Multivariate Control Charts for Individual Observations

Article

Tracy, Nola; Young, John; Mason, Robert   (1992, ASQC)   McNeese State University

Journal of Quality Technology    Vol. 24    No. 2
QICID: 11347    April 1992    pp. 88-95
List $10.00
Member $5.00

FOR A LIMITED TIME, ACCESS TO THIS CONTENT IS FREE!
You will need to be signed in.
New to ASQ? Register here.

Article Abstract

When p correlated process characteristics are being measured simultaneously, often individual observations are initially collected. The process data are monitored and special causes of variation are identified in order to establish control and to obtain a "clean" reference sample to use as a basis in determining the control limits for future observations. One common method of construction multivariate control charts is based on Hotelling's T2 statistic. Currently, when a process is in the start-up stage and only individual observations are available, approximate F and chi-square distributions are used to construct the necessary multivariate control limits. These approximations are conservative in this situation. This article presents an exact method, based on the beta distribution, for constructing multivariate control limits at the start-up stage. An example from the chemical industry illustrates that this procedure is an improvement over the approximate techniques, especially when the number of subgroups is small.

Keywords

Hotelling's T2 statistic,Multivariate quality control


Browse QIC Articles Chronologically:     Previous Article     Next Article

New Search

Featured advertisers





ASQ is a global community of people passionate about quality, who use the tools, their ideas and expertise to make our world work better. ASQ: The Global Voice of Quality.