A Novel Model Validation Method Based on Area Metric Disagreement between Accelerated Storage Distributions and Natural Storage Data

Bin Suo, Yang Qi, Kai Sun () and Jingyuan Xu
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Bin Suo: School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Yang Qi: School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Kai Sun: Institute of Microelectronics of the Chinese Academy of Sciences, Beijing 100029, China
Jingyuan Xu: Institute of Microelectronics of the Chinese Academy of Sciences, Beijing 100029, China

Mathematics, 2023, vol. 11, issue 11, 1-18

Abstract: It has been a challenge to quantify the credibility of the accelerated storage model until now. This paper introduces a quantitative measurement named the CMADT (Creditability Metric of Accelerated Degradation Test), which quantifies the credibility of the accelerated aging model based on available data. The relevant criterion data are obtained from the natural storage test. CMADT is a credibility metric obtained by measuring the difference in the metric area between the probability distribution of the accelerated storage model and its criterion data. In addition, the accelerated aging model might include multiple parameters resulting in several single-parameter CMADTs. This paper proposes a method that integrates several single-parameter CMADT metrics into a single metric to assess the overall credibility of the accelerated storage model. Moreover, CMADT is universal for different scales of sample data. The cases addressed in this paper show that CMADT helps designers and decision-makers judge the credibility of the result obtained by the accelerated storage model intuitively and makes it easier to compare various products horizontally.

Keywords: accelerated aging test; normal stress test; credibility evaluation; area metric; CMADT (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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