Multi-response optimization of turning parameters for laser powder bed fusion 17-4PH stainless steel using PCA-GRA
Bibliographic record
Abstract
No abstract is available for this record. The assistant can identify its topic from the title, but cannot infer the study’s results.
Source: Not provided · Quality: missing
Research context
OpenAlex topics: Additive Manufacturing Materials and Processes · Advanced machining processes and optimization · Laser Material Processing Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (32)
Show source-provided references
1. Hakami A, Ojo SA, Abere DV, Uzuh FD, Robert RA (2025) Advancements in metal additive manufacturing: opportunities, limitations, impact on properties, and potential solutions: a review. Prog Addit Manuf 10:4447–4495. https://doi.org/10.1007/s40964-024-00885-610.1007/s40964-024-00885-6 ↗
2. Mansoura A, Omidi N, Barka N, Karganroudi SS, Dehghan S (2024) Selective Laser Melting of Stainless Steels: A review of Process, Microstructure and Properties. Met Mater Int 30:2343–2371. https://doi.org/10.1007/s12540-024-01650-810.1007/s12540-024-01650-8 ↗
3. Sghaier TAM, Sahlaoui H, Mabrouki T, Sallem H, Rech J (2023) Selective Laser Melting of Stainless-Steel: A Review of Process, Microstructure, Mechanical Properties and Post-Processing treatments. Int J Mater Form 16:41. https://doi.org/10.1007/s12289-023-01769-w10.1007/s12289-023-01769-w ↗
4. Shi X, Liu X, Ren S, Lu P, Xie Z, Wu M (2022) Selective laser melting fabricated tungsten with thin-walled structure: role of linear energy density on temperature evolution and manufacturing quality. Int J Mater Form 15:2. https://doi.org/10.1007/s12289-021-01646-410.1007/s12289-021-01646-4 ↗
5. Bertocco A, Iannitti G, Caraviello A, Esposito L (2022) Lattice structures in stainless steel 17-4PH manufactured via selective laser melting (SLM) process: dimensional accuracy, satellites formation, compressive response and printing parameters optimization. Int J Adv Manuf Technol 120:4935–4949. https://doi.org/10.1007/s00170-022-08946-210.1007/s00170-022-08946-2 ↗
6. Kartikeya Sarma I, Selvaraj N, Kumar A (2023) Parametric investigation and characterization of 17 – 4 PH stainless steel parts fabricated by selective laser melting. J Cent South Univ 30:855–870. https://doi.org/10.1007/s11771-022-5150-210.1007/s11771-022-5150-2 ↗
7. Alkunte S, Gupta M, Shingare K, More N, Mali A, Ingle N, Nalawade S, Khan AU, Sinha N, Liao K, Fidan I (2025) Porosity in additive manufacturing: influence on mechanical, thermal, and electrical properties—a review. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-025-16452-410.1007/s00170-025-16452-4 ↗
8. Fayazfar H, Sharifi J, Keshavarz MK, Ansari M (2023) An overview of surface roughness enhancement of additively manufactured metal parts: a path towards removing the post-print bottleneck for complex geometries. Int J Adv Manuf Technol 125:1061–1113. https://doi.org/10.1007/s00170-023-10814-610.1007/s00170-023-10814-6 ↗
9. Sadiq MA, Hoang NM, Valencia N, Obeidat S, Hung WNP (2018) Experimental study of micromilling selective laser melted Inconel 718 superalloy. Procedia Manuf 26:983–992. https://doi.org/10.1016/j.promfg.2018.07.12910.1016/j.promfg.2018.07.129 ↗
10. Li B, Tian X, Zhang M (2020) Modeling and multi-objective optimization of cutting parameters in the high-speed milling using RSM and improved TLBO algorithm. Int J Adv Manuf Technol 111:2323–2335. https://doi.org/10.1007/s00170-020-06284-910.1007/s00170-020-06284-9 ↗
11. (SMAW) An Integrated Approach of GRA Coupled with Principal Component Analysis for Multi-Optimization of Shielded Metal Arc Welding, Process (2025) (n.d.). https://www.mdpi.com/1996-1944/13/16/3457 (accessed September 1010.3390/ma13163457 ↗
12. Pereira JLJ, Oliver GA, Francisco MB, Cunha SS, Gomes GF (2022) A Review of Multi-objective Optimization: Methods and Algorithms in Mechanical Engineering Problems. Arch Comput Methods Eng 29:2285–2308. https://doi.org/10.1007/s11831-021-09663-x10.1007/s11831-021-09663-x ↗
13. Chakraborty S, Datta HN, Chakraborty S (2023) Grey Relational Analysis-Based Optimization of Machining Processes: a Comprehensive Review, Process Integr. Optim Sustain 7:609–639. https://doi.org/10.1007/s41660-023-00311-410.1007/s41660-023-00311-4 ↗
14. Irrinki H, Jangam JSD, Pasebani S, Badwe S, Stitzel J, Kate K, Gulsoy O, Atre SV (2018) Effects of particle characteristics on the microstructure and mechanical properties of 17 – 4 PH stainless steel fabricated by laser-powder bed fusion. Powder Technol 331:192–203. https://doi.org/10.1016/j.powtec.2018.03.02510.1016/j.powtec.2018.03.025 ↗
15. Sghaier TAM, Sahlaoui H, Mabrouki T, Sallem H, Rech J (2024) A comparative study on microstructure and mechanical properties of 17-4PH processed by a laser powder bed fusion vs rolling process. Prog Addit Manuf. https://doi.org/10.1007/s40964-024-00837-010.1007/s40964-024-00837-0 ↗
16. Abas M, Sayd L, Akhtar R, Khalid QS, Khan AM, Pruncu CI (2020) Optimization of machining parameters of aluminum alloy 6026-T9 under MQL-assisted turning process. J Mater Res Technol 9:10916–10940. https://doi.org/10.1016/j.jmrt.2020.07.07110.1016/j.jmrt.2020.07.071 ↗
17. Nandagopal K, Kailasanathan C (2016) Analysis of mechanical properties and optimization of gas tungsten Arc welding (GTAW) parameters on dissimilar metal titanium (6Al4V) and aluminium 7075 by Taguchi and ANOVA techniques. J Alloys Compd 682:503–516. https://doi.org/10.1016/j.jallcom.2016.05.00610.1016/j.jallcom.2016.05.006 ↗
18. Panda S, Mishra D, Biswal BB (2011) Determination of optimum parameters with multi-performance characteristics in laser drilling—A grey relational analysis approach. Int J Adv Manuf Technol 54:957–967. https://doi.org/10.1007/s00170-010-2985-810.1007/s00170-010-2985-8 ↗
19. Qazi MI, Akhtar R, Abas M, Khalid QS, Babar AR, Pruncu CI (2020) An Integrated Approach of GRA Coupled with Principal Component Analysis for Multi-Optimization of Shielded Metal Arc Welding (SMAW) Process. Materials 13:3457. https://doi.org/10.3390/ma1316345710.3390/ma13163457 ↗
20. Palanikumar K, Latha B, Senthilkumar VS, Davim JP (2012) Analysis on Drilling of Glass Fiber–Reinforced Polymer (GFRP) Composites Using Grey Relational Analysis. Mater Manuf Process 27:297–305. https://doi.org/10.1080/10426914.2011.57786510.1080/10426914.2011.577865 ↗
21. Zhang Y, Ren H, Yan H, Long Y (2025) In Situ Study of Surface Morphology Formation Mechanism During Laser Powder Bed Fusion. Appl Sci 15:2550. https://doi.org/10.3390/app1505255010.3390/app15052550 ↗
22. Korkmaz ME, Günay M (2018) Finite Element Modelling of Cutting Forces and Power Consumption in Turning of AISI 420 Martensitic Stainless Steel. Arab J Sci Eng 43:4863–4870. https://doi.org/10.1007/s13369-018-3204-410.1007/s13369-018-3204-4 ↗
23. Liu G, Zou B, Huang C, Wang X, Wang J, Liu Z (2016) Tool damage and its effect on the machined surface roughness in high-speed face milling the 17-4PH stainless steel. Int J Adv Manuf Technol 83:257–264. https://doi.org/10.1007/s00170-015-7564-610.1007/s00170-015-7564-6 ↗
24. Ji H, Gupta MK, Song Q, Cai W, Zheng T, Zhao Y, Liu Z, Pimenov DY (2021) Microstructure and machinability evaluation in micro milling of selective laser melted Inconel 718 alloy. J Mater Res Technol 14:348–362. https://doi.org/10.1016/j.jmrt.2021.06.08110.1016/j.jmrt.2021.06.081 ↗
25. Binali R, Demirpolat H, Kuntoğlu M, Salur E (2023) Different Aspects of Machinability in Turning of AISI 304 Stainless Steel: A Sustainable Approach with MQL Technology. Metals 13:1088. https://doi.org/10.3390/met1306108810.3390/met13061088 ↗
26. Singh M, Dixit AR, Sharma AK (2026) Experimental and Predictive Analysis of Cutting Force and Surface Roughness in MQL-Assisted Turning of AISI 304 Using Varying Concentrations of Al2O3 Nanofluid. JOM 78:590–607. https://doi.org/10.1007/s11837-025-07872-410.1007/s11837-025-07872-4 ↗
27. Natesh CP, Siddeshkumar NG, Srinivasa G, Shivaramakrishna A, Pruthvi HM, Prasad CD, Shashidhara YM, Amarendra HJ, Tiwari A, Aden AA (2025) Multi-objective optimization of surface roughness and MRR in AISI 316L stainless steel processed by MQL end milling using taguchi, RSM, ANN, and RFR methods. Sci Rep 15:36583. https://doi.org/10.1038/s41598-025-20454-310.1038/s41598-025-20454-3 ↗
28. Ross NS, Mashinini PM, Sherin Shibi C, Kumar Gupta M, Erdi Korkmaz M, Krolczyk GM, Sharma VS (2024) A new intelligent approach of surface roughness measurement in sustainable machining of AM-316L stainless steel with deep learning models. Measurement 230:114515. https://doi.org/10.1016/j.measurement.2024.11451510.1016/j.measurement.2024.114515 ↗
29. Praveen N, N g SK, R S, Prasad CD, Soni H, Prasad VGM, T c SK, Mallik US, Aden AA (2025) Effect of CNC Turning Parameters on MRR, Cutting Force and Surface Roughness for Ternary Shape Memory Alloys (SMAs), Results Eng. 26:104876. https://doi.org/10.1016/j.rineng.2025.10487610.1016/j.rineng.2025.104876 ↗
30. Stephens MA (1974) EDF Statistics for Goodness of Fit and Some Comparisons. J Am Stat Assoc 69:730–737. https://doi.org/10.1080/01621459.1974.1048019610.1080/01621459.1974.10480196 ↗
31. Denkena B, Dittrich M-A, Noske H, Witt M (2020) Statistical approaches for semi-supervised anomaly detection in machining. Prod Eng 14:385–393. https://doi.org/10.1007/s11740-020-00958-910.1007/s11740-020-00958-9 ↗
32. Chate GR, Patel GCM, Kulkarni RM, Vernekar P, Deshpande AS, Parappagoudar MB (2018) Study of the Effect of Nano-silica Particles on Resin-Bonded Moulding Sand Properties and Quality of Casting. Silicon 10:1921–1936. https://doi.org/10.1007/s12633-017-9705-z10.1007/s12633-017-9705-z ↗