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A Technical review on Investigation Of Cutting Conditions On Tool Life And Material Removal Rate In Turning Of T51620 Using Cermet And Tungsten Carbide Insert

Dr. Pratik Kikani, Dilip Chauhan

Abstract


The performance of turning operation is depend upon the tool life and MRR of the tool material T51620 material is employed in making of dies in different industry. Tungsten carbide is most suitable insert material used for turning of T51620 .but now days industries need higher productivity and includes higher tool life and higher MRR with same parameters so one should compare the tool material with the advance one cermet insert material is the combination of ceramic and metal material. It fulfills the both the requirement of tool life and MRR so the current investigation is to experimental comparison of tungsten carbide and cermet insert for the turning of T51620 material based on the literature.


Keywords


tungsten carbide, Cermet,MRR

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References


Gupta, A., Singh, H., & Aggarwal, A. (2011). Taguchi-fuzzy multi output optimization (MOO) in high speed CNC turning of AISI P-20 tool steel. Expert Systems with Applications, 38(6), 6822-6828.

Badaruddin, M., Riza, R. T., & Zulhanif. (2018, July). The effect of diffusion treatment on the mechanical properties of hot-dip aluminum coating on AISI P20 steel. In AIP Conference Proceedings (Vol. 1983, No. 1, p. 050004). AIP Publishing LLC.

Gamage, J. R., DeSilva, A. K., Harrison, C. S., & Harrison, D. K. (2016). Process level environmental performance of electrodischarge machining of aluminium (3003) and steel (AISI P20). Journal of Cleaner Production, 137, 291-299.

Tlhabadira, I., Daniyan, I. A., Machaka, R., Machio, C., Masu, L., & VanStaden, L. R. (2019). Modelling and optimization of surface roughness during AISI P20 milling process using Taguchi method. The International Journal of Advanced Manufacturing Technology, 102(9), 3707-3718.

Thamizhmanii, S., Saparudin, S., & Hasan, S. (2007). Analyses of surface roughness by turning process using Taguchi method. Journal of achievements in materials and manufacturing engineering, 20(1-2), 503-506.

Mukkoti, V. V., Mohanty, C. P., Gandla, S., & Sarkar, P. (2020). Optimization of process parameters in CNC milling of P20 steel by cryo-treated tungsten carbide tools using NSGA-II. Production & Manufacturing Research, 8(1), 291-312.

Rathod, N. J., Chopra, M. K., Vidhate, U. S., & Saindane, U. V. (2021). Multi objective optimization in turning operation of SS304 sheet metal component. Materials Today: Proceedings, 47, 5806-5811.

Kumar, R., Bilga, P. S., & Singh, S. (2017). Multi objective optimization using different methods of assigning weights to energy consumption responses, surface roughness and material removal rate during rough turning operation. Journal of cleaner production, 164, 45-57.

Jagatheesan, K., Babu, K., & Madhesh, D. (2021). Experimental investigation of machining parameter in MQL turning operation using AISI 4320 alloy steel. Materials Today: Proceedings, 46, 4331-4335.

Gürgen, S., & Sofuoğlu, M. A. (2020). Integration of shear thickening fluid into cutting tools for improved turning operations. Journal of Manufacturing Processes, 56, 1146-1154.

Bharilya, R. K., Malgaya, R., Patidar, L., Gurjar, R. K., & Jha, A. K. (2015). Study of optimised process parameters in turning operation through force dynamometer on CNC machine. Materials Today: Proceedings, 2(4-5), 2300-2305.

Lu, C., Gao, L., Li, X., & Chen, P. (2016). Energy-efficient multi-pass turning operation using multi-objective backtracking search algorithm. Journal of Cleaner Production, 137, 1516-1531.

Valera, H. Y., & Bhavsar, S. N. (2014). Experimental investigation of surface roughness and power consumption in turning operation of EN 31 alloy steel. Procedia Technology, 14, 528-534.

Wang, Y. C., Chiu, Y. C., & Hung, Y. P. (2011). Optimization of multi-task turning operations under minimal tool waste consideration. Robotics and Computer-Integrated Manufacturing, 27(4), 674-680.

Belloufi, A., Assas, M., & Rezgui, I. (2013). Optimization of turning operations by using a hybrid genetic algorithm with sequential quadratic programming. Journal of applied research and technology, 11(1), 88-94.

López-Gálvez, H., & Soldani, X. (2020). Determination of optimum numerical parameters in a 3D model of finish turning operation applied to Inconel 718. Simulation Modelling Practice and Theory, 99, 102035.

Daniyan, I. A., Tlhabadira, I., Daramola, O. O., &Mpofu, K. (2019). Design and optimization of machining parameters for effective AISI P20 removal rate during milling operation. Procedia CIRP, 84, 861-867.

Phang, Y. M., Asmelash, M., Hamedon, Z., & Azhari, A. (2021). Investigation on turning operation using die sinking EDM process. Materials Today: Proceedings, 46, 1569-1573.

Kumar, S. L. (2019). Measurement and uncertainty analysis of surface roughness and material removal rate in micro turning operation and process parameters optimization. Measurement, 140, 538-547.

Kumari, S., Kumar, A., Yadav, R. K., & Vivekananda, K. (2018). Optimisation of machining parameters using grey relation analysis integrated with harmony search for turning of aisi d2 steel. Materials Today: Proceedings, 5(5), 12750-12756.

Khan, S. A., Anwar, S., Ishfaq, K., Afzal, M. Z., Ahmad, S., & Saleh, M. (2020). Wear performance of modified inserts in hard turning of AISI D2 steel: A concept of one-step sustainable machining. Journal of Manufacturing Processes, 60, 457-469.

Fernando, W. L. R., Karunathilake, H. P., & Gamage, J. R. (2021). Strategies to reduce energy and metalworking fluid consumption for the sustainability of turning operation: A review. Cleaner Engineering and Technology, 3, 100100.

Vardhan, M. V., Mohanty, C. P., &Dhanraj, B. (2020, March). Experimental Study on Parameters of P-20 Steel in CNC milling machine. In Journal of Physics: Conference Series (Vol. 1495, No. 1, p. 012027). IOP Publishing.

Mikołajczyk, T., Nowicki, K., Bustillo, A., & Pimenov, D. Y. (2018). Predicting tool life in turning operations using neural networks and image processing. Mechanical systems and signal processing, 104, 503-513.

Rao, C. J., Sreeamulu, D., & Mathew, A. T. (2014). Analysis of tool life during turning operation by determining optimal process parameters. Procedia Engineering, 97, 241-250.

Bazaz, S. M., Lohtander, M., & Varis, J. (2020). The prediction method of tool life on small lot turning process–Development of Digital Twin for production. Procedia Manufacturing, 51, 288-295.

Katiyar, S., Jaiswal, M., Narain, R. P., Singh, S., & Shrivastava, Y. (2021). A short review on investigation and suppression of tool chatter in turning operation. Materials Today: Proceedings.

Mohan, E., Azaath, L. M., & Natarajan, U. (2021). Experiment study on damping characteristics of the turning tool holder materials. Materials Today: Proceedings, 37, 3713-3717.

Tatar, K., Sjöberg, S., & Andersson, N. (2020). Investigation of cutting conditions on tool life in shoulder milling of Ti6Al4V using PVD coated micro-grain carbide insert based on design of experiments. Heliyon, 6(6), e04217.

Chen, J., Liu, W., Deng, X., & Wu, S. (2016). Tool life and wear mechanism of WC–5TiC–0.5 VC–8Co cemented carbides inserts when machining HT250 gray cast iron. Ceramics international, 42(8), 10037-10044

Husein, N. F., & Razak, N. H. (2022). Tool deterioration of 316 stainless steel in dry down-milling using carbide insert. Materials Today: Proceedings, 48, 911-915.

Palanisamy, D., Devaraju, A., Manikandan, N., & Arulkirubakaran, D. (2020). Performance evaluation of cryo-treated tungsten carbide inserts in machining PH stainless steel. Materials Today: Proceedings, 22, 487-491.

Ee, K. C., Li, P. X., Balaji, A. K., Jawahir, I. S., & Stevenson, R. (2006). Performance-based predictive models and optimization methods for turning operations and applications: part 1—tool wear/tool life in turning with coated grooved tools. Journal of Manufacturing Processes, 8(1), 54-66.




DOI: https://doi.org/10.37591/tmet.v12i3.6776

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