Nesting of two-dimensional irregular parts: an integrated approach

The present paper reports an intelligent computer-aided nesting (CAN) system for optimal nesting of two-dimensional parts, especially parts with complicated shapes, with the objective of effectively improving the utilization ratio of sheet materials. This paper also systemically reviews the nesting algorithms that were developed to perform various nesting tasks, and attacks the irregular part nesting problem by efficiently integrating and improving the performance of nesting algorithms such as the rectangular enclosure method, bottom-left nesting algorithms, heuristic algorithms and genetic algorithms. The CAN system has also been developed as a nesting algorithm test platform for researching and developing new nesting algorithms. Through this test platform, the limitations of existing nesting algorithms are investigated and problems such as nesting parts in spaces within a single part or between parts are also studied. Efforts have been devoted to improving the nesting efficiency of the existing algorithms and developing new nesting algorithms. Case studies are carried out in a sheet metal cutting company. The results show that the intelligent CAN system can effectively nest both regular and irregular parts, and greatly improve the utilization ratio of raw sheet material.