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Intelligent modeling of complex manufacturing processes using hierarchical fuzzy basis function networks

机译:使用层次模糊基函数网络智能建模复杂制造过程

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This paper presents a generalized modeling approach to modeling of complex manufacturing processes. Fuzzy basis function networks with a novel training algorithm are used to capture the cause-effect relationships of complex manufacturing processes. The modeling scheme allows for utilization of the existing knowledge in the form of analytical models, experimental data and heuristic rules in developing a suitable model. The method is implemented for the surface grinding processes based on the hierarchical structure of fuzzy basis function networks proposed by Lee and Shin [21]. Process models for surface roughness and residual stress are developed based on the available grinding model structures with a small number of experimental data to demonstrate the concept. The accuracy of developed models is validated through independent sets of grinding experiments.
机译:本文介绍了复杂制造工艺建模的广义建模方法。模糊基函数网络采用新型训练算法捕获复杂制造过程的原因关系。建模方案允许以分析模型,实验数据和启发式规则的形式利用现有知识,在开发合适的模型中。该方法是基于李和胫骨提出的模糊基函数网络的层次结构的表面研磨过程来实现。基于具有少量实验数据的可用研磨模型结构来开发表面粗糙度和残余应力的过程模型,以展示该概念。通过独立的研磨实验验证开发模型的准确性。

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