›› 2016, Vol. 22 ›› Issue (第3期): 728-737.DOI: 10.13196/j.cims.2016.03.016

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Decision-making method for used components remanufacturing process plan based on modified FNN

  

  • Online:2016-03-31 Published:2016-03-31
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.51305470,51475059),and the Fundamental Research Funds for the Central Universities,China(No.CDJZR12110076).

基于改进模糊神经网络的废旧零部件再制造工艺方案决策方法

李聪波1,冯亚1,杜彦斌2,李玲玲1   

  1. 1.重庆大学机械传动国家重点实验室
    2.重庆工商大学制造装备机构设计与控制重庆市重点实验室
  • 基金资助:
    国家自然科学基金资助项目(51305470,51475059);中央高校基本科研业务费资助项目(CDJZR12110076)。

Abstract: Due to the various damage conditions of used components and different quality requirements for reconditioning operations,the remanufacturing process plans would be uncertain and fuzzy.To ensure the optimal remanufacturing process plan,a decision-making problem model was established based on describing the features inherent in remanufacturing process,and a modified Takagi-Sugeno Fuzzy Neural Network (T-S FNN) method was introduced to obtain the optimal decision-making model of remanufacturing process plan.The method was applied in the remanufacturing process planning of a machine tool plant's waste machine tool spindle to analyze its performance with Matlab programming,and the effectiveness was verified by comparing with the traditional FNN method.

Key words: remanufacturing, process plan, decision-making method, takagi-sugeno fuzzy neural network

摘要: 鉴于废旧零部件损伤状况及其再制造质量要求的差异性导致再制造工艺方案具有不确定性和模糊性,为确定最优再制造工艺方案,在对废旧零部件再制造工艺过程特征问题进行描述的基础上,建立了再制造工艺方案优化决策模型;提出一种基于改进T-S模糊神经网络的再制造工艺方案决策方法,并对该模型进行了求解。将所提出的方法应用到某机床厂废旧机床主轴再制造中,运用MATLAB编程实现了再制造工艺方案的优化决策,并通过与传统模糊神经网络方法进行性能对比,验证了所提出方法的有效性。

关键词: 再制造, 工艺方案, 决策方法, T-S模糊神经网络

CLC Number: