A clustering approach to identify the time of a step change in shewhart control charts

Ghazanfari, M ; Sharif University of Technology | 2008

547 Viewed
  1. Type of Document: Article
  2. DOI: 10.1002/qre.925
  3. Publisher: 2008
  4. Abstract:
  5. Control charts are the most popular statistical process control tools used to monitor process changes. When a control chart indicates an out-of-control signal it means that the process has changed. However, control chart signals do not indicate the real time of process changes, which is essential for identifying and removing assignable causes and ultimately improving the process. Identifying the real time of the change is known as the change-point estimation problem. Most of the traditional methods of estimating the process change point are developed based on the assumption that the process follows a normal distribution with known parameters, which is seldom true. In this paper, we propose clustering techniques to estimate Shewhart control chart change points. The proposed approach does not depend on the true values of the parameters and even the distribution of the process variables. Accordingly, it is applicable to both phase-I and phase-II of normal and non-normal processes. At the end, we discuss the performance of the proposed method in comparison with the traditional procedures through extensive simulation studies. Copyright ©2008 John Wiley & Sons, Ltd
  6. Keywords:
  7. Control theory ; Flow of solids ; Flowcharting ; Normal distribution ; Quality control ; Statistical process control ; Surface treatment ; Assignable causes ; Change points ; Change-point estimation ; Clustering ; Clustering approaches ; Clustering techniques ; Control chart ; Control chart signals ; Control charts ; Control signals ; Extensive simulations ; Process changes ; Process variables ; Real times ; Shewhart control charts ; Statistical processes ; Step changes ; True values ; Process control
  8. Source: Quality and Reliability Engineering International ; Volume 24, Issue 7 , 2008 , Pages 765-778 ; 07488017 (ISSN)
  9. URL: https://onlinelibrary.wiley.com/doi/10.1002/qre.925