Abstract
This paper presents an analytical approach for optimizing machining parameters in Al-5456/ B4C/ Al2O3 hybrid composites using abrasive water jet machining. The influence of three input parameters, namely Standoff distance (SD), Water pressure (WP), and Jet speed (JS) on two output responses namely material removal rate (MRR), and surface roughness (SRS). Central composite design (CCD) is a popular experimental design technique used in response surface methodology (RSM) for designing experiments and modeling the response of a system to various factors. RSM is commonly used in fields such as engineering, chemistry, and manufacturing to optimize processes and improve product quality. Three factors at three levels in central composite design (CCD) are selected to formulate the experimental design with the support of RSM. The higher MRR is obtained in Experiment no:18 whereas the lowest surface roughness is observed in Experiment no:1. From ANOVA results, it is concluded that the variables WP, SD*JS, WP*JS are the most significant variables to improve the MRR on machining of Al hybrid composites because p-value is less than 0.05. Similarly, in surface roughness, SD is most significant variable followed by WP and JS.
Similar content being viewed by others
Data availability
No datasets were generated or analysed during the current study.
References
Zagórski, I., Kłonica, M., Kulisz, M., Łoza, K.: Effect of the AWJM method on the machined surface layer of AZ91D magnesium alloy and simulation of roughness parameters using neural networks. Materials 11, 2111 (2018)
Oczoś, K.E., Kawalec, A.: Light metals forming. Wydawnictwo Naukowe PWN, Warsaw (2012). (In Polish)
Kulisz, M., Zagórski, I., Korpysa, J.: The effect of abrasive waterjet machining parameters on the condition of Al-Si alloy. Materials 13(14), 3122 (2020). https://doi.org/10.3390/ma13143122
Bañon, F., Sambruno, A., Mayuet, P.F., Gómez-Parra, Á.: Study of abrasive water jet machining as a texturing operation for thin aluminium alloy UNS A92024. Materials 16(10), 3843 (2023). https://doi.org/10.3390/ma16103843
Holmberg, J., Wretland, A., Berglund, J.: Abrasive water jet milling as an efficient manufacturing method for superalloy gas turbine components. J. Manuf. Mater. Process. 6(5), 124 (2022). https://doi.org/10.3390/jmmp6050124
Amar, A.K., Tandon, P.: Investigation of gelatin enabled abrasive water slurry jet machining (AWSJM). CIRP J. Manuf. Sci. Technol. 33, 1–14 (2021). https://doi.org/10.1016/j.cirpj.2021.02.005
Rajesh, N., Lokanadham, R.: Optimization of machining parameters & studies on characteristics of Monel k400 alloy using abrasive water jet Machining using ANFIS. Mater. Today: Proc. 98, 40–46 (2024). https://doi.org/10.1016/j.matpr.2023.08.376
Zhuang, K., Wan, L., Weng, J., Wu, Z., Zhang, Y., Tian, C., Yang, Y.: A new elastic abrasive jet machining method for post–treatment of tool coatings: a case study on TiAlN coated tools for titanium machining. Tribol. Int. 185(108533), 108533 (2023). https://doi.org/10.1016/j.triboint.2023.108533
Llanto, J.M., Vafadar, A., Aamir, M., Tolouei-Rad, M.: Analysis and optimization of process parameters in abrasive waterjet contour cutting of AISI 304L. Metals 11(9), 1362 (2021). https://doi.org/10.3390/met11091362
Vijayakumar, S., Satheesh Kumar, P.S., Sampathkumar, P., Manickam, S., Ramaiah, G.B., Pydi, H.P.: The effect of stir-squeeze casting process parameters on mechanical property and density of aluminum matrix composite. In: Khan, M.A. (ed.) Advances in Materials Science and Engineering, vol. 2022, pp. 1–10. Hindawi Limited (2022). https://doi.org/10.1155/2022/3741718
Gugulothu, B., Bharadwaja, K., Vijayakumar, S., Rao, T.V.J., Sri, M.N.S., Anusha, P., Agrawal, M.K.: Modeling and parametric optimization of electrical discharge machining on casted composite using central composite design. Int. J. Interact. Des. Manuf. (IJIDeM) (2023). https://doi.org/10.1007/s12008-023-01323-7
Karumuri, S., Haldar, B., Pradeep, A., Karanam, S.A.K., Sri, M.N.S., Anusha, P., …, Vijayakumar, S.: Multi-objective optimization using Taguchi based grey relational analysis in friction stir welding for dissimilar aluminium alloy. Int. J. Interact. Des. Manuf. (IJIDeM). (2023). https://doi.org/10.1007/s12008-023-01529-9
Sundararaj, J., et al.: Grey-Taguchi approach for optimizing FSW parameters in joining AA6262 and AA5083 alloys. Warasan Khana Witthayasat Maha Witthayalai Chiang Mai 51(1), 1–16 (2024)
Author information
Authors and Affiliations
Contributions
Author's contribution: S. Sathees kumar ,s vijayakumar & M. Naga Swapna Sri- Data collection, litrature survey, design of experiments and figures prepartion I. J. Isaac Premkum & R. Muthalagu- experimnetal setup , manuscript preparing based on the data and optimization works(ANOVA,SN ratio)
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Sathees Kumar, S., Isaac Premkumar, I.J., Muthalagu, R. et al. Examination of Abrasive water jet machining for Al hybrid composites using RSM-Central composite design. Interactions 245, 220 (2024). https://doi.org/10.1007/s10751-024-02056-z
Accepted:
Published:
DOI: https://doi.org/10.1007/s10751-024-02056-z