Abstract
AbstractThe titanium alloy, Ti6Al4V, is a popularly used material in aerospace and medical applications due to its specific attributes, such as excellent strength-to-weight ratio and resistance to corrosion. Ti6Al4V is challenging to machine using conventional methods due to its poor thermal conductivity, which necessitates the use of unconventional machining methods like abrasive water jet machining (AWJM). In this work, AWJM was preferred for machining Ti6Al4V, considering three key process variables: nozzle traverse speed (Tv), abrasive flow rate (Af), and stand-off distance (Sd). The performance of the AWJM process was assessed using three main metrics: Material removal rate (MRR), Surface roughness (SR), and Kerf taper angle (θ), which were crucial for evaluating the effectiveness of the AWJM. Taguchi’s L9 array, a design of experiments method, was used to plan the experiments. The adequacy of the developed models was assessed by analysis of variance (ANOVA). ANOVA results have shown that Tv, Af, and Sd were found to have a significant effect on MRR, SR, θ with contributions of 73.15%, 49.72%, and 78.35% respectively. The Passing Vehicle Search algorithm was adopted to find the global optimal solution. Simultaneous optimization results using the PVS algorithm have shown the optimal MRR, SR, and θ values of 0.17 g/min, 3.28 μm, and 2.45, respectively, at Tv of 237 mm/min, Af of 450 g/min, and Sd of 2.0 mm. The optimization results with Pareto points will help to achieve desired outcomes by selecting appropriate input conditions.
Funder
Manipal Academy of Higher Education, Manipal
Publisher
Springer Science and Business Media LLC
Reference57 articles.
1. Vora, J., Shah, Y., Khanna, S., Patel, V.K., Jagdale, M., Chaudhari, R.: Multi-response optimization and influence of expanded graphite on performance of WEDM process of Ti6Al4V. J. Manuf. Mater. Process. 7(3), 111 (2023)
2. Farooq, M.U., Ali, M.A., Anwar, S., Bhatti, H.A.: Process parameters optimization and performance analysis of micro-complex geometry machining on Ti6Al4V. Int. J. Interact. Des. Manuf. :1–21. (2024)
3. Devarasiddappa, D., Chandrasekaran, M.: Experimental investigation and optimization of sustainable performance measures during wire-cut EDM of Ti-6Al-4V alloy employing preference-based TLBO algorithm. Mater. Manuf. Processes. 35(11), 1204–1213 (2020)
4. Wei, G., Tan, M., Attarilar, S., Li, J., Uglov, V.V., Wang, B., et al.: An overview of Surface Modification, a way toward fabrication of nascent Biomedical Ti-6Al-4V alloys. J. Mater. Res. Technol. (2023)
5. Khan, M.A., Jaffery, S.H.I., Khan, M., Younas, M., Butt, S.I., Ahmad, R., et al.: Multi-objective optimization of turning titanium-based alloy Ti-6Al-4V under dry, wet, and cryogenic conditions using gray relational analysis (GRA). Int. J. Adv. Manuf. Technol. 106(9), 3897–3911 (2020)
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献