PREDICTION AND ENHANCEMENT OF THICKNESS REDUCTION IN MULTI-POINT FORMING PROCESS USING ANOVA ALGORITHM

Abstract

Multipoint forming is an engineering concept which means that the working surface of the dieand/or punch is made up of hemispherical ends of individual active elements (called pins), whereeach pin can be independently, vertically displaced using a geometrically reconfigurable die,precious production time is saved because several different products can be made withoutchanging tools. The aim of this work is to present the effect of many parameters (blank Holdertypes, rubber thickness and forming speed) on the reduction of thickness for brass with 0.71 mmthickness. This research is concentrate on the development of predictive models to estimate theminimum deviation in thickness using analysis of variance (ANOVA), minimum thicknessdeviation has been modeled. In the development of this predictive model, blank holder, rubberthickness and forming speed have been considered as model parameters. Arithmetic theminimum thickness deviation used as response parameter to assess the thickness reduction ofMultipoint forming parts. The data required has been generated, compared and evaluated to theproposed models that obtained from experiments. Taguchi algorithm is used to predict theeffect of forming parameters on thickness reduction in forming process of Brass (65-35) basedon orthogonal array of L9. The analysis of variance was used to find the best factors that effecton the thickness deviation, The result of this research is the contribution of blank holder types,rubber thickness and forming speed with respect to minimum thickness deviation is (69.195,18.1 and 12.733) % respectively.