A novel metric for determining the constraining effect of resources in manufacturing via simulation

Brian Kernan, Andrew Lynch, Dang Tung, Con Sheahan

Research output: Contribution to journalArticlepeer-review

Abstract

This paper provides a novel method for determining the constraining effect of resources in a manufacturing system using discrete event simulation. Traditionally manufacturing systems are constrained by one or more bottlenecks. Eliminating or mitigating the bottleneck will speed up the system throughput. However, bottlenecking resources generally only refer to machines, and primarily focus on flow-shops not job-shops. One important resource we believe that is often overlooked is workers and their associated skills, and we propose that a particular skill could be flagged as a bottleneck resource. We define new metrics known as resource constraint metrics (RCM) for measuring the constraining effect of a resource on the entire manufacturing system. These metrics are flexible and differentiate between the constraining effects of machines and their requested skills. The metrics can also deal with complex workflows with alternative routing, alternative resources, calendars (a necessary consideration when dealing with workers), worker performance, and multiple modes of operation of machines (e.g. run, setup, and maintenance). The use of RCMs in simulation aids in real-world decision-making, by determining which resource should be focussed on and improved to reduce the overall system feeling constrained. This will have the effect of increasing throughput or at least providing the capacity for increased throughput.

Original languageEnglish
Pages (from-to)3565-3584
Number of pages20
JournalInternational Journal of Production Research
Volume49
Issue number12
DOIs
Publication statusPublished - 15 Jun 2011

Keywords

  • enterprise
  • machine
  • manufacturing
  • resource
  • skill
  • starvation

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