Simulation study reveals superior detection performance of new EWMA control charts for two-parameter exponential lifetime data, highlighting more sensitive quality monitoring.
Designing effective control charts is important for improving quality monitoring in lifetime studies. To address the challenges encountered in monitoring lifetime data, this paper proposes two EWMA charts for monitoring the location and scale parameters of the two‐parameter exponential distribution. The average run‐length profiles of the proposed charts are estimated using Monte Carlo simulation. Under steady‐state conditions, their performance is compared with existing EWMA and CUSUM charts using the expected weighted run‐length and relative mean index. The results show that the proposed EWMA charts outperform the existing EWMA and CUSUM charts. Finally, two real datasets are used to demonstrate the implementation and effectiveness of the proposed charts.
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Munir et al. (2026) studied this question.
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