Showing papers by "William H. Woodall published in 2002"
TL;DR: This paper presents a Markov chain model of the synthetic control chart and uses it to evaluate the zero-state and steady-state average run length (ARL) performance and alters the synthetic chart to achieve better ARL performance.
Abstract: A synthetic control chart designed to detect shifts in the process mean can be represented as a runs rule chart with a head start feature. A Markov chain model of the synthetic control chart is proposed for the evaluation of the zero-state and steady-st..
156 citations
TL;DR: In this paper, a robust control chart for ordinal data is described and the authors demonstrate its advantages over a commonly used approach for categorical data, which can be a cheaper alternative to measurement of a continuous variable.
Abstract: SYNOPTIC ABSTRACTEvery day, professionals use control charts to increase the quality of goods and services. These charts help by signaling when special causes of process variation occur so that they are investigated. An influence identified as changing process variability, i.e., an assignable cause, is removed or made a permanent part of the process depending on which action improves quality. To monitor a process, quality characteristic measurements form control chart statistics that indicate when some parameter of the measurements' distribution changes. Sometimes a process is effectively monitored using ordinal data, which can be a cheaper alternative to measurement of a continuous variable. Items are graded and simply counted. We describe a robust control chart for ordinal data and demonstrate its advantages over a commonly used approach for categorical data.
27 citations
TL;DR: In this article, the authors summarize the assumptions made regarding the out-of-control process shift in the economic design of multivariate control charts and address their consequences, and study the average run length (ARL) properties of the χ 2 control chart using a numerical example.
Abstract: It is an increasingly common practice to monitor several related quality characteristics of a product or process using a multivariate control chart procedure. Several types of multivariate control charts, including Hotelling's χ 2 and T 2 control charts, have been developed in attempts to improve monitoring by using the correlation structure that exists between quality characteristics. The purpose of this paper is to summarize the assumptions made regarding the out-of-control process shift in the economic design of multivariate control charts and to address their consequences. We study the average run length (ARL) properties of the χ 2 control chart using a numerical example and show that this chart can perform ineffectively under the assumed out-of-control conditions when designed using the economic approach. Following Healy,[1] we offer an alternative procedure that has improved ARL properties and overall performance. These results can be important to researchers and practitioners who are inter...
19 citations