Machinability studies on metal additive manufactured 316L stainless steel using electrochemical machine
Metal additive manufactured 316L stainless steel is considered for machinability studies through electrochemical machining (ECM). This material is used in prototyping in the automotive, aerospace, jewellery and biomedical industries, where customized components for individual circumstances are requ...
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| Format: | Article |
| Language: | English |
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International Association of Physical Chemists (IAPC)
2025-01-01
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| Series: | Journal of Electrochemical Science and Engineering |
| Subjects: | |
| Online Access: | https://pub.iapchem.org/ojs/index.php/JESE/article/view/2567 |
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| author | Rajan Natarajan Shanmugapriyan Kanagaraj Thangavel Palaniappan Deepa Dhanaskodi |
| author_facet | Rajan Natarajan Shanmugapriyan Kanagaraj Thangavel Palaniappan Deepa Dhanaskodi |
| author_sort | Rajan Natarajan |
| collection | DOAJ |
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Metal additive manufactured 316L stainless steel is considered for machinability studies through electrochemical machining (ECM). This material is used in prototyping in the automotive, aerospace, jewellery and biomedical industries, where customized components for individual circumstances are required. In this study, ECM process parameters such as voltage, electrolyte concentration, duty cycle, and selection of an L16 orthogonal array sing four levels were considered for optimization. The multi-criteria decision machining method, namely entropy-based multi-objective optimization, is used for performance analysis based on the ratio analysis method. The study reveals that 14 V, 35 g l-1 NaNO3 electrolyte concen¬tration, and 90 % duty cycle are recommended for optimal machining performance. Accord¬ing to the main effect table, the best combination is 16 V, 35 g l-1 electrolyte concentration, and 60 % duty cycle. Analysis of variance result shows that the duty cycle accounts for approximately 27.06 1% of machining performance, voltage contributes by 24.015 % and electrolyte content contributes roughly 15.58 % to the machining performance. A scanning electron microscope was used to scan each micromachined hole, and different resolution images were taken in order to analyse the machined hole quality.
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| format | Article |
| id | doaj-art-61638f783a18443bb8eb690d3fc61597 |
| institution | Kabale University |
| issn | 1847-9286 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | International Association of Physical Chemists (IAPC) |
| record_format | Article |
| series | Journal of Electrochemical Science and Engineering |
| spelling | doaj-art-61638f783a18443bb8eb690d3fc615972025-01-30T07:51:05ZengInternational Association of Physical Chemists (IAPC)Journal of Electrochemical Science and Engineering1847-92862025-01-0110.5599/jese.2567Machinability studies on metal additive manufactured 316L stainless steel using electrochemical machineRajan Natarajan0Shanmugapriyan Kanagaraj1Thangavel Palaniappan2Deepa Dhanaskodi3Vinayaka Mission’s Kirupananda Variyar Engineering College, Vinayaka Mission’s Research Foundation, Deemed to be University, Salem-636308, IndiaVinayaka Mission’s Kirupananda Variyar Engineering College, Vinayaka Mission’s Research Foundation, Deemed to be University, Salem-636308, IndiaErode Sengunthar Engineering College, Perundurai 638057, IndiaBannari Amman Institute of Technology, Sathyamangalam, 638401, India Metal additive manufactured 316L stainless steel is considered for machinability studies through electrochemical machining (ECM). This material is used in prototyping in the automotive, aerospace, jewellery and biomedical industries, where customized components for individual circumstances are required. In this study, ECM process parameters such as voltage, electrolyte concentration, duty cycle, and selection of an L16 orthogonal array sing four levels were considered for optimization. The multi-criteria decision machining method, namely entropy-based multi-objective optimization, is used for performance analysis based on the ratio analysis method. The study reveals that 14 V, 35 g l-1 NaNO3 electrolyte concen¬tration, and 90 % duty cycle are recommended for optimal machining performance. Accord¬ing to the main effect table, the best combination is 16 V, 35 g l-1 electrolyte concentration, and 60 % duty cycle. Analysis of variance result shows that the duty cycle accounts for approximately 27.06 1% of machining performance, voltage contributes by 24.015 % and electrolyte content contributes roughly 15.58 % to the machining performance. A scanning electron microscope was used to scan each micromachined hole, and different resolution images were taken in order to analyse the machined hole quality. https://pub.iapchem.org/ojs/index.php/JESE/article/view/2567Additively built austenitic steelmicromachined holeselectrochemical process parametersmulti-objective optimization (MOORA)entropy weighting; variance analysis |
| spellingShingle | Rajan Natarajan Shanmugapriyan Kanagaraj Thangavel Palaniappan Deepa Dhanaskodi Machinability studies on metal additive manufactured 316L stainless steel using electrochemical machine Journal of Electrochemical Science and Engineering Additively built austenitic steel micromachined holes electrochemical process parameters multi-objective optimization (MOORA) entropy weighting; variance analysis |
| title | Machinability studies on metal additive manufactured 316L stainless steel using electrochemical machine |
| title_full | Machinability studies on metal additive manufactured 316L stainless steel using electrochemical machine |
| title_fullStr | Machinability studies on metal additive manufactured 316L stainless steel using electrochemical machine |
| title_full_unstemmed | Machinability studies on metal additive manufactured 316L stainless steel using electrochemical machine |
| title_short | Machinability studies on metal additive manufactured 316L stainless steel using electrochemical machine |
| title_sort | machinability studies on metal additive manufactured 316l stainless steel using electrochemical machine |
| topic | Additively built austenitic steel micromachined holes electrochemical process parameters multi-objective optimization (MOORA) entropy weighting; variance analysis |
| url | https://pub.iapchem.org/ojs/index.php/JESE/article/view/2567 |
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