Economic Advantages of CUSUM Control Charts for Variables

Abstract

CUSUM charts are usually recommended to be used to monitor the quality of a stable process when the expected shift is small. Here, a number of authors have shown that the average run length (ARL) performance of the CUSUM chart is better than that of the standard Shewhart chart. In this paper we address this question from an economic perspective. Specifically we consider the case where one is monitoring a stable process where the quality measurement is a variable and the underlying distribution is normal. We compare the economic performance of CUSUM and $$ \bar X$$ charts for a wide range of cost and system parameters in a large experiment using examples from the literature. We find that there are several situations in which CUSUM control charts have an economic advantage over $$ \bar X$$ charts. These situations are: 1. when there are high costs of false alarms and high costs of repairing a process; 2. when there are restrictions on sample size and sampling interval; 3. when there are several components of variance, and; 4. when there are statistical constraints on ARL.

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