Optimization design of control charts: A systematic review

Author:

Haridy Salah12ORCID,Maged Ahmed23ORCID,Alherimi Nadin1,Shamsuzzaman Mohammad1,Al‐Ali Sondos1

Affiliation:

1. Department of Industrial Engineering and Engineering Management College of Engineering University of Sharjah Sharjah United Arab Emirates

2. Benha Faculty of Engineering Benha University Benha Egypt

3. Department of Mechanical Engineering University of North Texas Denton Texas United States

Abstract

AbstractIn today's competitive landscape, fulfilling customer expectations and achieving a competitive edge are crucial for business success. These objectives can be attained by effective monitoring in both manufacturing and service sectors to enhance quality, reduce variation, and augment productivity. The control chart, a widely used tool for this purpose, has attracted significant attention from researchers for its ability to detect anomalies and manage out‐of‐control situations. The optimization of control charts, a central focus of this review, not only enhances the detection effectiveness but also maintains the desired false alarm rate, thus ensuring efficient process control without additional cost, complexity, or operational challenges for shop floor personnel. The optimization process involves adjusting charting parameters like the sample size, sampling interval, and control limits within a hypothesis testing framework, thereby achieving optimal system performance. Numerous optimization models have been developed to enhance control chart performance. This paper introduces a classification scheme to analyze and categorize the existing research on control chart optimization. By conducting a thorough review of more than 240 articles, the study pinpoints research gaps and offers valuable insights, thereby advancing the future research in this domain.

Funder

University of Sharjah

Publisher

Wiley

Reference265 articles.

1. A novel adaptive control chart with variable sample size, sampling interval and control limits: a three stage variable parameters (TSVP);Deheshvar A;Int J Bus Manag,2013

2. Some Applications of Statistical Methods to the Analysis of Physical and Engineering Data

3. A Discussion on Statistically-Based Process Monitoring and Control

4. Multivariate information in univariate control charts;Braun L;Stoch Qual Control,2007

5. Optimization Problems and Methods in Quality Control and Improvement

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