Modeling manufacturing resources based on manufacturability features

Manufacturability evaluation is an effective way to shorten the development period, optimize manufacturing processes, and reduce product costs. The manufacturability of a product depends on the processing ability of specific manufacturing resources. The development of a manufacturing resources model serves as the foundation for manufacturability evaluation. To better utilize the information on manufacturing resources, this study adopted a hybrid approach by integrating the fuzzy c-means clustering algorithm and the genetic algorithm to group manufacturing resources based on manufacturing and geometric features. The information model of manufacturing resources was built by using the object-oriented method. Subsequently, the framework to evaluate manufacturing capability based on manufacturing resources was defined. Further, an application sample was exploited and its results were analyzed. The results of the subgroup showed that the hybrid algorithm was reliable and valid and helped improve the overall performance of the company chosen for this study. The proposed approach enhanced feasibility in decision-making and facilitated the management to make more informed decisions.