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International Journal of Automotive Technology > Volume 21(5); 2020 > Article
International Journal of Automotive Technology 2020;21(5): 1097-1106.
doi: https://doi.org/10.1007/s12239-020-0103-y
Risky Ayu Febriani, Hong Seok Park, Saurabh Kumar, Chang Myung Lee
University of Ulsan
PDF Links Corresponding Author.  Hong Seok Park , Email. phosk@ulsan.ac.kr
Optimizing the design of the preform shapes used in warm forging processes is important for improving quality and reducing cost. The main objective of this study was to optimize the design of a preform shape for a bevel gear to obtain a good product and to improve the efficiency of the warm forging process. Quality parameters included in the fitness function were form-filling, preform volume, and complexity. First, basic principles pertaining to the cross sections, thickness, and concave radius of a bevel gear preform were applied in conjunction with certain theoretical expressions and empirical methods to produce an initial preform shape and initial geometry. Subsequently, mathematical evaluation models of the fitness function were generated to optimize the preform shape. Finally, a genetic algorithm was applied to solve the multi-objective optimization problem, and the best solution was determined considering the accuracy of the results, within the close proximity set generated by the multi-objective genetic algorithm optimization. The optimal preform shape was decreased in weight by approximately 8 % and its flash dimensions were decreased by about 5 % compared to the initial preform shape. This research is expected to improve the efficiency of fabricating bevel gears by means of warm forging processes.
Key Words: Preform shape, Bevel gear, Warm forging process, Genetic algorithm
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