Triple Sampling (X)over-Bar Control Chart for Gamma Process
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH(2024)
Univ Sains Malaysia
Abstract
Monitoring production processes to provide potential customers with quality products while utilising fewer resources and reducing the cost of inspection is a challenge to quality and industrial engineers. Aiming at developing an improved design using reduced sample sizes, this study proposes a triple sampling (TS) (X) over bar chart to monitor shifts in the process mean when the quality characteristic of interest follows the gamma distribution. Optimal parameters are determined by employing three optimisation procedures. The detection ability of the TS <(X)over bar chart is evaluated and contrasted with competing charts via the average number of observations to signal (ANOS), average run length (ARL) and expected ANOS (EANOS) criteria. When the TS <(X)over bar> chart is designed for detecting small and large shifts, it is noticed that the sample sizes at the first, second and third sampling stages are larger for detecting small shifts. Compared to its competitors, the TS <(X)over bar chart requires fewer observations on the average to signal a shift; hence, it uses resources more efficiently and incurs lower inspection costs. To aid in the implementation of the TS <(X)over bar chart, an illustrative example of monitoring the wafer process is provided. Overwhelming evidence based on reported results supports the TS <(X)over bar chart.
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Key words
Adaptive control charts,Average number of observations to signal,Average run length,Gamma distribution,Triple sampling (X)over-bar chart
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