A Reliability Prediction Method for Industrial Robots Using Interval Analytic Hierarchy Process

Tudi Huang, Hua-Ming Qian, Jun Cai, Jinhua Mi and Hong-Zhong Huang ()
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Tudi Huang: University of Electronic Science and Technology of China
Hua-Ming Qian: University of Electronic Science and Technology of China
Jun Cai: University of Electronic Science and Technology of China
Jinhua Mi: University of Electronic Science and Technology of China
Hong-Zhong Huang: University of Electronic Science and Technology of China

A chapter in Reliability Analysis and Maintenance Optimization of Complex Systems, 2025, pp 35-44 from Springer

Abstract: Abstract In conventional reliability prediction methods employed for industrial robots, accurately estimating the degree of difference in reliability levels between evaluation objects and similar products poses a challenge. This paper introduces a novel approach to predicting the reliability of industrial robots based on the Interval Analytic Hierarchy Process (AHP) to address this limitation. The methodology involves an initial analysis of the relationship between the reliability of the entire machine and that of its subsystems. Subsequently, a reliability prediction model for the entire machine is formulated. During the prediction of subsystem reliability, the reliability data from analogous products are extensively leveraged. A comprehensive analysis of differences between the evaluation objects and similar products is conducted. The proposed methodology culminates in the establishment of a reliability correction factor evaluation model. This model is computed using the Interval AHP, facilitating the synthesis of deterministic information and fuzzy information to achieve a more comprehensive understanding of reliability.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-3-031-70288-4_3

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DOI: 10.1007/978-3-031-70288-4_3

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