Parametric estimation for AWJ cutting of Ti-6Al-4V alloy using Rat swarm optimization algorithm

References

• Tripathi, D.; Vachhani, K.; Bandhu, D.; Kumari, S.; Kumar, V.; Abhishek, K. Experimental Investigation and Optimisation of Abrasive Waterjet Machining Parameters for GFRP Composites Using Metaphor-Less Algorithms. Mater. Manuf. Processes. 2021, 36(7), 803–813. DOI: 10.1080/10426914.2020.1866193.
   Web of Science ®Google Scholar
• Doğankaya, E.; Kahya, M.; Özgür Ünver, H. Abrasive Water Jet Machining of UHMWPE and Trade-Off Optimisation. Mater. Manuf. Processes. 2020, 35(12), 1339–1351. DOI: 10.1080/10426914.2020.1772486.
   Web of Science ®Google Scholar
• Panchal, K.; Shaikh, A. Performance Analysis and Process Parameters Optimisation on Specific Cutting Energy in the Abrasive Waterjet Cutting. Int. J. Ambient Energy. 2021, 1–8. DOI: 10.1080/01430750.2021.1873851.
   Web of Science ®Google Scholar
• Naresh Babu, M.; Muthukrishnan, N. Investigation of Multiple Process Parameters in Abrasive Water Jet Machining of Tiles. J. Chin. Inst. Eng. 2015, 38(6), 692–700. DOI: 10.1080/02533839.2015.1010944.
   Web of Science ®Google Scholar
• Ishfaq, K.; Ahmad Mufti, N.; Ahmed, N.; Pervaiz, S. Abrasive Waterjet Cutting of Cladded Material: Kerf Taper and MRR Analysis. Mater. Manuf. Processes. 2018, 34(5), 544–553. DOI: 10.1080/10426914.2018.1544710.
   Web of Science ®Google Scholar
• Llanto, J.; Tolouei-Rad, M.; Vafadar, A.; Aamir, M. Recent Progress Trend on Abrasive Waterjet Cutting of Metallic Materials: A Review. Appl. Sci. 2021, 11(8), 3344. DOI: 10.3390/app11083344.
   Google Scholar
• Rao, R.; Rai, D.; Balic, J. Multi-Objective Optimisation of Abrasive Waterjet Machining Process Using Jaya Algorithm and PROMETHEE Method. J. Intell. Manuf. 2017, 30(5), 2101–2127. DOI: 10.1007/s10845-017-1373-8.
   Web of Science ®Google Scholar
• Dharmendra, B. V.; Kodali, S. P.; Boggarapu, N. R. Multi-Objective Optimisation for Optimum Abrasive Water Jet Machining Process Parameters of Inconel 718 Adopting the Taguchi Approach. Multidiscip. Model. Mater. Struct. 2020, 16(2), 306–321. DOI: 10.1108/MMMS-10-2018-0175.
   Web of Science ®Google Scholar
• Karataş, M. A.; Motorcu, A. R.; Gökkaya, H. Optimisation of Machining Parameters for Kerf Angle and Roundness Error in Abrasive Water Jet Drilling of CFRP Composites with Different Fiber Orientation Angles. J. Braz. Soc. Mech. Sci. Eng. 2020, 42, 173. DOI: 10.1007/s40430-020-2261-2.
   Web of Science ®Google Scholar
• Jagadeesh, B.; Dinesh Babu, P.; Nalla Mohamed, M.; Marimuthu, P. Experimental Investigation and Optimisation of Abrasive Water Jet Cutting Parameters for the Improvement of Cut Quality in Carbon Fiber Reinforced Plastic Laminates. J. Ind. Text. 2017, 48(1), 178–200. DOI: 10.1177/1528083717725911.
   Web of Science ®Google Scholar
• Shanmugam, A., Krishnamurthy, K., Mohanraj, T. Experimental Study of Surface Roughness and Taper Angle in Abrasive Water Jet Machining of 7075 Aluminium Composite Using Response Surface Methodology. Surf. Rev. Lett. 2019, 1950112, 1–9. DOI: 10.1142/S02.
   Google Scholar
• Mahalingam, S., Kuppusamy, B., Natarajan, Y. Multi-Objective Soft Computing Approaches to Evaluate the Performance of Abrasive Water Jet Drilling Parameters on Die Steel. Arab. J. Sci. Eng. 2021, 46, 7893–7907. DOI: 10.1007/s13369-021-05591-x.
   Web of Science ®Google Scholar
• Qiang, Z.; Miao, X.; Wu, M.; Sawhney, R. Optimisation of Abrasive Water Jet Machining Using Multi-Objective Cuckoo Search Algorithm. Int. J. Adv. Manuf. Technol. 2018, 99(5–8), 1257–1266. DOI: 10.1007/s00170-018-2549-x.
   Web of Science ®Google Scholar
• Wang, S.; Hu, D.; Yang, F.; Lin, P. Research on Kerf Error of Aluminum Alloy 6061-T6 Cut by Abrasive Water Jet. Int. J. Adv. Manuf. Technol. 2022, 118, 2513–2521. DOI: 10.1007/s00170-021-08056-5.
   Web of Science ®Google Scholar
• Shukla, R.; Singh, D. Experimentation Investigation of Abrasive Water Jet Machining Parameters Using Taguchi and Evolutionary Optimisation Techniques. Swarm Evol. Comput. 2017, 32, 167–183. DOI: 10.1016/j.swevo.2016.07.002.
   Web of Science ®Google Scholar
• Santhanakumar, M.; Adalarasan, R.; Rajmohan, M. Experimental Modelling and Analysis in Abrasive Waterjet Cutting of Ceramic Tiles Using Grey-Based Response Surface Methodology. Arab. J. Sci. Eng. 2015, 40(11), 3299–3311. DOI: 10.1007/s13369-015-1775-x.
   Web of Science ®Google Scholar
• Pawar, P.; Vidhate, U.; Khalkar, M. Improving the Quality Characteristics of Abrasive Water Jet Machining of Marble Material Using Multi-Objective Artificial Bee Colony Algorithm. J. Comput. Des. Eng. 2017, 5(3), 319–328. DOI: 10.1016/j.jcde.2017.12.002.
   Web of Science ®Google Scholar
• Chakraborty, S.; Mitra, A. Parametric Optimisation of Abrasive Water-Jet Machining Processes Using Grey Wolf Optimizer. Mater. Manuf. Processes. 2018, 33(13), 1471–1482. DOI: 10.1080/10426914.2018.1453158.
   Web of Science ®Google Scholar
• Tamilarasan, A.; Renugambal, A.; Manikanta, D.; Sekhar Reddy, G. B. C.; Sravankumar, K.; Sreekar, B.; Prasadreddy, G. V. Application of Crow Search Algorithm for the Optimisation of Abrasive Water Jet Cutting Process Parameters. IOP Conf. Ser. Mater. Sci. Eng. 2018, 390, 012034. DOI: 10.1088/1757-899x/390/1/012034.
   Google Scholar
• Arumugam, S.; Chengareddy, P.; Tamilarasan, A.; Santhanam, V. RSM and Crow Search Algorithm-Based Optimisation of Ultrasonicated Transesterification Process Parameters on Synthesis of Polyol Ester-Based Biolubricant. Arab. J. Sci. Eng. 2019, 44(6), 5535–5548. DOI: 10.1007/s13369-019-03847-1.
   Web of Science ®Google Scholar
• Li, H.; Wang, J. An Experimental Study of Abrasive Waterjet Machining of Ti-6Al-4V. Int. J. Adv. Manuf. Technol. 2015, 81(1–4), 361–369. DOI: 10.1007/s00170-015-7245-5.
   Web of Science ®Google Scholar
• Umanath, K.; Devika, D.; Rashia Begum, S. Experimental Investigation of Role of Particles Size and Cutting Passes in Abrasive Waterjet Machining Process on Titanium Alloy (Ti–6al–4v) Using Taguchi’s Method. Mater. Manuf. Processes. 2021, 36(8), 936–949. DOI: 10.1080/10426914.2020.1866202.
   Web of Science ®Google Scholar
• Jani, S.; Senthil Kumar, A.; Khan, M.; Sujin Jose, A. Design and Optimisation of Unit Production Cost for AWJ Process on Machining Hybrid Natural Fibre Composite Material. Int. J. Light Weight Mater. Manuf. 2021, 4(4), 491–497. DOI: 10.1016/j.ijlmm.2021.07.002.
   Google Scholar
• Dhiman, G.; Garg, M.; Nagar, A.; Kumar, V.; Dehghani, M. A Novel Algorithm for Global Optimisation: Rat Swarm Optimizer. J. Ambient. Intell. Humaniz. Comput. 2020, 12(8), 8457–8482. DOI: 10.1007/s12652-020-02580-0.
   Web of Science ®Google Scholar
• Ghadge, R.; Prakash, S. Investigation and Prediction of Hybrid Composite Leaf Spring Using Deep Neural Network Based Rat Swarm Optimisation. Mech. Based Des. Struct. 2021, 1–30. DOI: 10.1080/15397734.2021.1972309.
   Web of Science ®Google Scholar