A module classification method for light industrial equipment based on improved NSGA2-FCM algorithm

Hui Zheng ¹

Hanwen Guo ¹

Pang Tonglin ¹

Zijian Guo ¹

Xiao Guo ¹

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Tianjin University of science and Technology |

Publication type: Posted Content

Publication date: 2023-06-13

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DOI: 10.21203/rs.3.rs-2893445/v1

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Abstract

To solve the problem that the traditional clustering algorithm tends to fall into local optimum when dividing modules, the initialization strategy of NSGA2 algorithm is improved, and an improved NSGA2-FCM algorithm is proposed for clustering analysis in combination with FCM algorithm. First, FBS mapping is used to model the functional structure of the product system and identify the relationship between the functional structures of the product. Secondly, the relevant synthesis matrix is constructed based on the relationship between the driving factors of module division, and finally, the improved NSGA2-FCM algorithm is used to cluster the product to arrive at the best module division solution. The paper concludes with a case study of a beer fermenter to verify the effectiveness of the algorithm for modular classification of light industrial equipment.

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