Abstract:
Design parameters not only affect the performance of a product, but also affect the feasibility, effectiveness and efficiency of manufacturing. Processing parameters, in turn, affect the performance of the part. For this reason, a design optimization study focusing on just design parameters may result in a design difficulty to manufacture or a processing optimization study considering just processing parameters may result in a product with inferior quality. Therefore, effective optimization of a product requires a joint consideration of all these variables. In this study, a concurrent design optimization methodology is proposed to minimize the cost of a cold forging process using both product design and process design parameters as optimization variables. An objective function is defined combining material cost, manufacturing cost, and post manufacturing (shearing) cost of the product. The part to be optimized is a simply supported I-beam under a centric load. Because of large number optimization variables, a two-level approach is adopted. In the first level, only design variables defining the geometry of the part are considered to optimize its shape. In the second one, all of the process variables like preform dimensions and fillet radii and some of the design variables are considered. Various constraints are imposed related to the performance of the product in working condition and the effectiveness of manufacturing. Nelder-Mead, a robust zero - order search algorithm, is used as the search algorithm and analyses are carried out using commercial finite element software, ANSYS. After repeated runs, results are obtained that show considerable improvement in the cost.
