Multi-component genetic algorithm for generating best bending sequence and tool selection in sheet metal parts

2002 ◽  
Author(s):  
C.M. Thanapandi ◽  
A. Walairacht ◽  
S. Ohara
Keyword(s):  
Genetic Algorithm ◽  
Sheet Metal ◽  
Tool Selection ◽  
Metal Parts ◽  
Sheet Metal Parts ◽  
Bending Sequence

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.

The Integration of CAPP and Production Planning for Bent Sheet Metal Parts

2005 ◽  
Vol 6-8 ◽  
pp. 263-270 ◽  
Author(s):  
Dirk Cattrysse ◽  
P. Collin ◽  
Joost R. Duflou ◽  
T.H.M. Nguyen ◽  
Dirk Van Oudheusden
Keyword(s):  
Production Planning ◽  
Sheet Metal ◽  
Process Planning ◽  
Planning System ◽  
Tool Selection ◽  
Computer Aided Process Planning ◽  
Metal Parts ◽  
Air Bending ◽  
Sheet Metal Parts ◽  
Selection For

Both the topics of Computer Aided Process Planning and Production Planning in the context of sheet metal air bending have been presented as standalone topics previously. This paper will focus on the interaction between both modules. Choices made by the CAPP-module seem to influence the possible gains that can be obtained in production planning and vice versa. The used procedures for both the CAPP module, including process planning and tool selection for air bending, and the Production Planning module, modelling the production planning as a Travelling Purchaser Problem, are described. The different areas of interaction between both modules are also specified. Results demonstrate that the interaction between both modules has a significant impact and should be taken into account in an integrated process and production planning system.

Automatic Tool Selection for NC Turret Operation in Sheet Metal Stamping

1994 ◽  
Vol 116 (2) ◽  
pp. 239-246 ◽  
Author(s):  
Kyung Ho Cho ◽  
Kunwoo Lee
Keyword(s):  
Sheet Metal ◽  
Shape Index ◽  
Production Performance ◽  
Tool Selection ◽  
Index Set ◽  
Metal Parts ◽  
Sheet Metal Parts ◽  
Metal Fabrication ◽  
Metal Stamping ◽  
Automatic Tool

In sheet metal fabrication using an NCT (numerically controlled turret punch press) machine, automatic tool selection is a major problem to be solved to improve its production performance. However, this operation has been done either manually or semi-automatically by human experts. In this paper, we have introduced the shape-index-set to handle the shape of sheet metal parts and developed an algorithm through which one can find the successive matching curves between two curve lists, one from the punching tool and the other from the boundaries of the sheet metal part. The algorithm is used to select the tools automatically to punch out the boundaries of sheet metal parts. Several experiments are presented to prove the successful tool selection.

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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