A unified framework for probabilistic sequential tolerance control

Ronald G. McGarvey, Tom M. Cavalier, Enrique Del Castillo, E. Amine Lehtihet

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Sequential tolerance control (STC) is a methodology that uses available measurement information at the completion of one manufacturing operation to position the set point for subsequent operations. It has been shown that STC can lead to inferior solutions when the manufacturing process distributions are skewed. This paper presents an adaptive sphere-fitting method (ASF-STC) that adjusts for such skewness. ASF-STC requires as inputs both the direction of skewness and the probability distribution parameters for each operation. Heuristic methods for estimating each of these inputs are presented. Through computational testing, ASF-STC is shown to offer significant improvements over STC when such skewness exists.

Original languageEnglish (US)
Pages (from-to)1443-1453
Number of pages11
JournalInternational Journal of Production Research
Volume42
Issue number7
DOIs
StatePublished - Apr 1 2004

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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