Preprocessor to Improve Performance of GA in Determining Bending Process for Sheet Metal Industry

Abstract

In manufacturing fabricated sheet metal parts, the required shape has to be bent from the flat 2-D layouts. In this bending process, the most complex and critical work is determining the bend sequence and assigning appropriate tools for each bend. Determining the bend sequence is itself a combinatorial problem and this when coupled with tool assignment leads to a huge combination and clearly shows an exhaustive approach is impossible and we propose Genetic Algorithm (GA), an adaptive algorithm to solve the problem. Information regarding the operator knowledge and operator desire are input to the system to generate efficient bending process. And moreover, in order to improve the performance of GA, a preprocessor is being implemented which searches combinable bends and thereby reduce search space and solve the problem in time-economic way.