A Sequential-Interval Optimal Sampling Strategy Based on Reliability Prediction Under Wiener Process

Mengying Ren, Yubin Tian (), Xingyu Liu and Furi Guo
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Mengying Ren: School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China
Yubin Tian: Faculty of Computational Mathematics and Cybernetics, Shenzhen MSU-BIT University, Shenzhen 518172, China
Xingyu Liu: School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China
Furi Guo: Department of Mathematics and Statistics, Shanxi Datong University, Datong 037009, China

Mathematics, 2025, vol. 13, issue 11, 1-13

Abstract: For satellite electronic components characterized by high reliability and long lifespan, achieving improved efficiency in reliability prediction is essential when only a limited amount of data is available. Many studies have collected degradation data using uniform sampling strategies. In this work, we propose sequential-interval G- and D-optimal sampling strategies for in-orbit degradation data collection based on the Wiener process, aiming to enhance the efficiency of reliability prediction. Finally, a simulation study is performed to verify the effectiveness of the proposed strategies. This study utilizes both linear and nonlinear models of satellite MOSFETs and employs the Monte Carlo method.

Keywords: D-optimality; degradation data; G-optimality; reliability prediction; Wiener process (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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