چکیده مقاله
The present study focuses on the multi objective modeling and optimization of Surface Roughness SR , Tool Wear Rate TWR and Material Removal Rate MRR in Electrical Discharge Machining EDM of 40CrMnMoS86 hot worked steel parts The proposed approach is based on Grey Relational Analysis GRA and Genetic Algorithm GA The experimental data are gathered using Taguchi L36 design matrix Experimental tests are conducted under varying peak current I , voltage V , pulse on time Ton , pulse off time Toff and duty factor Grey relational analysis and regression modeling are then employed to establish the relations between machining parameters and process output responses To find optimal parameter settings, the developed multi objective model is optimized using Genetic Algorithm A confirmation test is also performed to verify the effectiveness of the optimization procedure in determining the optimum levels of machining parameters The results show that the combination of Taguchi technique, Grey relational analysis and Genetic Algorithm is quite efficient in modeling and optimization EDM process parameters
کلیدواژهها
نویسندگان
F. Kolahan
Department of Mechanical Engineering, College of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
M. Azadi Moghaddam
Department of Mechanical Engineering, College of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
R. Golmezerji
Department of Mechanical Engineering, College of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
شیوه ارجاع
Kolahan, F. and Azadi Moghaddam, M. and Golmezerji, R.,1390,Multi Objective Optimization of EDM Parameters for 40CrMnMoS86 Hot Worked Steel Using Grey Relational Analysis and Genetic Algorithm,12th Iranian Conference on Manufacturing Engineering (ICME 2010),Tehran
ارائهشده در
مجموعه مقالات دوازدهمین کنفرانس ملی مهندسی ساخت و تولید ایران6 دی 1390 · تهران