Multiobjective Genetic Algorithm Approach to the Economic Statistical Design of Control Charts with an Application to X¯bar and S2 Charts. (16th April 2012)

• Record Type: Journal Article
• Authors: Faraz, Alireza; Saniga, Erwin
• Is Part Of: Quality and reliability engineering international. Volume 29:Number 3(2013:Apr.)
• Page Start: 407
• Page End: 415
• Publication Date: 2012-04-16
• Subjects: Reliability (Engineering) -- Periodicals; Quality control -- Periodicals; High technology -- Periodicals; 620.00452
• DOI: 10.1002/qre.1390
• Languages: English
• ISSNs: 0748-8017

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Control charts are the primary tools of statistical process control. These charts may be designed by using a simple rule suggested by Shewhart, a statistical criterion, an economic criterion, or a joint economic statistical criterion. Each method has its strengths and weaknesses. One weakness of the methods of design listed is their lack of flexibility and adaptability, a primary objective of practical mathematical models. In this article, we explore multiobjective models as an alternative for the methods listed. These provide a set of optimal solutions rather than a single optimal solution and thus allow the user to tailor their solution to the temporal imperative of a specific industrial situation. We present a solution to a well‐known industrial problem and compare optimal multiobjective designs with economic designs, statistical designs, economic statistical designs, and heuristic designs. Copyright © 2012 John Wiley &amp; Sons, Ltd.</p> </abstract>