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A CAD-based method for multi-objectives optimization of mechanical products

Alessio Vita, Marco Mandolini, Vincenzo Castorani, Michele Germani (Università Politecnica delle Marche)

CHALLENGE - This paper presents an approach for multi-objective optimization of mechanical products by associating the Response Surface Methodology (RSM) and the Design of Experiments (DoE) technique with CAD/CAE/DfC integration. The proposed methodology integrates three different levels of analysis: optimization problem formulation, virtual prototyping and design optimization. The aim is to develop a methodology to redesign a modular structure in armchairs reducing manufacturing time and cost.

SOLUTION -  This method has been used to redesign a modular structure used for the rotation of the armchairs under the floor level.  An Italian leading company in the production of sofas and armchairs actively participated at the test of the proposed method. The CAD system Catia is able to interconnect both the CAE software and the DfC software for the specific analysis. In this paper, the Multi-Objective Genetic Algorithm (MOGA) has been used to solve the multiobjective optimization. 







BENEFITS -  Two design teams carried out the same optimization analysis of the modular structure, the first (two engineers) using the presented methodology, and the second (three engineers) following the traditional method. The aim was to test the functionality of the automated process and to compare the results achieved. The team that used the present approach was able to identify the optimal solution, saving 13% of manufacturing cost and 17% of manufacturing time, compared to the solution achieved by the other group. The redesign of the whole modular structure led to a significant reduction of the component number, from 300 to less than 200 (-30%), manufacturing costs by 40% and the total time of production by 35%.