Abstract
The prime objective of the current study is to illustrate not only the tribomechanical properties of hardfaced deposit but also the parametric study, modelling and optimisation of cutting performance of the Ni-based hardfaced turning tool insert. The modern manufacturing industry emphasises high productivity, precise dimensional accuracy and superior surface finish. Therefore, biological evolution-based multi-objective particle swarm optimisation (MOPSO) and the technique for order of preference by similarity to the ideal solution (TOPSIS) have been coupled to develop a hybrid optimisation technique for high machining efficiency and good surface finish. The input variables have been selected as speed, feed, and depth of cut for machining C30 steel using hardfaced cutting tool insert. Speed has been observed as the most significant factor followed by depth of cut for material removal rate. However, feed, depth of cut and speed contribute 39.34%, 20.05% and 19.34%, respectively in the overall inconsistency in surface roughness. The MOPSO-TOPSIS hybrid approach has provided the ideal machining condition at the combination of 415 rpm speed, 0.06 mm/rev feed and 0.5 mm depth of cut with marginal error of 2.496% and 3.352%, for material removal rate and surface roughness, respectively. The suggested hybrid optimisation yielded a maximum material removal rate of 2139.084 mm3/min and a minimum surface roughness of 2.713 µm. On the other hand, the overall hardness of hardfaced deposit was detected 1914.532 Hv. Moreover, adhesive strength and coefficient of friction of Ni-based deposit were observed as 3.981 N and 0.197, respectively.
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Sinha, M.K., Pal, A., Kishore, K., Singh, A., Sansanwal, H., Sharma, P.: Applications of sustainable techniques in machinability improvement of superalloys: a comprehensive review. Int. J. Interact. Des. Manufact. (IJIDeM) 17, 1–26 (2022)
Bijanzad, A., Munir, T., Abdulhamid, F.: Heat-assisted machining of superalloys: a review. Int. J. Adv. Manuf. Technol. 1–27 (2021)
Li, B., Zhang, S., Du, J., Sun, Y.: State-of-the-art in cutting performance and surface integrity considering tool edge micro-geometry in metal cutting process. J. Manuf. Process. 77, 380–411 (2022)
Tan, L., Yao, C., Li, X., Fan, Y., Cui, M.: Effects of machining parameters on surface integrity when turning Inconel 718. J. Mater. Eng. Perform. 31(5), 4176–4186 (2022)
Niemczewska-Wójcik, M.: The influence of the surface geometric structure on the functionality of implants. Wear 271(3–4), 596–603 (2011)
Leksycki, K., Feldshtein, E., Królczyk, G.M., Legutko, S.: On the chip shaping and surface topography when finish cutting 17–4 PH precipitation-hardening stainless steel under near-dry cutting conditions. Materials 13(9), 2188 (2020)
Orak, S., Arapoğlu, R.A., Sofuoğlu, M.A.: Development of an ANN-based decision-making method for determining optimum parameters in turning operation. Soft Comput. 22, 6157–6170 (2018)
Dash, L., Padhan, S., Das, S.R.: Experimental investigations on surface integrity and chip morphology in hard tuning of AISI D3 steel under sustainable nanofluid-based minimum quantity lubrication. J. Braz. Soc. Mech. Sci. Eng. 42, 1–25 (2020)
Bag, R., Panda, A., Sahoo, A.K., Kumar, R.: Sustainable high-speed hard machining of AISI 4340 steel under dry environment. Arab. J. Sci. Eng. 48, 1–24 (2022)
Karnan, B., Kuppusamy, A., Latchoumi, T.P., Banerjee, A., Sinha, A., Biswas, A., Subramanian, A.K.: Multi-response optimization of turning parameters for cryogenically treated and tempered WC–Co inserts. J. Inst. Eng. India Ser. D. 103(1), 263–274 (2022)
Goyal, A., Kothari, B., Pathak, V.K.: Fuzzy logic and desirability based models for predicting performance characteristics of varying concentration graphite nanoplatelets (GNPs) mixed nanofluid MQL in turning of AISI-1045 steel. Int. J. Interact. Des. Manufact. (IJIDeM) 16(4), 1559–1584 (2022)
Sivaiah, P., Chakradhar, D.: Performance improvement of cryogenic turning process during machining of 17–4 PH stainless steel using multi objective optimization techniques. Measurement 136, 326–336 (2019)
Rathod, N.J., Chopra, M.K., Shelke, S.N., Chaurasiya, P.K., Kumar, R., Saxena, K.K., Prakash, C.: Investigations on hard turning using SS304 sheet metal component grey based Taguchi and regression methodology. Int. J. Interact. Des. Manufact. (IJIDeM) (2023). https://doi.org/10.1007/s12008-023-01244-5
Leksycki, K., Królczyk, J.B.: Comparative assessment of the surface topography for different optical profilometry techniques after dry turning of Ti6Al4V titanium alloy. Measurement 169, 108378 (2021)
Niemczewska-Wójcik, M., Madej, M., Kowalczyk, J., Piotrowska, K.: A comparative study of the surface topography in dry and wet turning using the confocal and interferometric modes. Measurement 204, 112144 (2022)
Buddaraju, K.M., Sastry, G.R.K., Kosaraju, S.: Grey-Taguchi optimization of machining of Inconel 600 using AlTiN coated carbide inserts under dry environmental conditions. Int. J. Interact. Des. Manufact. (IJIDeM) (2022). https://doi.org/10.1007/s12008-022-01038-1
Dhar, N.R., Paul, S., Chattopadhyay, A.B.: The influence of cryogenic cooling on tool wear, dimensional accuracy and surface finish in turning AISI 1040 and E4340C steels. Wear 249(10–11), 932–942 (2001)
Diniz, A.E., Micaroni, R.: Cutting conditions for finish turning process aiming: the use of dry cutting. Int. J. Mach. Tools Manuf. 42(8), 899–904 (2002)
Adler, D.P., Hii, W.S., Michalek, D.J., Sutherland, J.W.: Examining the role of cutting fluids in machining and efforts to address associated environmental/health concerns. Mach. Sci. Technol. 10(1), 23–58 (2006)
Musavi, S.H., Davoodi, B.: Risk assessment for hazardous lubricants in machining industry. Environ. Sci. Pollut. Res. 28, 625–634 (2021)
Park, R.M.: Risk assessment for metalworking fluids and cancer outcomes. Am. J. Ind. Med. 61(3), 198–203 (2018)
Haider, J., Hashmi, M.S.J.: 8.02—Health and environmental impacts in metal machining processes. Comprehens. Mater. Process. 8, 7–33 (2014)
Deenadayalan, K., Murali, V., Elayaperumal, A., Arulvel, S., Asl, M.S.: Friction and wear properties of short time heat-treated and laser surface re-melted NiCr-WC composite coatings at various dry sliding conditions. J. Mater. Res. Technol. 17, 3080–3104 (2022)
Reinaldo, P.R., D’Oliveira, A.S.C.M.: NiCrSiB coatings deposited by plasma transferred arc on different steel substrates. J. Mater. Eng. Perform. 22, 590–597 (2013)
Farahmand, P., Kovacevic, R.: Corrosion and wear behavior of laser cladded Ni–WC coatings. Surf. Coat. Technol. 276, 121–135 (2015)
Azzoug, R., Mebdoua, Y., Hellal, F., Marra, F.: Analysis of microstructure, mechanical indentation and corrosive behavior of a thermally sprayed NiFeCrBSi-WC composite coating. J. Alloys Compd. 900, 163505 (2022)
Kashani, H., Amadeh, A., Ghasemi, H.M.: Room and high temperature wear behaviors of nickel and cobalt base weld overlay coatings on hot forging dies. Wear 262(7–8), 800–806 (2007)
Bhosale, D.G., Rathod, W.S.: Tribological behaviour of atmospheric plasma and high velocity oxy-fuel sprayed WC-Cr3C2-Ni coatings at elevated temperatures. Ceram. Int. 46(8), 12373–12385 (2020)
Gudala, S., Ramesh, M.R., Srinath, M.S.: Microstructure and wear behavior of self-lubricating microwave clads deposited on titanium alloy. J. Mater. Eng. Perform. 31(11), 8864–8877 (2022)
Bhattacharya, A., Das, S., Majumder, P., Batish, A.: Estimating the effect of cutting parameters on surface finish and power consumption during high speed machining of AISI 1045 steel using Taguchi design and ANOVA. Prod. Eng. 3, 31–40 (2009)
Jhodkar, D., Amarnath, M., Chelladurai, H., Ramkumar, J.: Performance assessment of microwave treated WC insert while turning AISI 1040 steel. J. Mech. Sci. Technol. 32, 2551–2558 (2018)
Dhar, N.R., Islam, S., Kamruzzaman, M., Paul, S.: Wear behavior of uncoated carbide inserts under dry, wet and cryogenic cooling conditions in turning C-60 steel. J. Braz. Soc. Mech. Sci. Eng. 28, 146–152 (2006)
Kumar, V., Mondal, S.C.: Cutting performance of Ni-W-Cr-B-Si hardfaced turning tool insert. SILICON 14(8), 4035–4044 (2022)
Abbas, A.T., Al-Abduljabbar, A.A., El Rayes, M.M., Benyahia, F., Abdelgaliel, I.H., Elkaseer, A.: Multi-objective optimization of performance indicators in turning of AISI 1045 under dry cutting conditions. Metals 13(1), 96 (2023)
Sidhu, A.S., Singh, S., Kumar, R., Pimenov, D.Y., Giasin, K.: Prioritizing energy-intensive machining operations and gauging the influence of electric parameters: an industrial case study. Energies 14(16), 4761 (2021)
Paturi, U.M.R., Yash, A., Palakurthy, S.T., Reddy, N.S.: Modeling and optimization of machining parameters for minimizing surface roughness and tool wear during AISI 52100 steel dry turning. Mater. Today Proc. 50, 1164–1172 (2022)
Jhodkar, D., Amarnath, M., Chelladurai, H., Ramkumar, J.: Experimental investigations to study the effects of microwave treatment strategy on tool performance in turning operation. J. Mater. Eng. Perform. 27, 6374–6388 (2018)
Nouioua, M., Yallese, M.A., Khettabi, R., Belhadi, S., Bouhalais, M.L., Girardin, F.: Investigation of the performance of the MQL, dry, and wet turning by response surface methodology (RSM) and artificial neural network (ANN). Int. J. Adv. Manuf. Technol. 93(5–8), 2485–2504 (2017)
Hamadi, B., Yallese, M.A., Boulanouar, L., Hammoudi, A., Nouioua, M.: Evaluation of the cutting performance of PVD, CVD and MTCVD carbide inserts in dry turning of AISI 4140 steel using RSM-based NAMDE optimization. J. Braz. Soc. Mech. Sci. Eng. 44(8), 342 (2022)
Garcia, R.F., Feix, E.C., Mendel, H.T., Gonzalez, A.R., Souza, A.J.: Optimization of cutting parameters for finish turning of 6082–T6 aluminum alloy under dry and RQL conditions. J. Braz. Soc. Mech. Sci. Eng. 41, 1–10 (2019)
Das, A., Tirkey, N., Patel, S.K., Das, S.R., Biswal, B.B.: A comparison of machinability in hard turning of EN-24 alloy steel under mist cooled and dry cutting environments with a coated cermet tool. J. Fail. Anal. Prev. 19, 115–130 (2019)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In Proceedings of ICNN'95-International Conference on Neural Networks, 4, 1942–1948 (1995).https://doi.org/10.1109/ICNN.1995.488968
Mandal, P., Mondal, S.C.: Multi-objective optimization of Cu-MWCNT composite electrode in electro discharge machining using MOPSO-TOPSIS. Measurement 169, 108347 (2021)
Cui, Y., Meng, X., Qiao, J.: A multi-objective particle swarm optimization algorithm based on two-archive mechanism. Appl. Soft Comput. 119, 108532 (2022)
Acharjee, P., Goswami, S. K.: Chaotic particle swarm optimization based reliable algorithm to overcome the limitations of conventional power flow methods. In IEEE/PES Power Systems Conference and Exposition PSCE. 1–7 (2009). https://doi.org/10.1109/PSCE.2009.4839945
Agrawal, A., Tripathi, S.: Particle swarm optimization with adaptive inertia weight based on cumulative binomial probability. Evol. Intell. 14, 305–313 (2021)
Reyes-Sierra, M., Coello, C.C.: Multi-objective particle swarm optimizers: a survey of the state-of-the-art. Int. J. Comput. Intell. Res. 2(3), 287–308 (2006)
Hwang, C.L., Yoon, K.: Multiple attribute decision making methods and applications: a state-of-the-art survey. In: Beckmann, M.; Kunzi, H.P. (eds.) Lecture Notes in Economics and Mathematical Systems, No. 186, Springer-Verlag, Berlin (1981). https://doi.org/10.1007/978-3-642-48318-9
Ramesh, S., Viswanathan, R., Ambika, S.: Measurement and optimization of surface roughness and tool wear via grey relational analysis TOPSIS and RSA techniques. Measurement 78, 63–72 (2016)
Behzadian, M., Otaghsara, S.K., Yazdani, M., Ignatius, J.: A state-of the-art survey of TOPSIS applications. Expert Syst. Appl. 39(17), 13051–13069 (2012)
Padmini, R., Krishna, P.V., Rao, G.K.M.: Effectiveness of vegetable oil based nanofluids as potential cutting fluids in turning AISI 1040 steel. Tribol. Int. 94, 490–501 (2016)
Cheng, Y., Wang, Y., Lin, J., Xu, S., Zhang, P.: Research status of the influence of machining processes and surface modification technology on the surface integrity of bearing steel materials. Int. J. Adv. Manuf. Technol. 125, 2897–2923 (2023)
He, H.B., Li, H.Y., Zhang, X.Y., Yue, Q.B., Zhang, J., Ma, L., Li, Y.M.: Research on the cutting performances and wear mechanisms of TiAlCrN coated tools during dry turning. Int. J. Precis. Eng. Manuf. 20, 201–207 (2019)
Tomac, N., Tønnessen, K., Rasch, F.O., Mikac, T.: A study of factors that affect the build-up material formation. In AMST’05 Advanced Manufacturing Systems and Technology: Proceedings of the Seventh International Conference. pp. 183–192 (2005). https://doi.org/10.1007/3-211-38053-1_17
Boyd, J.M., Veldhuis, S.C.: Manifestations of reduced tool-chip friction during turning of AISI 1045 steel with PVD-coated carbide inserts. Int. J. Adv. Manuf. Technol. 91, 687–698 (2017)
Robati, A., Barani, G.A., Pour, H.N.A., Fadaee, M.J., Anaraki, J.R.P.: Balanced fuzzy particle swarm optimization. Appl. Math. Model. 36(5), 2169–2177 (2012)
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Kumar, V., Mondal, S.C. Tribomechanical investigation and parametric optimisation of the cutting performance of Ni-based hardfaced turning tool insert. Int J Interact Des Manuf 18, 217–238 (2024). https://doi.org/10.1007/s12008-023-01464-9
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DOI: https://doi.org/10.1007/s12008-023-01464-9