A single X chart outperforming the joint X &amp; R and X &amp; S charts for monitoring mean and variance

Process monitoring is regarded as a continuous phenomenon requiring careful consideration to acquire an enhanced output quality. Dispersion and location are significant parameters in the entire process, and timely detection of the changes that occur in a stable process is needed. Today, quality practitioners recommend using a single charting setup offering better capability of detecting joint changes in the parameters of a process. As provided in the literature, a detailed review paper for simultaneous monitoring is conducted in 2013 which many reaserchers were attracted to publish papers in this field. In this paper, a meticulous content analysis (on the basis of 59 reviewed papers in the field of joint monitoring from 2013 to 2021) is exploited to classify the papers that includes joint control charts for statistical process monitoring (SPM), to identify the potential topics and present some suggestions for further studies in simultaneous monitoring.

Section: Analytic Resultsmentioning

confidence: 99%

A literature review on joint control schemes in statistical process monitoring

Jalilibal

Amiri

Khoo

2022

Optimization design of control charts: A systematic review

Haridy,

Maged,

Alherimi

et al. 2024

Self Cite

In 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.

A Control Chart for the Joint Monitoring of Mean and Variance With Klein's Supplementary Rule

Quinino,

Costa,

Trindade

2024

Supplementary run rules have been employed since the 1950s to enhance the performance of control charts, such as the control chart, which aims to control the process mean, or control chart, which aims to control the process variance. One simple, effective, and popular suggestion is Klein's 2‐of‐2, which signals an out‐of‐control process only when two sequential sample averages are observed above the upper control limit or below the lower control limit. We propose to implement Klein's 2‐of‐2 for a more complex control chart, the joint control chart, which aims to simultaneously monitor the mean and the variance of a process. Compared with the traditional control chart, using this rule for the control chart reduces the average run length (ARL) and standard deviation of the run length (SDRL) for detecting small process shifts while maintaining high applicability owing to the ease of use in employing the 2‐of‐2 rule in practical environments. Klein's run rule was implemented in the control chart through a 15‐state Markov chain, and its performance was compared with the basic control chart as well as the exponentially weighted moving average (EWMA) chart, known to have excellent capabilities in detecting small process average shifts at the cost of a more complex control scheme. The newly proposed Klein control chart demonstrated superior performance compared to the traditional control chart and competitive performance even against the more complex joint EWMA control chart.