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Title: Multiple objective optimization in reliability demonstration test

Abstract

Reliability demonstration tests are usually performed in product design or validation processes to demonstrate whether a product meets specified requirements on reliability. For binomial demonstration tests, the zero-failure test has been most commonly used due to its simplicity and use of minimum sample size to achieve an acceptable consumer’s risk level. However, this test can often result in unacceptably high risk for producers as well as a low probability of passing the test even when the product has good reliability. This paper explicitly explores the interrelationship between multiple objectives that are commonly of interest when planning a demonstration test and proposes structured decision-making procedures using a Pareto front approach for selecting an optimal test plan based on simultaneously balancing multiple criteria. Different strategies are suggested for scenarios with different user priorities and graphical tools are developed to help quantify the trade-offs between choices and to facilitate informed decision making. As a result, potential impacts of some subjective user inputs on the final decision are studied to offer insights and useful guidance for general applications.

Authors:
 [1];  [2];  [1]
  1. Univ. of South Florida, Tampa, FL (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOD; USDOE
OSTI Identifier:
1329901
Report Number(s):
LA-UR-15-29249
Journal ID: ISSN 0022-4065
Grant/Contract Number:  
AC52-06NA25396
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Quality Technology
Additional Journal Information:
Journal Volume: 48; Journal Issue: 4; Journal ID: ISSN 0022-4065
Publisher:
American Society for Quality (ASQ)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; mathematics; Bayesian analysis; consumer's risk; decision making; pareto front; producer's risk; trade-offs

Citation Formats

Lu, Lu, Anderson-Cook, Christine Michaela, and Li, Mingyang. Multiple objective optimization in reliability demonstration test. United States: N. p., 2016. Web.
Lu, Lu, Anderson-Cook, Christine Michaela, & Li, Mingyang. Multiple objective optimization in reliability demonstration test. United States.
Lu, Lu, Anderson-Cook, Christine Michaela, and Li, Mingyang. Sat . "Multiple objective optimization in reliability demonstration test". United States. https://www.osti.gov/servlets/purl/1329901.
@article{osti_1329901,
title = {Multiple objective optimization in reliability demonstration test},
author = {Lu, Lu and Anderson-Cook, Christine Michaela and Li, Mingyang},
abstractNote = {Reliability demonstration tests are usually performed in product design or validation processes to demonstrate whether a product meets specified requirements on reliability. For binomial demonstration tests, the zero-failure test has been most commonly used due to its simplicity and use of minimum sample size to achieve an acceptable consumer’s risk level. However, this test can often result in unacceptably high risk for producers as well as a low probability of passing the test even when the product has good reliability. This paper explicitly explores the interrelationship between multiple objectives that are commonly of interest when planning a demonstration test and proposes structured decision-making procedures using a Pareto front approach for selecting an optimal test plan based on simultaneously balancing multiple criteria. Different strategies are suggested for scenarios with different user priorities and graphical tools are developed to help quantify the trade-offs between choices and to facilitate informed decision making. As a result, potential impacts of some subjective user inputs on the final decision are studied to offer insights and useful guidance for general applications.},
doi = {},
journal = {Journal of Quality Technology},
number = 4,
volume = 48,
place = {United States},
year = {2016},
month = {10}
}

Journal Article:
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