Robust Tolerance Design for Failure Rate of Roadheader Cutting Unit Based on Human-machine Collaboration

doi:10.3901/JME.2025.03.077

Abstract

Abstract: The robust operation of the roadheader cutting unit is a necessary condition for the timely and high-quality completion of excavation work. Robust tolerance design for failure rate of cutting unit is an effective measure to meet the robust operation while reducing manufacturing costs. Aiming at the problems of large sample size of fault data, lack of relevant robustness optimization mathematical models, and difficulty in solving high-dimensional objective functions, a robust tolerance method for failure rate of cutting unit based on human-machine collaboration is proposed. This method is supported by the strong computing power of computers. Firstly, the human interval fuzzy reasoning knowledge and maximum likelihood estimation method are employed to fit a significant number of failure data and obtain an approximate estimation of components' failure rates. Secondly, a robustness metric function is designed based on the mathematical goal programming knowledge and n-fold Riemannian integrals, and a high-dimensional and high-order robustness optimization mathematical model is constructed. Then, the seeker optimization algorithm and algorithm parameter analysis knowledge are utilized to solve the problem, and a relatively optimal solution of the failure rate tolerance is obtained. Finally, a multi-dimensional fluctuation simulation strategy based on integration is designed to obtain the fluctuation curve of the cutting unit’s failure rate. The comparison results show that the proposed robust tolerance design method for failure rate of cutting unit based on human-machine collaboration is capable of obtaining the extended ranges of components’ failure rates, and the cutting unit’s robust performance is maintained at a high level. With the combined advancements of human cognitive ability and computer computing intelligence, the proposed robust tolerance design method can be further applied to other complex systems through adaptive adjustments.

Key words: failure rate of cutting unit, robust tolerance design, human-machine collaboration, maximum likelihood estimation, Riemann integral, seeker optimization algorithm

CLC Number:

TD421

CUI Kaiyue, HONG Zhaoxi, LOU Shanhe, YAN Weiyu, FENG Yixiong, TAN Jianrong. Robust Tolerance Design for Failure Rate of Roadheader Cutting Unit Based on Human-machine Collaboration[J]. Journal of Mechanical Engineering, 2025, 61(3): 77-90.

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