Setup adjustment of multiple lots using a sequential monte carlo method

Zilong Lian, Bianca M. Colosimo, Enrique Del Castillo

Research output: Contribution to specialist publicationArticle

7 Citations (Scopus)

Abstract

A new sequential Monte Carlo (SMC) adjustment method is presented for solving the machine setup adjustment problem when process parameters are unknown. In setup adjustment problems, the mean of the distribution of the quality characteristic of parts can change from lot to lot due to an improper setup operation. It is shown how a first SMC approach has performance equivalent to a recently proposed Markov chain Monte Carlo method but at a small fraction of the computational cost, allowing for on-line control. A second, modified SMC rule that avoids unnecessary adjustments that can inflate the variance is also presented. A simulation approach is presented that allows tuning of the modified SMC rule to provide robust adjustment with respect to the unknown process parameters. Applications in short-run manufacturing processes are discussed.

Original languageEnglish (US)
Pages373-385
Number of pages13
Volume48
No3
Specialist publicationTechnometrics
DOIs
StatePublished - Aug 1 2006

Fingerprint

Sequential Monte Carlo Methods
Sequential Monte Carlo
Adjustment
Monte Carlo methods
Markov processes
Process Parameters
Tuning
Markov Chain Monte Carlo Methods
Costs
Unknown Parameters
Computational Cost
Manufacturing
Unknown
Simulation

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Applied Mathematics

Cite this

Lian, Zilong ; Colosimo, Bianca M. ; Castillo, Enrique Del. / Setup adjustment of multiple lots using a sequential monte carlo method. In: Technometrics. 2006 ; Vol. 48, No. 3. pp. 373-385.
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Setup adjustment of multiple lots using a sequential monte carlo method. / Lian, Zilong; Colosimo, Bianca M.; Castillo, Enrique Del.

In: Technometrics, Vol. 48, No. 3, 01.08.2006, p. 373-385.

Research output: Contribution to specialist publicationArticle

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