Ship part nesting by pattern recognition and group arrangement

The automatic nesting for a computer-aided manufacturing (CAM) system in shipbuilding industry requires more constraints than in other fields such as automobile, clothes and shoes. The nesting software has more influence on the productivity of shipbuilding industry, being equipped with such functions as automated operation, user-friendly interface, generation of stable cutting data and draft, and synchronization with enterprise resource planning (ERP). Many algorithms have been developed to increase the utilization rates of sheet metal plates and decrease scrap ratios. However, the minimization of the computational time and scrap ratio has not been fulfilled yet because of inherent constraints in nesting processes. To increase the efficiency of the part nesting in shipbuilding industry, this study presents pattern recognition and group arrangement method. The form features of ship parts are recognized and classified into pre-defined patterns by using the ray projection method. Then, the parts are grouped based on grouping rules. The proposed method has been validated with actual ship parts.

[1]  Wen-Chen Lee,et al.  A heuristic for nesting problems of irregular shapes , 2008, Comput. Aided Des..

[2]  A. Ramesh Babu,et al.  A generic approach for nesting of 2-D parts in 2-D sheets using genetic and heuristic algorithms , 2001, Comput. Aided Des..

[3]  S. Jakobs,et al.  European Journal Ofoperational Research on Genetic Algorithms for the Packing of Polygons , 2022 .

[4]  Jiawei Ye,et al.  A Solution of Irregular Parts Nesting Problem Based on Immune Genetic Algorithm , 2008, 2008 International Symposium on Computational Intelligence and Design.

[5]  Suck-Joo Na,et al.  Two-Stage Approach for Nesting in Two-Dimensional Cutting Problems Using Neural Network and Simulated Annealing , 1996 .

[6]  Chia-Cheng Liu,et al.  Fast Nesting of 2-D Sheet Parts With Arbitrary Shapes Using a Greedy Method and Semi-Discrete Representations , 2007, IEEE Transactions on Automation Science and Engineering.

[7]  A. Ramesh Babu,et al.  Effective nesting of rectangular parts in multiple rectangular sheets using genetic and heuristic algorithms , 1999 .

[8]  Kamineni Pitcheswara Rao,et al.  Quick and precise clustering of arbitrarily shaped flat patterns based on stringy effect , 1997 .

[9]  Henry J. Lamousin,et al.  Nesting of two-dimensional irregular parts using a shape reasoning heuristic , 1997, Comput. Aided Des..

[10]  Masahiro Toyosada,et al.  Automatic two-dimensional layout using a rule-based heuristic algorithm , 2003 .

[11]  Francis E. H. Tay,et al.  Pattern nesting on irregular-shaped stock using Genetic Algorithms , 2002 .