TY - JOUR
T1 - Multi-objective optimization of wire electro discharge machining (WEDM) process parameters using grey-fuzzy approach
AU - Das, Partha Protim
AU - Diyaley, Sunny
AU - Chakraborty, Shankar
AU - Ghadai, Ranjan Kumar
N1 - Publisher Copyright:
© 2018 Budapest University of Technology and Economics. All Rights Reserved.
PY - 2019
Y1 - 2019
N2 - Wire electro discharge machining (WEDM) is a versatile non-traditional machining process that is extensively in use to machine the components having intricate profiles and shapes. In WEDM, it is very important to select the optimal process parameters so as to enhance the machine performance. This paper emphasizes the selection of optimal parametric combination of WEDM process while machining on EN31 steel, using grey-fuzzy logic technique. Process parameters such as servo voltage, wire tension, pulse-on-time and pulse-off-time were considered while taking into account several multi-responses such as material removal rate (MRR) and surface roughness (SR). It was found that pulse-on-time of 115 µs, pulse-off-time of 35 µs, servo voltage of 40 V and wire tension of 5 kgf results in a larger value of grey fuzzy reasoning grade (GFRG) which tends to maximize MRR and improve SR. Finally, analysis of variance (ANOVA) is applied to check the influence of each process parameters in the estimation of GFRG.
AB - Wire electro discharge machining (WEDM) is a versatile non-traditional machining process that is extensively in use to machine the components having intricate profiles and shapes. In WEDM, it is very important to select the optimal process parameters so as to enhance the machine performance. This paper emphasizes the selection of optimal parametric combination of WEDM process while machining on EN31 steel, using grey-fuzzy logic technique. Process parameters such as servo voltage, wire tension, pulse-on-time and pulse-off-time were considered while taking into account several multi-responses such as material removal rate (MRR) and surface roughness (SR). It was found that pulse-on-time of 115 µs, pulse-off-time of 35 µs, servo voltage of 40 V and wire tension of 5 kgf results in a larger value of grey fuzzy reasoning grade (GFRG) which tends to maximize MRR and improve SR. Finally, analysis of variance (ANOVA) is applied to check the influence of each process parameters in the estimation of GFRG.
UR - https://www.scopus.com/pages/publications/85059265882
UR - https://www.scopus.com/pages/publications/85059265882#tab=citedBy
U2 - 10.3311/PPme.12167
DO - 10.3311/PPme.12167
M3 - Article
AN - SCOPUS:85059265882
SN - 0324-6051
VL - 63
SP - 16
EP - 25
JO - Periodica Polytechnica Mechanical Engineering
JF - Periodica Polytechnica Mechanical Engineering
IS - 1
ER -