Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques
Electric discharge machining is an essential modern manufacturing process employed to machine porous sintered metals. The sintered 316L porous stainless steel (PSS) components are widely used in diverse engineering domains, as interconnected pores are present. The PSS material has excellent lightwei...
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MDPI AG
2022-09-01
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| Online Access: | https://www.mdpi.com/1996-1944/15/19/6571 |
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| author | Himanshu Singh Praful Patrange Prateek Saxena Yogesh M. Puri |
| author_facet | Himanshu Singh Praful Patrange Prateek Saxena Yogesh M. Puri |
| author_sort | Himanshu Singh |
| collection | DOAJ |
| description | Electric discharge machining is an essential modern manufacturing process employed to machine porous sintered metals. The sintered 316L porous stainless steel (PSS) components are widely used in diverse engineering domains, as interconnected pores are present. The PSS material has excellent lightweight and damping properties and superior mechanical and metallurgical properties. However, conventional machining techniques are not suitable for porous metals machining. Such techniques tend to block the micro-pores, resulting in a decrease in porous materials’ breathability. Thus, the EDM process is an effective technique for porous metal machining. The input process parameters selected in this study are peak current <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><msub><mi>I</mi><mi>p</mi></msub><mo>)</mo></mrow></semantics></math></inline-formula>, pulse on time <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><msub><mi>T</mi><mrow><mi>o</mi><mi>n</mi></mrow></msub><mo>)</mo></mrow></semantics></math></inline-formula>, voltage <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><mi>V</mi><mo>)</mo></mrow></semantics></math></inline-formula>, flushing pressure <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><msub><mi>f</mi><mi>p</mi></msub><mo>)</mo></mrow></semantics></math></inline-formula>, and porosity. The response parameters selected are material removal rate (MRR) and tool wear rate (TWR). The present work aims to obtain optimum machining process parameters in the EDM of porous sintered SS316L using two meta-heuristic optimization techniques, i.e., Teaching Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO) algorithms, to maximize the MRR and minimize the TWR values. In the case of PSS having a 12.60% porosity value, PSO and TLBO algorithms give same optimum machining parameters. However, for PSS having an 18.85% porosity value, the PSO algorithm improves by about 5.25% in MRR and by 5.63% in TWR over the TLBO. In the case of PSS having a 31.11% porosity value, the PSO algorithm improves about 3.73% in MRR and 6.46% in TWR over the TLBO. The PSO algorithm is found to be consistent and to converge more quickly, taking minimal computational time and effort compared to the TLBO algorithm. The present study’s findings contribute valuable information in regulating the EDM performance in machining porous SS316L. |
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| language | English |
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| spelling | doaj.art-a231b346004a4d3398670f71fe39ceb12023-11-23T20:53:05ZengMDPI AGMaterials1996-19442022-09-011519657110.3390/ma15196571Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic TechniquesHimanshu Singh0Praful Patrange1Prateek Saxena2Yogesh M. Puri3Department of Mechanical Engineering, Visvesvaraya National Institute of Technology, Nagpur 440010, Maharashtra, IndiaDepartment of Mechanical Engineering, Visvesvaraya National Institute of Technology, Nagpur 440010, Maharashtra, IndiaSchool of Mechanical and Materials Engineering, Indian Institute of Technology, Mandi 175005, Himachal Pradesh, IndiaDepartment of Mechanical Engineering, Visvesvaraya National Institute of Technology, Nagpur 440010, Maharashtra, IndiaElectric discharge machining is an essential modern manufacturing process employed to machine porous sintered metals. The sintered 316L porous stainless steel (PSS) components are widely used in diverse engineering domains, as interconnected pores are present. The PSS material has excellent lightweight and damping properties and superior mechanical and metallurgical properties. However, conventional machining techniques are not suitable for porous metals machining. Such techniques tend to block the micro-pores, resulting in a decrease in porous materials’ breathability. Thus, the EDM process is an effective technique for porous metal machining. The input process parameters selected in this study are peak current <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><msub><mi>I</mi><mi>p</mi></msub><mo>)</mo></mrow></semantics></math></inline-formula>, pulse on time <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><msub><mi>T</mi><mrow><mi>o</mi><mi>n</mi></mrow></msub><mo>)</mo></mrow></semantics></math></inline-formula>, voltage <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><mi>V</mi><mo>)</mo></mrow></semantics></math></inline-formula>, flushing pressure <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><msub><mi>f</mi><mi>p</mi></msub><mo>)</mo></mrow></semantics></math></inline-formula>, and porosity. The response parameters selected are material removal rate (MRR) and tool wear rate (TWR). The present work aims to obtain optimum machining process parameters in the EDM of porous sintered SS316L using two meta-heuristic optimization techniques, i.e., Teaching Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO) algorithms, to maximize the MRR and minimize the TWR values. In the case of PSS having a 12.60% porosity value, PSO and TLBO algorithms give same optimum machining parameters. However, for PSS having an 18.85% porosity value, the PSO algorithm improves by about 5.25% in MRR and by 5.63% in TWR over the TLBO. In the case of PSS having a 31.11% porosity value, the PSO algorithm improves about 3.73% in MRR and 6.46% in TWR over the TLBO. The PSO algorithm is found to be consistent and to converge more quickly, taking minimal computational time and effort compared to the TLBO algorithm. The present study’s findings contribute valuable information in regulating the EDM performance in machining porous SS316L.https://www.mdpi.com/1996-1944/15/19/6571porous SS316Lsinteringelectric discharge machiningoptimization |
| spellingShingle | Himanshu Singh Praful Patrange Prateek Saxena Yogesh M. Puri Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques Materials porous SS316L sintering electric discharge machining optimization |
| title | Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques |
| title_full | Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques |
| title_fullStr | Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques |
| title_full_unstemmed | Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques |
| title_short | Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques |
| title_sort | multi objective optimization of the process parameters in electric discharge machining of 316l porous stainless steel using metaheuristic techniques |
| topic | porous SS316L sintering electric discharge machining optimization |
| url | https://www.mdpi.com/1996-1944/15/19/6571 |
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