Opportunities for Improved Statistical Process Control

Publication Type

Journal Article

Publication Date

9-1997

Abstract

A Bayesian dynamic programming model builds on existing models to account for inspection delay, choice of keeping production going during inspection and/or restoration, and lot sizing. How dynamic statistical process control rules can improve on traditional, static ones is described. Numerical examples are explored and 9 opportunities for improvement are identified. Opportunities for improvement include: 1. Cancel some of the inspections called for by an optimal static rule when starting in control. 2. Inspect more frequently than called for by an optimal static rule once inspections begin, and inspect even more frequently than that when negative evidence is accumulated. 3. Utilize evidence from previous inspections to justify either restoration or another inspection. 4. Cancel inspections and hesitate to restore the process at the end of a production run. 5. Consider using scheduled restoration, in which restoration is carried out regardless of the results of any inspections.

Discipline

Business Administration, Management, and Operations

Research Areas

Operations Management

Publication

Management Science

Volume

43

Issue

9

First Page

1214

Last Page

1228

ISSN

0025-1909

Identifier

10.1287/mnsc.43.9.1214

Publisher

INFORMS

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