运用改进模糊C均值算法的复杂产品功构单元模块划分方法

为了解决目前已有聚类方法在复杂产品功构单元模块划分过程中存在的问题,提出了一种基于改进模糊C均值算法(D-FCM)的产品功构单元模块划分方法。该方法运用距离矩阵生成样本分层聚类树,结合F统计量方法确定模糊C均值算法最佳聚类数,在此基础上,应用模糊C均值算法进行聚类分析,获得聚类结果。最后,结合实际项目给出该聚类方法在机床模块划分过程中的典型应用,对该方法进行实例验证。以此为基础,开发出机床模块划分系统平台。系统实现及设计结果表明了所提出方法的有效性,为面向配置设计的机床模块划分提供了另一种有效的模块划分方法。

Modular division method of complex product function-and-structure unit based on the improved fuzzy C-means clustering algorithm

To solve the problem in modular division of complex product function-and-structure,an improved fuzzy C-means(D-FCM)clustering algorithm for product function-and-structure was proposed.In this algorithm,distance matrix and F statistic were used to confirm the best cluster date,on this basis,fuzzy C-means clustering algorithm was used to get the result of clustering.Finally,a typical machine tool instance was given with the method of the modified fuzzy C-means clustering algorithm to test the method.At the same time,a system for machine tool granularity division was developed based on this method,which shows the validity and promise of the method mentioned above.Therefore it provides another numerical analysis method of machine tool for configuration design.