4.7 Article

Reliability acceptance sampling plan for degraded products subject to Wiener process with unit heterogeneity

Journal

RELIABILITY ENGINEERING & SYSTEM SAFETY
Volume 229, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2022.108877

Keywords

Acceptance sampling plan; Degradation data; Wiener process; Unit heterogeneity; Sampling plan; Decision-making criterion

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This paper proposes an optimal ASP design method considering the unit heterogeneity, determines the optimal test time and sample size by maximizing the determinant of the Fisher information matrix, simplifies the acceptance test problem by using the average degradation rate as the acceptance index, and demonstrates the feasibility of the method through simulation and a real example.
The acceptance sampling plan (ASP), designed with the degradation data following the Wiener process, is widely used to verify the reliability requirements of products. Previous studies mainly designed ASPs under the given sampling plan, which lacked the justification of the sampling plan; furthermore, they ignored the unit hetero-geneity of products in the degradation modeling, which affects the description accuracy of risks. To solve the above problems, this paper proposes an optimal ASP design method considering the unit heterogeneity. Firstly, the determinant of the Fisher information matrix is used to characterize the parameters estimation accuracy, under the cost requirement, the optimal test time and sample size are determined by maximizing the determi-nant, and an optimal sampling plan is obtained. Then, with the likelihood ratio order and the monotonicity of the average failure time on the average degradation rate, the average degradation rate is taken as the acceptance index to effectively simplify the original acceptance test problem. On this basis, the decision-making criterion considering the existence of ASP is obtained by solving the risk constraint equations of both parties. Finally, the simulation and a real example are presented to demonstrate the implementation and feasibility of the proposed method.

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