The Simple Genetic Algorithm Approach for Optimization of Nesting of Sheet Metal Parts in Blanking Operation

2015 ◽  
Vol 14 (01) ◽  
pp. 41-53 ◽  
Author(s):  
K. Ramesh ◽  
N. Baskar
Keyword(s):  
Genetic Algorithm ◽  
Sheet Metal ◽  
Optimization Problem ◽  
Cutting Stock ◽  
Metal Parts ◽  
Sheet Metal Parts ◽  
Chromosome Representation ◽  
Genetic Algorithm Approach ◽  
Hard Problems ◽  
Maximum Utilization

The two-dimensional (2D) cutting stock is a common problem arising in the sheet metal industries, lock industries, textile industries, etc. Here, the problem is to reduce the wastage in order to increase the profit. This problem is also called as the general 2D problem or NP hard problems. The choice of chromosome representation in genetic algorithm (GA) depends on the variables of the optimization problem being solved. The main objectives of the work are the maximum utilization of part in the sheet and also minimizing the wastage.

A Genetic Algorithm Approach to Weld Pattern Optimization in Sheet Metal Assembly

2003 ◽  
Author(s):  
Gene Y. Liao
Keyword(s):  
Genetic Algorithm ◽  
Sheet Metal ◽  
Optimization Method ◽  
Structural Deformation ◽  
Assembly Process ◽  
Sheet Metal Parts ◽  
Final Assembly ◽  
Welding Operation ◽  
Genetic Algorithm Approach ◽  
Sheet Metal Assembly

In sheet metal assembly process, welding operation joins two or more sheet metal parts together. Since sheet metals are subject to dimensional variation resulted from manufacturing randomness, gap may be generated at each weld pair prior to welding. These gaps are forced to close during a welding operation and accordingly undesirable structural deformation results. Optimizing the welding pattern (the number and locations of weld pairs) of an assembly process was proven to significantly improve the quality of final assembly. This paper presents a Genetic Algorithm (GA)-based optimization method to automatically search for the optimal weld pattern so that the assembly deformation is minimized. Application result of a real industrial part demonstrated that the proposed algorithm effectively achieve the objective.

Fixture Layout Optimization Based on Social Radiation Algorithm

2014 ◽  
Author(s):  
Yanfeng Xing ◽  
Jun Ni ◽  
Shuhuai Lan
Keyword(s):  
Genetic Algorithm ◽  
Sheet Metal ◽  
Layout Design ◽  
Metal Parts ◽  
Sheet Metal Parts ◽  
Fixture Layout ◽  
The Social ◽  
Long Time ◽  
Fixture Layout Optimization

Sheet metal parts easily deformed during clamping and welding, and fixture layout design is very difficult because it takes a long time to calculate and read displacements of all nodes. This paper proposes a method to optimize fixture scheme by a social radiation algorithm (SRA). Firstly unfeasible candidate nodes are eliminated by some rules according to manufacturing experiences. Afterwards some feasible zones are optimized by SRA. Finally the best fixture layout is obtained through selecting the feasible nodes among the optimal zones. A case study of guiding gutter is used to illustrate the proposed method, and the results show that the social radiation algorithm has better efficiency and higher accuracy than the genetic algorithm.

Experimental and Numerical Analysis of Blanking for Thin Sheet Metal Parts

2001 ◽  
Vol 4 (3-4) ◽  
pp. 319-333
Author(s):  
Vincent Lemiale ◽  
Philippe Picart ◽  
Sébastien Meunier
Keyword(s):  
Numerical Analysis ◽  
Sheet Metal ◽  
Thin Sheet ◽  
Metal Parts ◽  
Sheet Metal Parts ◽  
Thin Sheet Metal
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