A variables-type multiple-dependent-state sampling plan based on the lifetime performance index under a Weibull distribution

Verification and validation of product quality highly affects the success of product design and manufacturing processes as well as the long-term collaboration between buyers and suppliers. Lifetime testing for acceptance is the main bottleneck in verification and validation and often requires consid...

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Bibliographic Details
Published inAnnals of operations research Vol. 311; no. 1; pp. 381 - 399
Main Authors Wang, To-Cheng, Wu, Chien-Wei, Shu, Ming-Hung
Format Journal Article
LanguageEnglish
Published New York Springer US 01.04.2022
Springer
Springer Nature B.V
Subjects
Acceptance tests
Advanced manufacturing technologies
Business and Management
Combinatorics
Dependent variables
Design
Design parameters
Failure
Industrial engineering
Lifetime
Manufacturing
Methods
Operations research
Operations Research/Decision Theory
Optimization models
Performance indices
Product design
Product quality
Product testing
S.I. : Reliability Modeling with Applications Based on Big Data
Sampling
Suppliers
Theory of Computation
Variables
Verification
Weibull distribution
Taiwan
OC curve
Lifetime performance index
Weibull distribution
Acceptance sampling plan
Type-II right censoring
Multiple-dependent-state sampling plans
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Summary:Verification and validation of product quality highly affects the success of product design and manufacturing processes as well as the long-term collaboration between buyers and suppliers. Lifetime testing for acceptance is the main bottleneck in verification and validation and often requires considerable time and expense, especially in the current high-product-yield era. To establish a cost-effective and risk-controllable life testing sampling scheme, we propose a variables-type multiple-dependent-state (MDS) sampling plan using the lifetime performance index under a Weibull distribution with Type-II right censoring. The design parameters of the lifetime-capable MDS sampling plan are formulated as optimization models to minimize the required number of testing failures subject to nonlinear constraints for the desired lifetime capability levels and allowable risks regulated by the supplier and buyer. Compared with variable single sampling plans, the plan proposed herein is more cost-effective sampling and has greater discriminatory power. The applicability of the proposed plan is demonstrated through an example.
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-020-03655-z