ECONOMIC-STATISTICAL DESIGN OF CUSUM CONTROL CHARTS UNDER EXPONENTIAL SHOCK MODEL
In a wide range of industrial applications, it is desirable that processes result in fault-free products. The manufacturing process must have limited variability around the target value for the product. In a process where a non-random factor leads to a change in the process under control, the out-of-control process is said to be the result of a process out of control of a defective product. Random agents are also caused by the accumulation of a number of small and unavoidable deviations that in the statistical quality control process, the random factor-affected process is usually considered as the process under control. The control chart discussed in this article is a cumulative control chart that is plotted by summing the pre-self statistical samples and comparing the result with the permissible control boundary detects how the process status is used to identify cost variables. Waiting time is the unit of time and cost of identifying the cause deviation as well as the decision variables that include sample size, sampling interval, and cumulative control chart decision distance, and reference value, economic statistical design. In this paper, the econometric design of control charts is performed under the cost model of Lorenzen and Vance.This paper deals with the economic performance of the cumulative control chart and compares it with the Schuharti control chart. The economic performance of the cumulative assembly control charts is more appropriate. It is necessary to explain the distribution mechanism of the exponential distribution process failure and all calculations are programmed with R software.
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