Application of Response Surface Analysis and Genetic Algorithm for the Optimization of Single Point Incremental Forming Process

Abstract

Single point incremental forming (SPIF) is a modern method of forming sheet metal, where parts can be formed without the use of dedicated dies. The ability of SPIF to form a part is based on various forming parameters. Previous work was not accomplished with the help of design of experiments (DOE), thus reducing the number of parameters varied at any time. This paper presents a Box-Behnken experimental design, which develops the numerical plan, formalizes the forming parameters critical in SPIF and analyse data. The most critical factors affecting SPIF were found to be wall inclination angle, incremental step size, material thickness and tool size. The main effects of these parameters on the quality of the formed parts were studied in detail. Actually this work aims to “optimize the thinning rate and the maximum force by considering the tool diameter and the vertical pitch as unknown parameters for two different wall angles and thicknesses”. To this purpose, an optimization procedure based on the use of response surface methodology (RSM) and genetic algorithms (GA) have been proposed for application to find the optimum solutions. Finally, it demonstrated that the developed methods can solve high non-linear problems successfully. Associated plots are shown to be very efficient for a quick localization of the region of the search space containing the global optimum values of the SPIF parameters.

Experimental Investigation of Forming Forces in Frictional Stir Incremental Forming of Aluminum Alloy AA6061-T6

“…It was found that increasing the values of these parameters led to increasing forming forces. The effect of the same process parameters was studied by Bahloul et al [33] to evaluate their outcomes on two important responses: sheet-thinning rates and maximum process forces. Based on the obtained results, the sheet thickness and the wall angle have the most significant effect on the two afore-mentioned responses.…”

Parameters for the FEA simulations of single point incremental forming

“…Complicated shell theories are required to consider thickness and to make up for the developmental assumptions. In addition, the two-dimensional material law and the assumptions employed in the shells lead to inaccuracies in the description of through thickness variables (Arfa, Bahloul, and Belhadjsalah, 2014;Bahloul et al, 2013;Computational Finite Element Methods in Nanotechnology, 2012;Liu, Daniel, Li, Liu, & Meehan, 2014;Petek & Kuzman, 2010).…”

“…Shear locking and membrane locking can be avoided by using reduced integration (Arfa et al, 2014;Bahloul et al, 2013;Liu et al, 2014;Malhotra et al, 2012;Mirnia, Mollaei Dariani, Vanhove, & Duflou, 2013;Petek & Kuzman, 2010). It is the easiest way to avoid locking.…”

“…FEA were successfully implemented to analyze stress and strain during the sheet deformation (Shanmuganatan & Senthil Kumar, 2012). Various studies have investigated the parameters like wall angle, tool diameter, incremental step size and material thickness critical in SPIF by the aid of numerical models (Arfa, Bahloul, & BelHadjSalah, 2012;Bahloul, Arfa, & Belhadjsalah, 2013;Shanmuganatan & Senthil Kumar, 2013). FEA are now widely employed for better understanding of the defects occurring in the formed component.…”

Application of artificial cognitive system to incremental sheet forming machine tools for part precision improvement

“…Many Authors focused on the tool path correction using strategies based on iterative algorithms [17][18][19], transfer function [20], part features [21] or neural networks [22,23]. A novel approach is proposed in [20] where the transfer function concept was introduced to correct the toolpath aiming at the precision part improvement.…”