Volume 14, Issue 2 (5-2014)
Modares Mechanical Engineering 2014, 14(2): 167-174 |
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Mohammadi Najafabadi H, Ataee A A, Sharififar M. Numerical and Experimental Investigation of Incremental Sheet Metal Forming Parameters and Multi-objective Optimization Using Neural-genetic Algorithm. Modares Mechanical Engineering 2014; 14 (2) :167-174
URL: http://mme.modares.ac.ir/article-15-11937-en.html
URL: http://mme.modares.ac.ir/article-15-11937-en.html
Abstract: (5838 Views)
The Incremental Sheet Metal Forming (ISMF) process is a new and flexible method that is well suited for small batch production or prototyping. In this study, after the process simulation with ABAQUS software and verification of results through experimental tests, the effects of three parameters including friction coefficient, tool diameter and vertical step size on three objectives including vertical force, minimum thickness of deformed sheet and amount of spring-back are investigated. A neural-network model is developed based on simulation data and the effects of parameters are studied on each objective. Also multi-objective genetic algorithm is performed to get the Pareto front of optimum points.
Article Type: Research Article |
Subject:
Finite Elements Method|Metal Forming
Received: 2013/01/26 | Accepted: 2014/03/14 | Published: 2014/05/4
Received: 2013/01/26 | Accepted: 2014/03/14 | Published: 2014/05/4
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