Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective Optimization
This research investigates the multi-response of both material removal rate (MRR) and surface roughness (Ra) for the wire electrical discharge machining (WEDM) of two stainless steel alloys: AISI 304 and AISI 316. Experimental results are utilized to compare the machining responses obtained for AISI...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Journal of Manufacturing and Materials Processing |
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| Online Access: | https://www.mdpi.com/2504-4494/7/6/194 |
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| author | Mona A. Aboueleaz Noha Naeim Islam H. Abdelgaliel Mohamed F. Aly Ahmed Elkaseer |
| author_facet | Mona A. Aboueleaz Noha Naeim Islam H. Abdelgaliel Mohamed F. Aly Ahmed Elkaseer |
| author_sort | Mona A. Aboueleaz |
| collection | DOAJ |
| description | This research investigates the multi-response of both material removal rate (MRR) and surface roughness (Ra) for the wire electrical discharge machining (WEDM) of two stainless steel alloys: AISI 304 and AISI 316. Experimental results are utilized to compare the machining responses obtained for AISI 316 with those obtained for AISI 304, as previously reported in the literature. The experimental work is conducted through a full factorial experimental design of five running parameters with different levels: applied voltage, transverse feed, pulse-on/pulse-off times and current intensity. The machined workpieces are analyzed using an image processing technique in order to evaluate the size of cut slots to allow the calculation of the MRR. Followed by the characterization of the surface roughness along the side walls of the slots. Different mathematical regression techniques were developed to represent the multi-response of both materials using the MATLAB regression toolbox. It was found that WEDM process parameters have a fuzzy influence on the responses of both material models. This allowed for multi-objective optimization of the regression models using four different techniques: multi-objective genetic algorithm (MOGA), multi-objective pareto search algorithm (MOPSA), weighted value grey wolf optimizer (WVGWO) and osprey optimization algorithm (OOA). The optimization results reveal that the optimal WEDM parameters of each response are inconsistent to the others. Hence, the optimal results are considered a compromise between the best results of different responses. Noteworthily, the multi-objective pareto search algorithm outperformed the other candidates. Eventually, the optimal results of both materials share the high voltage, high transverse feed rate and low pulse-off time parameters; however, AISI 304 requires low pulse-on time and current intensity levels while AISI 316 optimal results entail higher pulse-on time and current levels. |
| first_indexed | 2024-03-08T20:37:37Z |
| format | Article |
| id | doaj.art-372edd1d88ed4ecaa34c81b607b977a8 |
| institution | Directory Open Access Journal |
| issn | 2504-4494 |
| language | English |
| last_indexed | 2024-03-08T20:37:37Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Manufacturing and Materials Processing |
| spelling | doaj.art-372edd1d88ed4ecaa34c81b607b977a82023-12-22T14:18:22ZengMDPI AGJournal of Manufacturing and Materials Processing2504-44942023-11-017619410.3390/jmmp7060194Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective OptimizationMona A. Aboueleaz0Noha Naeim1Islam H. Abdelgaliel2Mohamed F. Aly3Ahmed Elkaseer4Production Engineering and Mechanical Design Department, Faulty of Engineering, Mansoura University, Mansoura 35516, EgyptDepartment of Production Engineering and Mechanical Design, Faculty of Engineering, Port Said University, Port Fuad 42526, EgyptDepartment of Mechanical Engineering, School of Sciences and Engineering, The American University in Cairo, AUC Avenue, New Cairo 11835, EgyptDepartment of Mechanical Engineering, School of Sciences and Engineering, The American University in Cairo, AUC Avenue, New Cairo 11835, EgyptDepartment of Production Engineering and Mechanical Design, Faculty of Engineering, Port Said University, Port Fuad 42526, EgyptThis research investigates the multi-response of both material removal rate (MRR) and surface roughness (Ra) for the wire electrical discharge machining (WEDM) of two stainless steel alloys: AISI 304 and AISI 316. Experimental results are utilized to compare the machining responses obtained for AISI 316 with those obtained for AISI 304, as previously reported in the literature. The experimental work is conducted through a full factorial experimental design of five running parameters with different levels: applied voltage, transverse feed, pulse-on/pulse-off times and current intensity. The machined workpieces are analyzed using an image processing technique in order to evaluate the size of cut slots to allow the calculation of the MRR. Followed by the characterization of the surface roughness along the side walls of the slots. Different mathematical regression techniques were developed to represent the multi-response of both materials using the MATLAB regression toolbox. It was found that WEDM process parameters have a fuzzy influence on the responses of both material models. This allowed for multi-objective optimization of the regression models using four different techniques: multi-objective genetic algorithm (MOGA), multi-objective pareto search algorithm (MOPSA), weighted value grey wolf optimizer (WVGWO) and osprey optimization algorithm (OOA). The optimization results reveal that the optimal WEDM parameters of each response are inconsistent to the others. Hence, the optimal results are considered a compromise between the best results of different responses. Noteworthily, the multi-objective pareto search algorithm outperformed the other candidates. Eventually, the optimal results of both materials share the high voltage, high transverse feed rate and low pulse-off time parameters; however, AISI 304 requires low pulse-on time and current intensity levels while AISI 316 optimal results entail higher pulse-on time and current levels.https://www.mdpi.com/2504-4494/7/6/194WEDMstainless steel 304stainless steel 316surface integrityMRRproductivity |
| spellingShingle | Mona A. Aboueleaz Noha Naeim Islam H. Abdelgaliel Mohamed F. Aly Ahmed Elkaseer Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective Optimization Journal of Manufacturing and Materials Processing WEDM stainless steel 304 stainless steel 316 surface integrity MRR productivity |
| title | Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective Optimization |
| title_full | Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective Optimization |
| title_fullStr | Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective Optimization |
| title_full_unstemmed | Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective Optimization |
| title_short | Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective Optimization |
| title_sort | wire electrical discharge machining of aisi304 and aisi316 alloys a comparative assessment of machining responses empirical modeling and multi objective optimization |
| topic | WEDM stainless steel 304 stainless steel 316 surface integrity MRR productivity |
| url | https://www.mdpi.com/2504-4494/7/6/194 |
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