Integration method for reliability assessment with multi-source incomplete accelerated degradation testing data

ABSTRACT

During the product life cycle, the lifetime information will be collected at each stage, mainly from different tests at the R&D phase, field usage, and maintenance. To comprehensively conduct reliability assessments, it generally requires the integration of multi-source datasets, even that from similar products. In this article, we considered the scenario that products have been arranged with several accelerated degradation tests (ADT) under different types of accelerated stresses with dependency. The obtained data is called incomplete ADT dataset with incomplete stress conditions which fails the traditional integration method for reliability assessments. A novel method is proposed to accomplish this task through mutually exclusive set (MES) theory. The probability assignments for each dataset are given through the union set of several MESs. Then, the multi-source ADT datasets are integrated with the assigned weights of probabilities. Finally, a simulation study and a real application are given to illustrate the effectiveness of the proposed methodology.

KEYWORDS:

• accelerated degradation testing
• incomplete data
• multiple sources
• reliability
• uncertainty

About the authors

Le Liu is a Reliability Engineer at Huawei Technologies. He received a Bachelor's degree in Quality and Reliability Engineering, and a Ph.D. degree in Systems Engineering from Beihang University in 2012 and 2017, respectively. His research interests include reliability tests and modeling.

 Xiao-Yang Li is an associate professor at the School of Reliability and Systems Engineering, Beihang University. She received a Ph.D. degree in Aerospace Systems Engineering from Beihang University in 2007. Her research interests include accelerated testing, prediction technology, and imprecise probability modeling.

 Tong-Min Jiang is an eminent professor at the School of Reliability and Systems Engineering, Beihang University. He received a Master's degree in Reliability Engineering from Beihang University in 1990. His research interests include reliability testing and environment engineering of product.

Funding

This work was supported in part by the National Natural Science Foundation of China (Grant No. 61603018 and 61104182) and the Fundamental Research Funds for the Central Universities (No. YWF-16-JCTD-A-02-06).

Additional information

Notes on contributors

Le Liu

Le Liu is a Ph.D. candidate at the School of Reliability and Systems Engineering, Beihang University. He received a Bachelor's degree in Quality and Reliability Engineering from Beihang University in 2012. His research interests include reliability modeling, accelerated testing, and uncertainty analysis.

Xiao-Yang Li

Xiao-Yang Li is an associate professor at the School of Reliability and Systems Engineering, Beihang University. She received a Ph.D. degree in Aerospace Systems Engineering from Beihang University in 2007. Her research interests include accelerated testing, prediction technology, and imprecise probability modeling.

Tong-Min Jiang

Tong-Min Jiang is an eminent professor at the School of Reliability and Systems Engineering, Beihang University. He received a Master's degree in Reliability Engineering from Beihang University in 1990. His research interests include reliability testing and environment engineering of product.