Abstract

A bounded adjustment strategy is an important link between statistical process control and engineering process control (or closed-loop feedback adjustment). The optimal bounded adjustment strategy for the case of a single variable has been reported in the literature and recently a number of publications have enhanced this relationship (but still for a single variable). The optimal bounded adjustment strategy for a multivariate processes (of arbitrary dimension) is derived in this article. This uses optimization and exploits a symmetry relationship to obtain a closed-form solution for the optimal strategy. Furthermore, a numerical method is developed to analyze the adjustment strategy for an arbitrary number of dimensions with only a one-dimensional integral. This provides the link between statistical and engineering process control in the important multivariate case. Both infinite- and finite-horizon solutions are presented along with a numerical illustration.

Original languageEnglish (US)
Pages (from-to)746-752
Number of pages7
JournalIIE Transactions (Institute of Industrial Engineers)
Volume42
Issue number10
DOIs
StatePublished - Oct 2010

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Process control
Statistical process control
Process engineering
Numerical methods
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Keywords

  • Dynamic programming
  • statistical quality control
  • stochastic control

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

Cite this

Optimal multivariate bounded adjustment. / Runger, George; Lian, Zilong; Del Castillo, Enrique.

In: IIE Transactions (Institute of Industrial Engineers), Vol. 42, No. 10, 10.2010, p. 746-752.

Research output: Contribution to journalArticle

Runger, George ; Lian, Zilong ; Del Castillo, Enrique. / Optimal multivariate bounded adjustment. In: IIE Transactions (Institute of Industrial Engineers). 2010 ; Vol. 42, No. 10. pp. 746-752.
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