit of production has an acceptable level of quality, which is not the case in many production environments. Many studies reported that a production process may go out-of-control therefore generating defective items requiring rework. Jaber and Guiffrida (Int J Prod Econ 127(1):27–38, 2004 ) have modified the WLC by accounting for rework time. In a later study, Jaber and Guiffrida (Eur J Oper Res 189(1):93–104, 2008 ) allowed for production interruption to restore the quality of the production process to reduce the number of defective items per lot. Although these works were the first analytical models that linked learning to quality, their results cannot be generalized as they considered a single (first) production cycle. This assumption ignores the transfer of learning that occurs between cycles in intermittent production environments. This paper addresses this limitation and considers the knowledge transferred to deteriorate because of forgetting. The results indicate that the performance function of the process has a convex form under certain conditions. The performance of the system improves with faster learning in production and rework, frequent process restorations, and transfer of learning between cycles. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • M. Jaber & Z. Givi, 2015. "Imperfect production process with learning and forgetting effects," Computational Management Science, Springer, vol. 12(1), pages 129-152, January.
  • Handle: RePEc:spr:comgts:v:12:y:2015:i:1:p:129-152
    DOI: 10.1007/s10287-014-0205-y
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    References listed on IDEAS

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    1. Jaber, Mohamad Y. & Guiffrida, Alfred L., 2008. "Learning curves for imperfect production processes with reworks and process restoration interruptions," European Journal of Operational Research, Elsevier, vol. 189(1), pages 93-104, August.
    2. repec:dar:wpaper:60485 is not listed on IDEAS
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