Abstract
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.
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References
Bariani, P., Benuzzi, E., Knight, W.A.: Computer aided design of multi-stage cold forging process: Load peaks and strain distribution evaluation. Annals of the CIRP 36(1), 145–148 (1987)
Sevenler, K., Raghupathi, P.S., Altan, T.: Forming-sequence design for multistage cold forging. J. of Mechanical Working Technology 14, 121–135 (1987)
Lange, K., Guohui, D.: A formal approach to designing forming sequences for cold forging. Trans. of the NAMRI/SME, 17–22 (1989)
Mahmood, T., Lengyel, B., Husband, T.M.: Expert system for process planning in the cold forging of steel. Expert Planning Systems 322, 141–146 (1990)
Takata, O., Nakanishi, K., Yamazaki, T.: Forming-sequence design expert system for multistage cold forging: Forest-d. In: Proc. of Pacific Rim International Conference on Artificial Intelligence 1990, pp. 101–113 (1990)
Yang, G., Osakada, K.: A review of expert system for process planning of cold forging. Manufacturing Review 6(2), 101–113 (1993)
Kim, H.S., Im, Y.T.: An expert system for cold forging process design based on a depth-first search. J. of Materials Processing Technology 95, 262–274 (1999)
Takata, O., Mure, Y., Nakashima, Y., Ogawa, M., Umeda, M., Nagasawa, I.: A knowledge-based system for process planning in cold forging using the adjustment of stepped cylinder method. In: Umeda, M., Wolf, A., Bartenstein, O., Geske, U., Seipel, D., Takata, O. (eds.) INAP 2005. LNCS, vol. 4369, pp. 161–174. Springer, Heidelberg (2006)
Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach, 2nd edn. Prentice-Hall, Englewood Cliffs (2002)
Verson, M.D.: Impact Machining. Verson Allsteel Press Company (1969)
JSTP. Forging Technology (in Japanese) Corona Publishing Co. (1995)
Umeda, M., Nagasawa, I., Higuchi, T.: The elements of programming style in design calculations. In: Proceedings of the Ninth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, pp. 77–86 (June 1996)
Katamine, K., Umeda, M., Nagasawa, I., Hashimoto, M.: Integrated development environment for knowledge-based systems and its practical application. IEICE Transactions on Information and Systems E87-D(4), 877–885 (2004)
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Takata, O., Mure, Y., Nakashima, Y., Ogawa, M., Umeda, M., Nagasawa, I. (2006). A Knowledge-Based System for Process Planning in Cold Forging Using the Adjustment of Stepped Cylinder Method. In: Umeda, M., Wolf, A., Bartenstein, O., Geske, U., Seipel, D., Takata, O. (eds) Declarative Programming for Knowledge Management. INAP 2005. Lecture Notes in Computer Science(), vol 4369. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11963578_13
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DOI: https://doi.org/10.1007/11963578_13
Publisher Name: Springer, Berlin, Heidelberg
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