Abstract
Objectives – Since parts and components are manufactured of different sizes and geometries, the fabrication of such parts of various size could be predicted the process parameters that affect the performance based on scaling laws and could be verified through experimentation. The purpose of this study is to determine optimum thinning process parameter settings of directionally rolled deep drawn copper cups at specified critical zones or regions for making miniaturized components and parts that results in better-quality products.Design/ Methodology/ Methodology - This study presents an integrated Analytic Hierarchy Process (AHP) with Combined Compromise Solution (CoCoSo) decision making algorithm to arrive a consolidation strategy with robust Taughi’s design of experiments, primarily to increase the accuracy of prediction of process parameters that affects the thinning rate of the deep-drawn cups. The weights of the alternatives is arrived with AHP and followed by CoCoSo method to determine the general multiplication factor to rank the alternatives by decision-making process. In this work, four control factors namely, number of stages of forming, clearance, punch nose radius, and coefficient of friction between x, were considered, with each at three levels, for determining the maximum thinning-rate at three different zones or locations namely, Cup-base, cup-nose-radius, and wall.Conclusions–This study described the real situation when forming performance on multi-stage deep-drawing with Uni-directional and bi-directional processed samples. The comparisons, such as sensitivity analysis approaches, methods developed to validate the proposed model.The virtual response were compared with the results of experiments on current multi stage deep drawing processes, good agreement being found.Originality/ Value –In this work a combined model using AHP and CoCoSo was attempted to improve the robustness of the products used for manufacturing miniaturized devices, which were not widely explored, and such integrated Multi-criteria decision-making (MCDM) methods was first proposed for engineering applications in the manufacturing field.
Determination of Process Parameters in Multi-Stage Hydro-Mechanical Deep Drawing by FE Simulation