Control chart limits are often calculated using parameter estimates from an in-control Phase I reference sample. In Phase II monitoring, statistics based on new samples are compared with the estimated control limits to monitor for departures from the in..

Effects of Parameter Estimation on Control Chart Properties; A Literature Review

In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as principal components analysis (PCA) and partial lest squares (PLS). Finally, we describe the most significant methods for the interpretation of an out-of-control signal.

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Multivariate statistical process control charts: an overview

There are many applications of control charts in health-care monitoring and in public-health surveillance. We introduce these applications to industrial practitioners and discuss some of the ideas that arise that may be applicable in industrial monitoring. The advantages and disadvantages of the charting methods proposed in the health-care and public-health areas are considered. Some additional contributions in the industrial statistical process control literature relevant to this area are given. There are many application and research opportunities available in the use of control charts for health-related monitoring.

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The Use of Control Charts in Health-Care and Public-Health Surveillance

Multivariate Statistical Process Control Charts: An Overview

The use of control charts in health-care and public-health surveillance

The use of control charts is considered for situations in which the quality of a process or product is better characterized by a relationship between a response variable and one or more explanatory variables than by use of a univariate quality character..

Using Control Charts to Monitor Process and Product Quality Profiles

We compare the performance of two phase II monitoring schemes for linear profiles, one based on the classical calibration method monitoring the deviations from the regression line (referred to as the NIST method) and the second based on individually monitoring the parameters of the linear profile (referred to as the KMW method). The comparison criterion is average run length performance under different sustained shifts in the intercept, slope and error standard deviation of the linear calibration line. A simulation study shows that the NIST method performs poorly compared to the combined control charting scheme of the KMW method.

Performance evaluation of two methods for online monitoring of linear calibration profiles

Robust parameter design is one of the important tools used in Design for Six Sigma. In this article, we present an application of the generalized linear mixed model (GLMM) approach to robust design and analysis of signal–response systems. We propose a split-plot approach to the signal–response system characterized by two variance components—within-profile variance and between-profile variance. We demonstrate that explicit modeling of variance components using GLMMs leads to more precise point estimates of important model coefficients with shorter confidence intervals. Copyright © 2009 John Wiley & Sons, Ltd.

Analysis of signal-response systems using generalized linear mixed models

Reliable and cost effective multistage interconnection networks (MINs) are the backbone of efficient distributed computing in supercomputer systems. In this paper new 3×3, 4×2, and 4×4 switching element (SE) structures are introduced which can be employed in various existing MINs to provide enhanced reliability at much reduced cost. The reliability function of proposed as well as the existing SEs have been formulated on basis of which their reliability values have been computed. The computed reliability values of all SEs (existing and proposed ones) have been compared and analyzed. The achieved results clearly depicts that the proposed SEs possess higher reliability and can replace the existing SEs of similar size without changing the existing design of MIN to improve reliability.

Shilpa Gupta

Papers

Using Control Charts to Monitor Process and Product Quality Profiles

Performance evaluation of two methods for online monitoring of linear calibration profiles

Analysis of signal-response systems using generalized linear mixed models

Design and Reliability Evaluation of Switching Element for Improving the QoS of Multistage Interconnection Network