基于模糊神经网络产品设计的可装配性评价

首先建立了基于模糊神经网络的可装配性评价模型，然后将产品的可装配性分为零件级可装配性和装配顺序级可装配性，并将影响零件可装配性的因素分为零件装配特征的对称性、零件易于装配的形状特征个数、零件易于识别和零件易于抓取的形状特征个数，将影响装配顺序可装配性的因素分为总的操作数．非装配操作、装配工具的更换次数、平行的装配任务的数量、基础件的重定向次数和装配方向，建立了评价指标体系。最后将评价模型应用于某产品可装配性的评价。

Assemblability evaluation of product design based on fuzzy neural network

Firstly the assemblability evaluation model based on fuzzy neural network was established, and then let the assemblability of product be divided into part leveled assemblability and assembly leveled assemblability, and let the factors affecting the parts assemblability be divided into the symmetry of assembly features, the amount of shape features prone to assembly of parts, the amount of shape features prone to identification and prone to grasp of parts. Let the assemblability factors that affecting the sequence of assembling be divided into total operation number, amount of non-assembly operation, number of replacement times of assembling tools, amount of parallel assembly tasks, times of foundational part's reorientation and direction of assembling, the evaluation index system was established. Finally, the evaluation model was applied to the assemblability evaluation of a certain product.