TY - JOUR
T1 - Multi-objective optimization of WEDM of aluminum hybrid composites using AHP and genetic algorithm
AU - Kumar, Amresh
AU - Grover, Neelkanth
AU - Manna, Alakesh
AU - Kumar, Raman
AU - Chohan, Jasgurpreet Singh
AU - Singh, Sandeep
AU - Singh, Sunpreet
AU - Pruncu, Catalin Iulian
PY - 2021/7/7
Y1 - 2021/7/7
N2 - Aluminum hybrid composites have the potential to satisfy emerging demands of lightweight materials with enhanced mechanical properties and lower manufacturing costs. There is an inclusion of reinforcing materials with variable concentrations for the preparation of hybrid metal matrix composites to attain customized properties. Hence, it is obligatory to investigate the impact of different machining conditions for the selection of optimum parameter settings for aluminum-based hybrid metal matrix composite material. The present study aims to identify the optimum machining parameters during wire electrical discharge machining of samples prepared with graphite, ferrous oxide, and silicon carbide. In the present research work, five different process parameters and three response parameters such as material removal rate, surface roughness, and spark Gap are considered for process optimization. Energy-dispersive spectroscopy and scanning electron microscopy analysis reported the manifestation of the recast layer. Analytical hierarchy process and genetic algorithm have been successfully implemented to identify the best machining conditions for hybrid composites.
AB - Aluminum hybrid composites have the potential to satisfy emerging demands of lightweight materials with enhanced mechanical properties and lower manufacturing costs. There is an inclusion of reinforcing materials with variable concentrations for the preparation of hybrid metal matrix composites to attain customized properties. Hence, it is obligatory to investigate the impact of different machining conditions for the selection of optimum parameter settings for aluminum-based hybrid metal matrix composite material. The present study aims to identify the optimum machining parameters during wire electrical discharge machining of samples prepared with graphite, ferrous oxide, and silicon carbide. In the present research work, five different process parameters and three response parameters such as material removal rate, surface roughness, and spark Gap are considered for process optimization. Energy-dispersive spectroscopy and scanning electron microscopy analysis reported the manifestation of the recast layer. Analytical hierarchy process and genetic algorithm have been successfully implemented to identify the best machining conditions for hybrid composites.
KW - analytical hierarchy process
KW - genetic algorithm
KW - metal matrix composites
KW - optimization
KW - wire electrical discharge machining
UR - http://www.scopus.com/inward/record.url?scp=85109406326&partnerID=8YFLogxK
U2 - 10.1007/s13369-021-05865-4
DO - 10.1007/s13369-021-05865-4
M3 - Article
AN - SCOPUS:85109406326
SN - 2193-567X
JO - Arabian Journal for Science and Engineering
JF - Arabian Journal for Science and Engineering
ER -