LAPSE:2023.1351
Published Article

LAPSE:2023.1351
Novel Fuzzy Measurement Alternatives and Ranking according to the Compromise Solution-Based Green Machining Optimization
February 21, 2023
Abstract
Due to the increase in the impact of different manufacturing processes on the environment, green manufacturing processes are the prime focus of many current pieces of research. In the current article, a green machining process for stainless steel and SS304 and AISI1045 steel has been optimized using newly developed Fuzzy Measurement Alternatives and Ranking according to the COmpromise Solution (F-MARCOS) method in the form of two case studies. In the first case study, nose radius, cutting speed, depth of cut, and feed rate are selected as the process parameters whereas surface roughness, consumption of electrical energy, and power factor are the outputs. In the second case study width of cut, depth of cut, feed rate, and cutting speed were the process parameters and material removal rate (MRR), active energy consumption (ACE), and surface roughness (Ra) are the response variables. The MARCOS method ranks the alternatives based on the ideal and anti-ideal solutions for the different criteria. The inclusion of fuzzy logic adds worth to the model by using a linguistic scale to make the method more practical and flexible. Based on the detailed analysis, it ranked the best alternative in case study one which results in a power factor of 0.862, 26.68 kJ of electrical energy consumption, and surface roughness of 0.36 μm. In the second case study, the best alternative selected by this method gave an MRR of 2400 mm3/min and Ra of 2.29 μm and utilizes 53.988 kJ ACE.
Due to the increase in the impact of different manufacturing processes on the environment, green manufacturing processes are the prime focus of many current pieces of research. In the current article, a green machining process for stainless steel and SS304 and AISI1045 steel has been optimized using newly developed Fuzzy Measurement Alternatives and Ranking according to the COmpromise Solution (F-MARCOS) method in the form of two case studies. In the first case study, nose radius, cutting speed, depth of cut, and feed rate are selected as the process parameters whereas surface roughness, consumption of electrical energy, and power factor are the outputs. In the second case study width of cut, depth of cut, feed rate, and cutting speed were the process parameters and material removal rate (MRR), active energy consumption (ACE), and surface roughness (Ra) are the response variables. The MARCOS method ranks the alternatives based on the ideal and anti-ideal solutions for the different criteria. The inclusion of fuzzy logic adds worth to the model by using a linguistic scale to make the method more practical and flexible. Based on the detailed analysis, it ranked the best alternative in case study one which results in a power factor of 0.862, 26.68 kJ of electrical energy consumption, and surface roughness of 0.36 μm. In the second case study, the best alternative selected by this method gave an MRR of 2400 mm3/min and Ra of 2.29 μm and utilizes 53.988 kJ ACE.
Record ID
Keywords
decision making, fuzzy, machining, MCDM, process optimization
Subject
Suggested Citation
Shanmugasundar G, Mahanta TK, Čep R, Kalita K. Novel Fuzzy Measurement Alternatives and Ranking according to the Compromise Solution-Based Green Machining Optimization. (2023). LAPSE:2023.1351
Author Affiliations
Shanmugasundar G: Department of Mechanical Engineering, Sri Sairam Institute of Technology, Chennai 60044, India [ORCID]
Mahanta TK: School of Mechanical Engineering, Vellore Institute of Technology, Chennai 600127, India [ORCID]
Čep R: Department of Machining, Assembly and Engineering Metrology, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic [ORCID]
Kalita K: Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi 600062, India [ORCID]
Mahanta TK: School of Mechanical Engineering, Vellore Institute of Technology, Chennai 600127, India [ORCID]
Čep R: Department of Machining, Assembly and Engineering Metrology, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic [ORCID]
Kalita K: Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi 600062, India [ORCID]
Journal Name
Processes
Volume
10
Issue
12
First Page
2645
Year
2022
Publication Date
2022-12-08
ISSN
2227-9717
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Original Submission
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PII: pr10122645, Publication Type: Journal Article
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LAPSE:2023.1351
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https://doi.org/10.3390/pr10122645
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