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The design tasks of cold forged products are very important because they have a great influence on the quality of the final products and the life of the forging dies. However, the design expertise required for the design tends to get scattered and lost, and therefore there is a need for a framework that will enable the accumulation, utilization and evolution of this expertise. The authors have been developing a knowledge-based system to support process planning and the design of dies and die-sets for cold forged products. The knowledge base contains design knowledge on cold forging, which is systematized based on the formal definition of die design problems and on methods with high generality for resolving these problems. These features facilitate the improvement of product quality using an exhaustive search of process plans and die structures, and the improvement of design performance by automating the design work. They also make it easier to pass on and evolve expertise by allowing design experts to self audit and maintain their own knowledge base. The proposed system has been applied to several cold forged products. Experiments show that it can generate multiple forging process plans, dies, and die-sets based on the design knowledge, and that feasible solutions can be obtained within a practical time span.

We report on a knowledge-based system for process planning in cold forging. In this system, a forged product is represented as an aggregation of forming patterns that consists of cylindrical pillar parts. The basic principle of the inference method we propose is to adjust the diameters of neighboring stepped cylinders so that they are identical. Plural deformable process plans are generated using expert knowledge about working limits, die configurations, and metal flow. This system can eliminate ineffective plans by using the knowledge of how to combine plural forming patterns into a single process. Moreover, it can evaluate process plans and interactively select the optimal one by considering production costs, the forming load, the effective strain in the product, the equipment, and other factors. We applied this system to actual forged products. As a result, this system is widely applicable to various shapes and types of equipment and can improve both maintenance and operation.

We propose a knowledge-based system for process planning in cold forging. In our study, we had developed FORTEK-L (FORging Technology of process planning using Expert Knowledge for Layout), which is widely applicable to various shapes and types of equipment. In the next step, we have developed a knowledge-based die configuration design system, FORTEK-D (Die configuration design), which can generate suitable die configurations from layouts obtained from FORTEK-L. In the development of FORTEK-D, we have analyzed and reproduced the expert engineer’s thinking process during die configuration design. Moreover, we have formulated the data representation, inference method, and knowledge-base for use with this system. In accordance with the formulation, we have developed a prototype system. We applied FORTEK-D to actual forged products and obtained appropriate results. The knowledge using the basic principle is widely applicable to various shapes and on a variety of equipment. Therefore, the abilities to maintain and operate the system have been improved.