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Showing 2 results for Process Capability
Sana Eftekhar, Ehsan Kharati-Koopaei, Soltan Mohammad Sadooghi-Alvandi,
Volume 9, Issue 2 (2-2016)
Abstract
Process capability indices are widely used in various industries as a statistical measure to assess how well a process meets a predetermined level of production tolerance. In this paper, we propose new confidence intervals for the ratio and difference of two Cpmk indices, based on the asymptotic and parametric bootstrap approaches. We compare the performance of our proposed methods with generalized confidence intervals in term of coverage probability and average length via a simulation study. Our simulation results show the merits of our proposed methods.
Dr. Robab Afshari,
Volume 16, Issue 2 (3-2023)
Abstract
Although the multiple dependent state sampling (MDS) plan is preferred over the conditional plans due to the small size required, it is impossible to use it in a situation where the quality of manufactured products depends on more than one quality characteristic. In this study, to improve the performance of the mentioned method, S^T_{pk}-based MDS plan is proposed, which is applicable to inspect products with independent and multivariate normally distributed characteristics. The principal component analysis technique is used to develop an application of the proposed plan in the presence of dependent variables. Moreover, optimal values of plan parameters are obtained based on a nonlinear optimization problem. Findings indicate that compared to S^T_{pk}-based variable single sampling and repetitive group sampling plans, the proposed method is the best in terms of required sample size and OC curve. Finally, an industrial example is given to explain how to use the proposed plan.
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