Confidence interval-based fuzzy testing approach for Six Sigma Quality Index

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Fuzzy testing method improves estimation accuracy of Six Sigma Quality Index, mitigating sampling errors and indicating a novel evaluation approach.

Fuzzy testing method improves estimation accuracy and addresses uncertainty in measurement data.
Findings show that the approach mitigates risk of misjudgment caused by sampling errors.
Analysis utilizes statistical inference to derive confidence intervals for the Six Sigma Quality Index.
This novel approach highlights the advantages over traditional statistical testing methods.

Chen et al. (2025) studied this question.

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Fuzzy testing method improves estimation accuracy of Six Sigma Quality Index, mitigating sampling errors and indicating a novel evaluation approach.