Reliability allocation of industrial robot systems based on BP neural network and Pythagorean fuzzy numbers
XU Minjun
DONG Qiuxian
LIU Ruliang
LIU Jun
XIA Chenguang
FANG Xiaojie
Abstract：In order to ensure the industrial robot realizes the reliability goal,reliability allocation is a task to be accomplished in its manufacturing design stage.According to the characteristics of industrial robots,such as complex structure,high uncertainty,few samples,and failure correlation between component parts,a reliability allocation method for industrial robot systems based on BP neural network and Pythagorean fuzzy numbers was proposed.Using Copula function to establish a system reliability model,the failures of industrial robots were classified into three levels,the system level,the subsystem level,and the component level.By using the back propagation(BP)neural network,the system reliability,subsystem structure importance and subsystem complexity were taken as the input variables to complete the system-to-subsystem reliability allocation.The Pythagoras fuzzy number was introduced to score the influence factors of importance,environmental condition,technical level,maintainability,cost sensitivity and complexity,complete the reliability allocation from the subsystem level to the component level.The results show that the methodology achieves reliability goals and ensures reliability growth.
Keywords：Reliability allocationIndustrial robotCopula functionBP neural networkPythagorean fuzzy number
Publication Date：2025-08-15
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：10( 131-140 )