A novel reliability evaluation technique for stochastic-flow manufacturing networks with multiple production lines

Yi-Kuei Lin*, Ping Chen Chang

*Corresponding author for this work

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

This paper presents a novel technique to measure the performance of a stochastic-flow manufacturing network (SMN) which violates the so-called flow conservation law due to the failure rates of stations. We address the mission reliability, the probability of demand satisfaction, as a performance indicator for the SMN while considering both the stochastic capacities and the multiple production lines. First, we construct a manufacturing system as an SMN through a graphical transformation, and decompose the transformed SMN into several paths for further analysis. Subsequently, two algorithms for different scenarios are designed to generate all minimal capacity vectors that stations should provide to satisfy the given demand. The first scenario is for the SMN with identical production lines in parallel. The second scenario is for distinct production lines with common stations in the SMN. We derive the mission reliability in terms of minimal capacity vectors by applying the recursive sum of disjoint products (RSDP) algorithm. A decision making issue is also discussed to decide a reliable production strategy.

Original languageEnglish
Article number6327387
Pages (from-to)92-104
Number of pages13
JournalIEEE Transactions on Reliability
Volume62
Issue number1
DOIs
StatePublished - 1 Jan 2013

Keywords

  • Different failure rates
  • mission reliability
  • multiple production lines
  • reworking
  • stochastic-flow manufacturing network

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