Abstract
In this paper, the Combined Shewhart-CUSUM control scheme has been proposed to monitor the production process when the quality characteristic follows exponential distribution to quickly detect the shift in the process. The simulated values of ARL are determined after the transformation of the data into approximate normal distribution by Nelson transformation method and adding Shewhart control limits to existing CUSUM Control Chart. Scheme parameters (value of k and h) and out of control ARL are calculated at various shift and at various in-control ARL. Parameters are also calculated to detect δ standard deviation shifts, which may be helpful to the quality control practitioners in designing the Combined Shewhart-CUSUM scheme when data is highly skewed.
Highlights
Statistical process control is the widely used technique for controlling the quality in manufacturing and service industry
It is noted that Shewhart (3 sigma) control chart for the mean is very useful if the shift in process parameters magnitude is 1.5 sigma or larger (Montgomery, 2018), but takes a large number of runs to detect a small constant shift in the process quality characteristic
In Statistical Process Control (SPC), many times a quality control engineer concerned to monitor the occurrence of events that can occur at any point within a continuous interval of time
Summary
Statistical process control is the widely used technique for controlling the quality in manufacturing and service industry. To overcome this problem with the c chart (Nelson, 1994) proposed to monitor these types of processes by different measurements, that is, the time between successive occurrences of the events and this random variable follows the exponential distribution.
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