Key initiatives to improve the machining characteristics of Inconel-718 alloy: Experimental analysis and optimization
Inconel 718 is a heat-resistant Ni-based superalloy widely used, particularly, in aircraft and aero-engineering applications. It has poor machinability due to its unique thermal and mechanical properties. For this reason, studies have been carried out from past to present to improve the machinabilit...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-11-01
|
| Series: | Journal of Materials Research and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S223878542201599X |
| _version_ | 1828116021900214272 |
|---|---|
| author | Saeed Rubaiee Mohd Danish Munish Kumar Gupta Anas Ahmed Syed Mohd Yahya Mehmet Bayram Yildirim Murat Sarikaya Mehmet Erdi Korkmaz |
| author_facet | Saeed Rubaiee Mohd Danish Munish Kumar Gupta Anas Ahmed Syed Mohd Yahya Mehmet Bayram Yildirim Murat Sarikaya Mehmet Erdi Korkmaz |
| author_sort | Saeed Rubaiee |
| collection | DOAJ |
| description | Inconel 718 is a heat-resistant Ni-based superalloy widely used, particularly, in aircraft and aero-engineering applications. It has poor machinability due to its unique thermal and mechanical properties. For this reason, studies have been carried out from past to present to improve the machinability of Nickel-based (Ni) alloys. Further improvement can be achieved by applying hybrid multi-objective optimization strategies to ensure that cutting parameters and cooling/lubrication strategies are also adjusted effectively. That is why, in this research, the machinability of Inconel 718 is optimized under various sustainable lubricating environments i.e., dry medium, minimum quantity lubrication (MQL), nano-MQL, and cryogenic conditions at different machining parameters during end-milling process. Subsequently, the analysis of variance (ANOVA) approach was implanted to apprehend the impact of each machining parameter. Finally, to optimize machining environments, two advanced optimization algorithms (non-dominated sorting genetic algorithm II (NSGA-II) and the Teaching-learning-based optimization (TLBO) approach) were introduced. As a result, both methods have demonstrated remarkable efficiency in machine response prediction. Both methodologies demonstrate that a cutting speed of 90 m/min, feed rate of 0.05 mm/rev, and CO2 snow are the optimal circumstances for minimizing machining responses during milling of Inconel 718. |
| first_indexed | 2024-04-11T12:49:31Z |
| format | Article |
| id | doaj.art-36b19ab92af5412aa7fd716ccea9beb2 |
| institution | Directory Open Access Journal |
| issn | 2238-7854 |
| language | English |
| last_indexed | 2024-04-11T12:49:31Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Materials Research and Technology |
| spelling | doaj.art-36b19ab92af5412aa7fd716ccea9beb22022-12-22T04:23:14ZengElsevierJournal of Materials Research and Technology2238-78542022-11-012127042720Key initiatives to improve the machining characteristics of Inconel-718 alloy: Experimental analysis and optimizationSaeed Rubaiee0Mohd Danish1Munish Kumar Gupta2Anas Ahmed3Syed Mohd Yahya4Mehmet Bayram Yildirim5Murat Sarikaya6Mehmet Erdi Korkmaz7Department of Mechanical and Materials Engineering, University of Jeddah, Jeddah, 21589, Saudi Arabia; Department of Industrial and Systems Engineering, University of Jeddah, Jeddah, 21589, Saudi ArabiaDepartment of Mechanical and Materials Engineering, University of Jeddah, Jeddah, 21589, Saudi Arabia; Corresponding author.Faculty of Mechanical Engineering, Opole University of Technology, 76 Proszkowska St., Opole 45-758, PolandDepartment of Industrial and Systems Engineering, University of Jeddah, Jeddah, 21589, Saudi ArabiaSustainable Energy and Acoustics Research Lab, Mechanical Engineering Department, Aligarh Muslim University, Aligarh-202002, India; Corresponding author.Department of Industrial and Manufacturing Engineering, Wichita State University, Wichita, KS 67260-0035, USADepartment of Mechanical Engineering, Sinop University, Sinop, TurkeyDepartment of Mechanical Engineering, Karabük University, Karabük, TurkeyInconel 718 is a heat-resistant Ni-based superalloy widely used, particularly, in aircraft and aero-engineering applications. It has poor machinability due to its unique thermal and mechanical properties. For this reason, studies have been carried out from past to present to improve the machinability of Nickel-based (Ni) alloys. Further improvement can be achieved by applying hybrid multi-objective optimization strategies to ensure that cutting parameters and cooling/lubrication strategies are also adjusted effectively. That is why, in this research, the machinability of Inconel 718 is optimized under various sustainable lubricating environments i.e., dry medium, minimum quantity lubrication (MQL), nano-MQL, and cryogenic conditions at different machining parameters during end-milling process. Subsequently, the analysis of variance (ANOVA) approach was implanted to apprehend the impact of each machining parameter. Finally, to optimize machining environments, two advanced optimization algorithms (non-dominated sorting genetic algorithm II (NSGA-II) and the Teaching-learning-based optimization (TLBO) approach) were introduced. As a result, both methods have demonstrated remarkable efficiency in machine response prediction. Both methodologies demonstrate that a cutting speed of 90 m/min, feed rate of 0.05 mm/rev, and CO2 snow are the optimal circumstances for minimizing machining responses during milling of Inconel 718.http://www.sciencedirect.com/science/article/pii/S223878542201599XInconel 718Cooling/lubrication strategiesEnd millingAdvanced optimization approachesNSGA-II and TLBO |
| spellingShingle | Saeed Rubaiee Mohd Danish Munish Kumar Gupta Anas Ahmed Syed Mohd Yahya Mehmet Bayram Yildirim Murat Sarikaya Mehmet Erdi Korkmaz Key initiatives to improve the machining characteristics of Inconel-718 alloy: Experimental analysis and optimization Journal of Materials Research and Technology Inconel 718 Cooling/lubrication strategies End milling Advanced optimization approaches NSGA-II and TLBO |
| title | Key initiatives to improve the machining characteristics of Inconel-718 alloy: Experimental analysis and optimization |
| title_full | Key initiatives to improve the machining characteristics of Inconel-718 alloy: Experimental analysis and optimization |
| title_fullStr | Key initiatives to improve the machining characteristics of Inconel-718 alloy: Experimental analysis and optimization |
| title_full_unstemmed | Key initiatives to improve the machining characteristics of Inconel-718 alloy: Experimental analysis and optimization |
| title_short | Key initiatives to improve the machining characteristics of Inconel-718 alloy: Experimental analysis and optimization |
| title_sort | key initiatives to improve the machining characteristics of inconel 718 alloy experimental analysis and optimization |
| topic | Inconel 718 Cooling/lubrication strategies End milling Advanced optimization approaches NSGA-II and TLBO |
| url | http://www.sciencedirect.com/science/article/pii/S223878542201599X |
| work_keys_str_mv | AT saeedrubaiee keyinitiativestoimprovethemachiningcharacteristicsofinconel718alloyexperimentalanalysisandoptimization AT mohddanish keyinitiativestoimprovethemachiningcharacteristicsofinconel718alloyexperimentalanalysisandoptimization AT munishkumargupta keyinitiativestoimprovethemachiningcharacteristicsofinconel718alloyexperimentalanalysisandoptimization AT anasahmed keyinitiativestoimprovethemachiningcharacteristicsofinconel718alloyexperimentalanalysisandoptimization AT syedmohdyahya keyinitiativestoimprovethemachiningcharacteristicsofinconel718alloyexperimentalanalysisandoptimization AT mehmetbayramyildirim keyinitiativestoimprovethemachiningcharacteristicsofinconel718alloyexperimentalanalysisandoptimization AT muratsarikaya keyinitiativestoimprovethemachiningcharacteristicsofinconel718alloyexperimentalanalysisandoptimization AT mehmeterdikorkmaz keyinitiativestoimprovethemachiningcharacteristicsofinconel718alloyexperimentalanalysisandoptimization |