Multi-objective optimization of incremental sheet metal forming

• Main Authors: Zakaria, Faiz, Hrairi, Meftah, Daoud, Jamal Ibrahim
• Format: Conference or Workshop Item
• Language: English; English
• Published: 2018
• Subjects: QA276 Mathematical Statistics; TJ Mechanical engineering and machinery
• Online Access: http://irep.iium.edu.my/68018/1/ICMAAE2018-261.pdf; http://irep.iium.edu.my/68018/2/ICMAAE18_ProgrammeBook.pdf; http://irep.iium.edu.my/68018/; http://iium.edu.my/icmaae/2018/

The aim of this research project is to optimize incremental sheet metal forming process by analyzing the significant parameters affecting the result of the optimization. The features of the incremental sheet forming (ISF) process allow it to meet a wide array of customer preferences without rely on dies and punches. In this paper, most significant parameter was systematically studied to achieve the aim of optimization. Taguchi method was used separately for single optimization of surface roughness, wall angles, spring back and wall thickness. By help of analysis of variance (ANOVA) the most significant parameter can be rank and the optimal set of parameters can be used according to the greatest effect on surface roughness and wall thickness. The confirmation test also showed that the response tables and graphs from Taguchi analysis and ANOVA constitute effective and efficient methods for determining each design parameter’s optimal level to produce the minimum value of the surface roughness and wall thickness. The implementation of Taguchi-based Grey optimization will be used to derive the optimal process parameters combination of wall angles, surface roughness and spring back. The output of the study will provide the optimal geometrical parameters for all objective functions, wall angles, surface roughness and spring back.