A novel single composite Shewhart‐EWMA control chart for monitoring the process mean

Abstract

Statistical process monitoring (SPM) literature recommends the combination of Shewhart and exponentially weighted moving average (EWMA) schemes to improve the ability of the standalone Shewhart and EWMA monitoring schemes in detecting small to large shifts. The resulting scheme is named combined (or composite) Shewhart‐EWMA (CSEWMA) scheme. In this paper, a new single composite Shewhart‐EWMA (denoted as SCSEWMA) scheme for monitoring the mean when the process parameters are known or unknown is proposed using an additive weighted model. The flexibility of the proposed scheme is made possible by an additional weighing parameter that regulates its sensitivity towards shifts of different sizes. The new scheme is compared to the existing Shewhart, EWMA and CSEWMA X¯$\bar X$ schemes, and the results reveal the superiority of the proposed scheme over the latter schemes. Simulated and real‐life data are used to demonstrate the application and implementation of the proposed scheme.

Algorithm for Correlation Diagnosis in Multivariate Process Quality Based on Optimal Typical Correlated Component Pairs Group

“…(3) Take P as reference, draw the weighted correlation graph G * of y; (4) Find the MCST of G * ; (5) Obtain the OTCCPG of y according to the MCST; (6) For every component pair (y i ,y j ) in the OTCCPG, establish its T 2 control chart K ij ; (7) Establish the T 2 control chart K to monitor the correlation shift of all the quality components. The number of T 2 control charts in this diagnostic system is p. When K is normal, the correlation of all the quality components is under control.…”

“…In the whole formation of the product's quality, process quality is the most basic session because the product's quality will be influenced by every process' quality directly or indirectly, so process quality control is the essence of quality management in manufacturing. Theory of statistical process control (SPC) and its tools, that is, control chart proposed by Shewhart, achieved the goal of univariate process quality management [1][2][3][4]. But in modern manufacturing, many processes contain more than one quality components.…”

Algorithm for Correlation Diagnosis in Multivariate Process Quality Based on the Optimal Typical Correlated Component Pair Group

“…The theory of statistical process control (SPC) and its tools, that is, the control chart proposed by Shewhart, achieved the goal of univariate process quality management [1][2][3][4]. However, in modern manufacturing, many processes contain more than one quality component.…”

A multivariate process quality correlation diagnosis method based on grouping technique

“…The objective of managing univariate process quality was achieved by using Shewhart's control chart, which is a tool in the theory of statistical process control (SPC) 1 – 4 . But in modern manufacturing, there are many processes that involve more than one quality component.…”