The aim of this paper is to present a synthetic chart based on the non‐central chi‐square statistic that is operationally simpler and more effective than the joint X¯ and R chart in detecting assignable cause(s). This chart will assist in identifying which (mean or variance) changed due to the occurrence of the assignable causes.
The approach used is based on the non‐central chi‐square statistic and the steady‐state average run length (ARL) of the developed chart is evaluated using a Markov chain model.
The proposed chart always detects process disturbances faster than the joint X¯ and R charts. The developed chart can monitor the process instead of looking at two charts separately.
The most important advantage of using the proposed chart is that practitioners can monitor the process by looking at only one chart instead of looking at two charts separately.
Costa, A. and Rahim, M. (2006), "A synthetic control chart for monitoring the process mean and variance", Journal of Quality in Maintenance Engineering, Vol. 12 No. 1, pp. 81-88. https://doi.org/10.1108/13552510610654556Download as .RIS
Emerald Group Publishing Limited
Copyright © 2006, Emerald Group Publishing Limited