OBRABOTKAMETALLOV Vol. 23 No. 4 2021 63 EQUIPMENT. INSTRUMENTS References 1. Grzesik W. Experimental investigation of the cutting temperature when turning with coated indexable inserts. International Journal of Machine Tools and Manufacture , 1999, vol. 39, iss. 3, pp. 355–369. DOI: 10.1016/S08906955(98)00044-3. 2. Grzesik W. The role of coatings in controlling the cutting process when turning with coated indexable inserts. Journal of Materials Processing Technology , 1998, vol. 79, iss. 1–3, pp. 133–143. DOI: 10.1016/S0924-0136(97)00491-3. Dimensional analysis and ANN simulation of chip-tool interface temperature during turning SS304 Atul Kulkarni 1, a , Satish Chinchanikar 1, b, * , Vikas Sargade 2, c 1Vishwakarma Institute of Information Technology, Survey No. 3/4, Kondhwa (Budruk), Pune - 411048, Maharashtra, India 2Dr. Babasaheb Ambedkar Technological University, Vidyavihar, Lonere, Dist. Raigad - 402103, Maharashtra, India a https://orcid.org/0000-0002-6452-6349, atul.kulkarni@viit.ac.in, b https://orcid.org/0000-0002-4175-3098, satish.chinchanikar@viit.ac.in, c https://orcid.org/0000-0001-8855-112X, vgsargade@dbatu.ac.in Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science. 2021 vol. 23 no. 4 pp. 47–64 ISSN: 1994-6309 (print) / 2541-819X (online) DOI: 10.17212/1994-6309-2021-23.4-47-64 Obrabotka metallov - Metal Working and Material Science Journal homepage: http://journals.nstu.ru/obrabotka_metallov ARTICLE INFO Article history : Received: 29 July 2021 Revised: 19 August 2021 Accepted: 07 September 2021 Available online: 15 December 2021 Keywords : Chip-tool interface temperature Dimensional analysis Artificial neural network Coated tools SS304 ABSTRACT Introduction. During machining, the resulting temperature has a wider and more critical impact on machining performance. During machining, the power consumption is mainly converted into heat near the cutting edge of the tool. Almost all the work performed during plastic deformation turns into heat. Researchers have put a lot of effort into measuring the cutting temperature during machining, as it significantly affects tool life and overall machining performance. The purpose of the work: to investigate the temperature of the chip-tool interface, taking into account the influence of cutting parameters and the type of tool coating during SS304turning. The chip-tool interface temperature is measured by changing the cutting speed and feed with a constant cutting depth for uncoated and PVDsingle-layer TiAlNand multi-layer TiN / TiAlNcoated carbide tools. In addition, an attempt is made to develop a model for predicting the temperature of the chip-tool interface using dimensional analysis and ANN simulating to better understand the process. The methods of investigation. Experiments are carried out with varying the cutting speed (140-260 m/min), feed (0.08-0.2 mm/rev) and a constant cutting depth of 1 mm. The chip-tool interface temperature is measured using the tool-work thermocouple principle. The Calibration Setup is designed to establish the relationship between the produced electromotive force ( EMF ) and the cutting temperature during machining. Statistical dimensional analysis and artificial neural network models have been developed to predict the temperature of the chip-tool interface. Tangential cutting force and chip attributes such as chip width and thickness are also measured depending on the cutting conditions, which is a prerequisite for dimensional analysis simulation. Results and Discussion. A tool made of TiAlNcarbide withPVDcoating had a lower temperature at the chip-tool interface than a tool withTiN / TiAlNcoating. It has been observed that the chip-tool interface temperature increases prominently with the cutting speed, followed by the chip cross-sectional area and the specific cutting pressure. However, a lower cutting force was observed when using a carbide tool with a multi-layerTiN / TiAlNcoating, which can be attributed to a lower coefficient of friction created by the front surface of this tool forflowing chips. On the other hand, the greatest cutting force was observed in uncoated carbide tools. It was noticed that the developed models allow predicting the temperature of the chip-tool interface with an absolute error of 5%. However, the lowest average absolute error of 0.78% was observed with theANNmodel and, therefore, can be reliably used to predict the chip-tool interface temperature duringSS304turning. For citation: Kulkarni A.P., Chinchanikar S., Sargade V.G. Dimensional analysis and ANN simulation of chip-tool interface temperature during turning SS304. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science , 2021, vol. 23, no. 4, pp. 47–64. DOI: 10.17212/1994-6309-2021-23.4-47-64. (In Russian). ______ * Corresponding author Chinchanikar Satish , Ph.D. (Engineering), Professor Vishwakarma Institute of Information Technology, Pune, Maharashtra, India Tel.: 91-2026950441, e-mail: satish.chinchanikar@viit.ac.in
RkJQdWJsaXNoZXIy MTk0ODM1