Automatic generation of optimal process plans for machined parts from 3D solid models

Abstract

The application of computers to the product design and manufacturing process brought changes in the traditionally separate disciplines of design and manufacturing. The usage of computer-aided design (CAD) covers a variety of applications such as stress analysis as well as designing, and computer-aided manufacturing (CAM) replaced the need of the coordinated interactions of skilled machinist. Though such advancements have been made in CAD/CAM, however, integration of them has not been fully achieved. Automated process planning has been considered as a key to the CAD/CAM integration. In this dissertation, a method to automatically generate the optimal process plan for a machined part is presented. This method first recognizes machining features from the solid model of the part by recursive volume decomposition (RVD). An RVD method has been developed in this research to solve the computational complexity of the earlier volume decomposition method. This RVD method quickly decomposes the delta volume into volumes called maximal volumes (MVs) and then transforms the MVs into machining features. Next, alternative process plans are generated by sequencing the features in different orders. In doing so, various machining rules are used so that only promising plans can be generated. Finally, the machining time for each plan is estimated and the plan that requires the least period of machining time is selected as the optimal plan. The results of case studies are presented to attest the usefulness of the proposed method. Overall, the performance of the proposed method demonstrates its potential for integration of CAD and CAM.