Application of novel heuristic and genetic methods for efficient sheet metal cutting processes

Abstract

Manufacturing of sheet metal components involves three major processes cutting, bending and assembly. Preparation of an optimum layout that suits for any of the cutting method employed such as Laser, Plasma, Abrasive Water Jet (AWJ) cutting or Profile Blanking, seems to be important prior to the cutting process. In this research, a novel two-dimensional nesting strategy suitable for sheet metal cutting process is presented. The proposed nesting approach is a combination of heuristic and genetic algorithms in order to generate an effective nested pattern, in such a way that, it minimizes the sheet material wastage and also the cutting tool path distance, while arranging a set of rectangular parts in a rectangular sheet. With the proposed Bottom-Left heuristic method, at first, the parts are considered in a specific sequence and orientation, and each part is translated to the most feasible newlinebottom left position on the previously placed parts and then adjusted to form the common cutting edges with the adjacent parts. Further, the heuristic algorithm ensures the formation of clusters, in which a group of parts share the cutting edges, for their effective handling. Finally the optimal and an effective nested pattern is generated by the genetic evaluation process which reproduces several sets of nested patterns, before converging to optimality. The effectiveness of the proposed work, in terms of utilization of the sheet material, is demonstrated by comparing the results obtained from the literature. Furthermore the uniqueness of the present approach in enhancing the efficiency of the nested pattern and minimizing the tool path distance with common cutting edge concept is illustrated. newline newline