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Volume 10
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10.3390/app10217591
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Article

An Adaptive Bayesian Melding Method for Reliability Evaluation Via Limited Failure Data: An Application to the Servo Turret

by
Bo Sun
1,2,
Zhaojun Yang
1,2,
Narayanaswamy Balakrishnan
3,
Chuanhai Chen
1,2,*,
Hailong Tian
1,2,4,* and
Wei Luo
1,2
1
Key Laboratory of CNC Equipment Reliability, Ministry of Education, Jilin University, Changchun 130025, China
2
School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China
3
Department of Mathematics and Statistics, McMaster University, Hamilton, ON L8S 4K1, Canada
4
College of Materials Science and Engineering, Jilin University, Changchun 130025, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2020, 10(21), 7591; https://doi.org/10.3390/app10217591
Submission received: 23 July 2020 / Revised: 16 October 2020 / Accepted: 23 October 2020 / Published: 28 October 2020
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Abstract

In the early stage of product development, reliability evaluation is an indispensable step before launching a product onto the market. It is not realistic to evaluate the reliability of a new product by a host of reliability tests due to the limiting factors of time and test costs. Evaluating the reliability of products in a short time is a challenging problem. In this paper, an approach is proposed that combines a group of experts’ judgments and limited failure data. Novel features of this approach are that it can reflect various kinds of information without considering the individual weight and reduces aggregation error in the uncertainty quantification of multiple inconsistent pieces of information. First, an expert system is established by the Bayesian best–worst method and fuzzy logic inference, which collects and aggregates a group of expert opinions to estimate the reliability improvement factor. Then, an adaptive Bayesian melding method is investigated to generate a posterior by inaccurate prior knowledge and limited test data; this method is made more computationally efficient by implementing an improved sampling importance resampling algorithm. Finally, an application for the reliability evaluation of a subsystem of a CNC lathe is discussed to illustrate the framework, which is shown to validate the reasonability and robustness of our proposal.
Keywords: reliability evaluation; product development; bayesian inference; reliability improvement; servo turret reliability evaluation; product development; bayesian inference; reliability improvement; servo turret

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MDPI and ACS Style

Sun, B.; Yang, Z.; Balakrishnan, N.; Chen, C.; Tian, H.; Luo, W. An Adaptive Bayesian Melding Method for Reliability Evaluation Via Limited Failure Data: An Application to the Servo Turret. Appl. Sci. 2020, 10, 7591. https://doi.org/10.3390/app10217591

AMA Style

Sun B, Yang Z, Balakrishnan N, Chen C, Tian H, Luo W. An Adaptive Bayesian Melding Method for Reliability Evaluation Via Limited Failure Data: An Application to the Servo Turret. Applied Sciences. 2020; 10(21):7591. https://doi.org/10.3390/app10217591

Chicago/Turabian Style

Sun, Bo, Zhaojun Yang, Narayanaswamy Balakrishnan, Chuanhai Chen, Hailong Tian, and Wei Luo. 2020. "An Adaptive Bayesian Melding Method for Reliability Evaluation Via Limited Failure Data: An Application to the Servo Turret" Applied Sciences 10, no. 21: 7591. https://doi.org/10.3390/app10217591

APA Style

Sun, B., Yang, Z., Balakrishnan, N., Chen, C., Tian, H., & Luo, W. (2020). An Adaptive Bayesian Melding Method for Reliability Evaluation Via Limited Failure Data: An Application to the Servo Turret. Applied Sciences, 10(21), 7591. https://doi.org/10.3390/app10217591

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