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Uncovering hidden capacity in overall equipment effectiveness management

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  • Hung, Yick-Hin
  • Li, Leon Y.O.
  • Cheng, T.C.E.

Abstract

An ongoing challenge in manufacturing management is to maximize the output volume from limited production capacity. Total productive maintenance (TPM) is a promising strategy to enhance machinery efficiency in factories by reducing downtime, speed, and quality losses. The associated metric of TPM is overall equipment effectiveness (OEE), which comprises three components, namely availability, performance, and quality, that measure the various aspects of production losses. However, output is restricted by the design cycle time in OEE, so purely improving OEE could only yield limited output increase. We argue that excess motion and processing in the ideal design cycle lead to design cycle losses. If these non-value-added activities as hidden capacity could be eliminated, production output would have considerable increment without extra investment. Adopting the input distance function approach, we show that the improvements gained from enhancing overall equipment availability and performance are different from the capacity unleashed by eliminating the design cycle losses. Accordingly, we propose value-added overall equipment effectiveness (VAOEE) as a novel metric to measure all the identified losses in search of hidden capacity. We provide three examples to demonstrate application of our novel productivity improvement approach in both semi-automatic and manual production in a non-continuous based plant.

Suggested Citation

  • Hung, Yick-Hin & Li, Leon Y.O. & Cheng, T.C.E., 2022. "Uncovering hidden capacity in overall equipment effectiveness management," International Journal of Production Economics, Elsevier, vol. 248(C).
  • Handle: RePEc:eee:proeco:v:248:y:2022:i:c:s0925527322000871
    DOI: 10.1016/j.ijpe.2022.108494
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    References listed on IDEAS

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    Cited by:

    1. Leoni, Leonardo & De Carlo, Filippo & Tucci, Mario, 2023. "Developing a framework for generating production-dependent failure rate through discrete-event simulation," International Journal of Production Economics, Elsevier, vol. 266(C).
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