Designing a Control Chart for Gamma Distribution through Repetitive Sampling with Imprecise Data
DOI:
https://doi.org/10.23055/ijietap.2024.31.6.10135Abstract
This article introduces an innovative control chart for gamma distribution monitoring in scenarios marked by uncertainty. The study involves determining control chart coefficients—namely, in-control probability, out-of-control probability, and average run lengths. These parameters are derived using the neutrosophic interval method, assuming the normal distribution's symmetrical property. The newly devised control chart's performance is evaluated through measurements of average run lengths across varying process conditions in an uncertain environment. The article explores the chart's behavior in both in-control and out-of-control situations, considering different magnitudes of shifts. Additionally, a comparative analysis with an existing control chart highlights the proposed chart's strengths. A real-world case study from the industrial sector is presented to illustrate practical applicability. Both simulation and real-world examples demonstrate the efficiency of the proposed control chart in swiftly detecting out-of-control processes.
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