| Summary: | === Control charts are used to effectively monitor and determine whether a process is in-control or out-of-control. The properties of EWMA control charts on a single process have been discussed by many researchers. They have proved that EWMA control charts detect small shifts in means or variances more quickly than the traditional Shewhart control charts. However, many products are currently produced in several dependent process steps. In this article, (1) we propose three kinds of EWMA control charts, - , - , and a combined control charts, to monitor the process mean and variance for a single process step, and (2) extend the three kinds of EWMA control charts in (1) to control two dependent steps. The performance of the proposed control charts is measured by using the Markov chain approach. The application of the proposed control charts is illustrated by using some numerical examples, and the performance of the proposed charts is compared by using some numerical examples. The adjusted average time to signal (AATS) and the adjusted average samples to signal (ANOS) are calculated to measure the performance of the proposed EWMA control charts by Markov chain approach. A data set consisting of the measurements of the inside diameter of the cylinder bores in an engine block example illustrates the applications of the three kinds of EWMA control charts for a single step and a empirical automobile braking system example illustrates the applications of the three kinds of EWMA control charts for two dependent steps. Moreover, their performances are compared by some numerical analysis results.
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