DEVELOPMENT OF PROCESS OPTIMIZATION FOR AN INTELLIGENT KNOWLEDGE-BASED SYSTEM FOR SPUR GEAR PRECISION FORGING DIE DESIGN

摘要

Forging sequence design is mainly carried out using empirical rules for the design of the intermediate die shapes, in addition to many trail-and-error runs resulting in prolonged development times and higher costs. An integrated optimal design of preform shapes and process conditions approach to minimize the energy required is essential. The research presented in this article aims at developing an optimization algorithm to determine the optimum intermediate die shape-designs that minimize the total energy required during the forging process sequence. It is based on the results obtained in the previous research with focus on knowledge base and database representation to design precision forging solid gears and provide detailed process specification. A three-step algorithm, which addresses gear construction design, manufacturability analysis of gear construction and die-design optimization, is used to generate the parametric gear model and automatically extract design information for manufacturing process planning based on the feature-based parametric design system. Utilization of the shape optimization method for preform stages avoids costly production problems. The optimized approach provides accurate description of all stages involved in the forging process. Forging load and energy required, along with metal flow and detailed geometry specification of die forms for every forging stage are obtained. The forging energy requirements based on this approach are as much as 25% lower than those arrived from die designs based on actual tooth profile geometry.