Vol. 25 No. 4 2023 3 EDITORIAL COUNCIL EDITORIAL BOARD EDITOR-IN-CHIEF: Anatoliy A. Bataev, D.Sc. (Engineering), Professor, Rector, Novosibirsk State Technical University, Novosibirsk, Russian Federation DEPUTIES EDITOR-IN-CHIEF: Vladimir V. Ivancivsky, D.Sc. (Engineering), Associate Professor, Department of Industrial Machinery Design, Novosibirsk State Technical University, Novosibirsk, Russian Federation Vadim Y. Skeeba, Ph.D. (Engineering), Associate Professor, Department of Industrial Machinery Design, Novosibirsk State Technical University, Novosibirsk, Russian Federation Editor of the English translation: Elena A. Lozhkina, Ph.D. (Engineering), Department of Material Science in Mechanical Engineering, Novosibirsk State Technical University, Novosibirsk, Russian Federation The journal is issued since 1999 Publication frequency – 4 numbers a year Data on the journal are published in «Ulrich's Periodical Directory» Journal “Obrabotka Metallov” (“Metal Working and Material Science”) has been Indexed in Clarivate Analytics Services. Novosibirsk State Technical University, Prospekt K. Marksa, 20, Novosibirsk, 630073, Russia Tel.: +7 (383) 346-17-75 http://journals.nstu.ru/obrabotka_metallov E-mail: metal_working@mail.ru; metal_working@corp.nstu.ru Journal “Obrabotka Metallov – Metal Working and Material Science” is indexed in the world's largest abstracting bibliographic and scientometric databases Web of Science and Scopus. Journal “Obrabotka Metallov” (“Metal Working & Material Science”) has entered into an electronic licensing relationship with EBSCO Publishing, the world's leading aggregator of full text journals, magazines and eBooks. The full text of JOURNAL can be found in the EBSCOhost™ databases.
OBRABOTKAMETALLOV Vol. 25 No. 4 2023 4 EDITORIAL COUNCIL EDITORIAL COUNCIL CHAIRMAN: Nikolai V. Pustovoy, D.Sc. (Engineering), Professor, President, Novosibirsk State Technical University, Novosibirsk, Russian Federation MEMBERS: The Federative Republic of Brazil: Alberto Moreira Jorge Junior, Dr.-Ing., Full Professor; Federal University of São Carlos, São Carlos The Federal Republic of Germany: Moniko Greif, Dr.-Ing., Professor, Hochschule RheinMain University of Applied Sciences, Russelsheim Florian Nürnberger, Dr.-Ing., Chief Engineer and Head of the Department “Technology of Materials”, Leibniz Universität Hannover, Garbsen; Thomas Hassel, Dr.-Ing., Head of Underwater Technology Center Hanover, Leibniz Universität Hannover, Garbsen The Spain: Andrey L. Chuvilin, Ph.D. (Physics and Mathematics), Ikerbasque Research Professor, Head of Electron Microscopy Laboratory “CIC nanoGUNE”, San Sebastian The Republic of Belarus: Fyodor I. Panteleenko, D.Sc. (Engineering), Professor, First Vice-Rector, Corresponding Member of National Academy of Sciences of Belarus, Belarusian National Technical University, Minsk The Ukraine: Sergiy V. Kovalevskyy, D.Sc. (Engineering), Professor, Vice Rector for Research and Academic Aff airs, Donbass State Engineering Academy, Kramatorsk The Russian Federation: Vladimir G. Atapin, D.Sc. (Engineering), Professor, Novosibirsk State Technical University, Novosibirsk; Victor P. Balkov, Deputy general director, Research and Development Tooling Institute “VNIIINSTRUMENT”, Moscow; Vladimir A. Bataev, D.Sc. (Engineering), Professor, Novosibirsk State Technical University, Novosibirsk; Vladimir G. Burov, D.Sc. (Engineering), Professor, Novosibirsk State Technical University, Novosibirsk; Aleksandr N. Korotkov, D.Sc. (Engineering), Professor, Kuzbass State Technical University, Kemerovo; Dmitry V. Lobanov, D.Sc. (Engineering), Associate Professor, I.N. Ulianov Chuvash State University, Cheboksary; Aleksey V. Makarov, D.Sc. (Engineering), Corresponding Member of RAS, Head of division, Head of laboratory (Laboratory of Mechanical Properties) M.N. Miheev Institute of Metal Physics, Russian Academy of Sciences (Ural Branch), Yekaterinburg; Aleksandr G. Ovcharenko, D.Sc. (Engineering), Professor, Biysk Technological Institute, Biysk; Yuriy N. Saraev, D.Sc. (Engineering), Professor, Institute of Strength Physics and Materials Science, Russian Academy of Sciences (Siberian Branch), Tomsk; Alexander S. Yanyushkin, D.Sc. (Engineering), Professor, I.N. Ulianov Chuvash State University, Cheboksary
Vol. 25 No. 4 2023 5 CONTENTS OBRABOTKAMETALLOV TECHNOLOGY Akintseva A.V., Pereverzev P.P. Modeling the interrelation of the cutting force with the cutting depth and the volumes of the metal being removed by single grains in fl at grinding........................................................................................................................................ 6 Sharma S.S., Joshi A., Rajpoot Y.S. A systematic review of processing techniques for cellular metallic foam production................. 22 Karlina Yu.I., Kononenko R.V., Ivantsivsky V.V., Popov M.A., Deryugin F.F., Byankin V.E. Review of modern requirements for welding of pipe high-strength low-alloy steels.......................................................................................................................................... 36 Startsev E.A., Bakhmatov P.V. The infl uence of automatic arc welding modes on the geometric parameters of the seam of butt joints made of low-carbon steel, made using experimental fl ux......................................................................................................................... 61 Martyushev N.V., Kozlov V.N., Qi M., Baginskiy A.G., Han Z., Bovkun A.S. Milling martensitic steel blanks obtained using additive technologies................................................................................................................................................................................ 74 Loginov Yu.N., Zamaraeva Yu.V. Evaluation of the bars’ multichannel angular pressing scheme and its potential application in practice................................................................................................................................................................................................... 90 EQUIPMENT. INSTRUMENTS Rajpoot Y.S., SharmaA.K., Mishra V.N., Saxena K., Deepak D., Sharma S.S. Eff ect of tool pin profi le on the tensile characteristics of friction stir welded joints of AA8011.................................................................................................................................................... 105 Chinchanikar S., Gadge M.G. Performance modeling and multi-objective optimization during turning AISI 304 stainless steel using coated and coated-microblasted tools........................................................................................................................................................ 117 Ghule G.S., Sanap S., Chinchanikar S. Ultrasonic vibration-assisted hard turning of AISI 52100 steel: comparative evaluation and modeling using dimensional analysis........................................................................................................................................................ 136 Pivkin P.M., Ershov A.A., Mironov N.E., Nadykto A.B. Infl uence of the shape of the toroidal fl ank surface on the cutting wedge angles and mechanical stresses along the drill cutting edge...................................................................................................................... 151 MATERIAL SCIENCE Sokolov R.A., Muratov K.R., Venediktov A.N., Mamadaliev R.A. Infl uence of internal stresses on the intensity of corrosion processes in structural steel....................................................................................................................................................................... 167 Klimenov V.A., Kolubaev E.A., Han Z., Chumaevskii A.V., Dvilis E.S., Strelkova I.L., Drobyaz E.A., Yaremenko O.B., Kuranov A.E. Elastic modulus and hardness of Ti alloy obtained by wire-feed electron-beam additive manufacturing................... 180 Vorontsov A.V., Filippov A.V., Shamarin N.N., Moskvichev E.N., Novitskaya O.S., Knyazhev E.O., Denisova Yu.A., Leonov A.A., Denisov V.V. In situ crystal lattice analysis of nitride single-component and multilayer ZrN/CrN coatings in the process of thermal cycling.......................................................................................................................................................................................... 202 Rubtsov V.E., Panfi lov A.O., Kniazhev E.O., Nikolaeva A.V., Cheremnov A.M., Gusarova A.V., Beloborodov V.A., Chumaevskii A.V., Grinenko A.V., Kolubaev E.A. Infl uence of high-energy impact during plasma cutting on the structure and properties of surface layers of aluminum and titanium alloys................................................................................................................... 216 Bobylyov E.E., Storojenko I.D., Matorin A.A., Marchenko V.D. Features of the formation of Ni-Cr coatings obtained by diff usion alloying from low-melting liquid metal solutions..................................................................................................................................... 232 Burkov А.А., Konevtsov L.А., Dvornik М.И., Nikolenko S.V., Kulik M.A. Formation and investigation of the properties of FeWCrMoBC metallic glass coatings on carbon steel.......................................................................................................................... 244 Sharma S.S., Khatri R., Joshi A. A synergistic approach to the development of lightweight aluminium-based porous metallic foam using stir casting method........................................................................................................................................................................... 255 Strokach E.A., Kozhevnikov G.D., Pozhidaev A.A., Dobrovolsky S.V. Numerical study of titanium alloy high-velocity solid particle erosion.......................................................................................................................................................................................... 268 EDITORIALMATERIALS 284 FOUNDERS MATERIALS 295 CONTENTS
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 Performance modeling and multi-objective optimization during turning AISI 304 stainless steel using coated and coated-microblasted tools Satish Chinchanikar a, *, Mahendra Gadge b Vishwakarma Institute of Information Technology, Survey No. 3/4, Kondhwa (Budruk), Pune - 411039, Maharashtra, India a https://orcid.org/0000-0002-4175-3098, satish.chinchanikar@viit.ac.in; b https://orcid.org/0000-0002-8603-8653, Mahendra.gadge@viit.ac.in Obrabotka metallov - Metal Working and Material Science Journal homepage: http://journals.nstu.ru/obrabotka_metallov Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science. 2023 vol. 25 no. 4 pp. 117–135 ISSN: 1994-6309 (print) / 2541-819X (online) DOI: 10.17212/1994-6309-2023-25.4-117-135 ART I CLE I NFO Article history: Received: 15 August 2023 Revised: 05 September 2023 Accepted: 09 September 2023 Available online: 15 December 2023 Keywords: AISI 304 Cutting force Tool life Coated tools Surface roughness Multi-objective optimization ABSTRACT Introduction. High-speed machining of stainless steel has long been a focus of research. Due to characteristics such as low thermal conductivity and work hardening, AISI 304 is considered to be a difficult material to cut. Machinability indicators provide important information about the efficiency and effectiveness of the machining process, enabling manufacturers to optimize their operations for increased productivity and precision. The purpose of the work. Coated carbide tools are most often used for machining AISI 304 stainless steel. Few studies, meanwhile, have examined the effects of pre-and post-treated coated carbide tools when turning these alloys at high speeds. In addition, only a small number of studies have simultaneously optimized the cutting parameters while employing preand post-treated tools. The methods of investigation. The present work comparatively evaluates the performance of coated and coated-microblasted tools during the turning of AISI 304 stainless steel. The tools were PVD-AlTiN coated, PVD-AlTiN coated with microblasting as a post-treatment (coated-microblasted), and MTCVD-TiCN/Al2O3 coated (MTCVD). The experimental-based mathematical models were developed to predict and optimize the turning performance. Results and Discussion. In this study, it is found that PVD-AlTiN coated tools have the lowest cutting forces and surface roughness, followed by PVD-AlTiN coated-microblasted and MTCVD-TiCN/Al2O3 coated tools. However, there is no significant difference observed in these responses for coated and coated-microblasted tools. It is found that the cutting forces increased with feed and depth of cut while decreasing with cutting speed. However, this effect is significant for MTCVD-coated tools. On the other hand, higher tool life is observed with MTCVD-TiCN/ Al2O3 coated tools, followed by PVD AlTiN coated-microblasted and PVD-AlTiN coated tools. Tool life was largely affected by cutting speed. However, PVD-AlTiN coated tools exhibited this effect more noticeably. The models, with correlation coefficients found above 0.9, can be utilized to predict responses in turning AISI 304 stainless steel. The optimization study revealed that turning AISI 304 stainless steel with MTCVD-TiCN/Al2O3 coated tools incurs lower cutting forces of 18–27 N, produces a minimum surface roughness of 0.3–0.44 μm, and has a better tool life of 36–51 min compared to PVD-AlTiN coated (C) and PVD-AlTiN coated-microblasted (CMB) tools. For citation: Chinchanikar S., Gadge M.G. Performance modeling and multi-objective optimization during turning AISI 304 stainless steel using coated and coated-microblasted tools. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2023, vol. 25, no. 4, pp. 117–135. DOI: 10.17212/1994-6309-2023-25.4-117-135. (In Russian). ______ * Corresponding author Chinchanikar Satish, Ph.D. (Engineering), Professor Vishwakarma Institute of Information Technology, Pune - 411039, Maharashtra, India Tel.: +91-2026950441, e-mail: satish.chinchanikar@viit.ac.in Introduction High-speed machining of stainless steel has long been a focus of research. Due to characteristics such as low thermal conductivity and tendency to work hardening, AISI 304 steel is difficult to machine. One of the most stringent indicators of the efficiency and effectiveness of a machining process is tool life. He et al. [1] revealed that the cutting temperature of a TiN-coated tool is lower than that of an uncoated one and increases with increasing cutting parameters. Rao et al. [2] multi-objectively optimized material removal rate and roughness during turning of SS 304. Kulkarni et al. [3] observed that cutting speed significantly affects the chip-tool interface temperature, and feed greatly affects the cutting forces during turning of SS 304. According to Bouzid et al. [4], when turning of SS 304 with Ti(C,N)/Al2O3/TiN coated
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 tools, the cutting duration is the main factor influencing the flank wear, which was then followed by the cutting speed. A study by Sharma and Gupta [5] showed that TiAlN/TiN coated carbide tools significantly reduced tool wear and roughness during turning of SS 304. Patel et al. [6] observed that mechanical properties and machining performance are influenced by the microstructure of cermet tools. Dubovska et al. [7] conducted a tool life study of carbide tools when turning of AISI 304 austenitic stainless steel. Sharma et al. [8] carried turning of AISI 304 steel using hybrid nanofluids with minimal lubrication. Their study developed models for forces and surface roughness. Rao et al. [9] optimized the surface roughness using the Differential Evolution (DE) algorithm in turning SS 304. Chen et al. [10] turned SS 304 using CrWN hard film tools. Their study optimized performance using grey relational analysis (GRA). Patil et al. [11] evaluated cryogenically treated and untreated carbide cutting tools for turning AISI 304 steel. Lower surface roughness and tool wear was observed with cryogenically treated tools. In turning SS 304, Singh et al. [12] found that cutting speed was a dominant factor affecting surface roughness and depth of cut, and the cutting speed-feed rate interaction significantly affected flank wear. Lubis et al. [13] obtained tool life data and analyzed the tool wear of coated tools in turning AISI 304 stainless steel. Khan et al. [14] conducted a study on the impact of surface-treated and AlCrN-coated drills when drilling SS 304 at different cutting speeds. Bedi et al. [15] observed better results when processing SS 304 steel with rice bran oil than coconut oil. Rathod et al. [16] optimized turning of SS 304 with coated carbide tools using the Taguchi and TOPSIS methods. Sivaiah et al. [17] analyzed the performance of micro-grooved tools during turning AISI 304. Textured tools performed better compared to untextured tools. Moganapriya et al. [18] found improved performance with TiAlSiN coated tools during machining of SS 304. A group of researchers evaluated the chip-tool interface temperature during machining of SS 304 [19– 20]. Experimental findings showed a significant influence of cutting speed on the temperature generated during machining. Patel et al. [21] found that the tool life of Ti-based coated cermet tools is significantly influenced by the coating compositions. Özbek et al. [22] found that during AISI 304 wet turning, the feed rate has a substantial impact on tool wear and surface roughness. According to the analysis of the literature, coated tools have been mostly used by the researchers to machine AISI 304 stainless steel. Few researchers, meanwhile, have examined the effects of pre-and posttreated coated carbide tools when turning these alloys at high speeds. In addition, only a small number of studies have simultaneously optimized the cutting parameters for improved machining performance while employing pre-and post-treated tools. In light of this, this study compares and contrasts the effectiveness of coated and coated-microblasted tools when turning AISI 304 stainless steel. The machining capabilities of tools coated with single-layer PVD AlTiN, coated-microblasted, and multi-layer MTCVD TiCN/Al2O3 were assessed. To predict and improve turning performance, the experimentally validated models were developed. Experimental Design Turning experiments were carried out on AISI 304 stainless steel bar with a diameter and length of 70 and 500 mm, respectively. The material’s composition is shown in table 1. Fig. 1 depicts the high-precision CNC lathe used for the experiments. To investigate the machining performance under dry conditions, experiments were conducted using single-layer PVD AlTiN coated Ta b l e 1 Percentage composition of AISI 304 C Si Mn P S Cr Ni N Fe 0.033 0.88 1.98 0.037 0.013 18.37 8.82 0.11 Balance
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 (hereafter referred to as “coated”), single-layer PVD AlTiN coated and microblasted as a post-treatment (hereafter referred to as “coated-microblasted”), and multi-layer MTCVD TiCN/Al2O3 coated (hereafter referred to as “MTCVD”). At regular intervals along the length of the cut, flank wear was observed. Based on the results of the pilot tests, literature rewiev, and a manufacturer’s recommendation, cutting parameters were selected. Uncoated carbide inserts, marked in accordancewith ISO as CNMG120408MS, are coatedwith aluminum titanium nitride (AlTiN) by physical vapor deposition (PVD) with pre- and post-treatment as described in table 1. The CNMG120408 inserts, diamond-shaped with an 80° angle and 0.8 mm nose radius were rigidly mounted on a tool holder, marked in accordance with ISO as PCBNR2525M12, as shown in fig. 2. The machining parameters were selected after a thorough literature study, catalog review, and searching experiments. Experimental matrix is shown in table 2. Flank wear was measured using a Dino-Lite digital microscope. Tool life (T) is obtained with flank wear of 0.2 mm. Longitudinal turning tests were carried out on a reliable, high-precision CNC lathe. A strain gauge-type lathe dynamometer was used to measure tangential force (Fc), feed force (Ff) and radial force (Fr) during the machining process. A Taylor Hobson Surftronic tester is used to evaluate surface roughness. Fig. 1. Experimental set-up Fig. 2. Details of cutting insert and tool holder
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 Ta b l e 2 Experimental matrix for AISI 304 stainless steel (V: Cutting speed, f: Feed, and d: Depth of cut) Parameters Expt. Run 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 V (m/min) 300 350 350 250 250 300 300 300 200 400 350 250 350 250 300 f (mm/rev) 0.1 0.08 0.12 0.08 0.12 0.05 0.1 0.15 0.1 0.1 0.08 0.12 0.12 0.08 0.1 D (mm) 0.5 0.4 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.1 Results and Discussion Turning experiments were performed on a CNC lathe using the cutting modes depicted in table 2. The surface roughness, three components of cutting force, namely, Fc, Ff, and Fr, and tool life (T) were measured until the flank wear reached 0.2 mm. Experimental results with different tools, namely PVD-AlTiN coated (C) tool, PVD-AlTiN coated-microblasted (CMB), and MTCVD-TiCN/Al2O3 coated (MTCVD), are depicted in table 3. Performance modeling Experimentally validated mathematical models were developed for the responses considered in this study for the various tools to better understand the turning characteristics. The regression equations were Ta b l e 3 Experimental results in turning AISI 304 with different tools Run no. PVD-AlTiN coated (C) tool PVD-AlTiN coated-microblasted (CMB) MTCVD-TiCN/Al2O3 coated (MTCVD) Fc (N) Ff (N) Fr (N) Ra (µm) T (min) Fc (N) Ff (N) Fr (N) Ra (µm) T (min) Fc (N) Ff (N) Fr (N) Ra (µm) T (min) 1 108 44 17 0.93 8.1 118 48 21 0.88 9.81 111 55 26 1.14 18.4 2 69 27 15 0.62 10.3 69 33 16 0.57 11.2 78 38 21 0.69 14.4 3 98 41 16 0.68 7.6 98 43 21 0.74 6.8 118 53 26 0.85 9.3 4 78 31 16 0.72 14.4 88 36 17 0.77 16.4 98 40 22 0.85 21.3 5 88 51 18 0.87 11.2 137 51 23 0.96 11.1 137 56 27 1.05 14.3 6 59 22 13 0.47 18.1 49 18 12 0.45 19.5 49 22 17 0.55 24.6 7 69 33 14 0.65 12.6 69 35 18 0.65 13.9 88 40 24 0.74 18.8 8 88 47 17 0.83 10.4 98 46 26 0.81 10.3 121 59 34 0.97 14.6 9 78 34 16 0.96 15.1 88 38 20 0.93 15.9 98 45 26 0.99 22.1 10 59 29 15 0.42 6.8 69 33 18 0.50 7.2 78 40 23 0.62 9.4 11 48 19 11 0.39 14.8 39 22 14 0.42 16.4 39 29 21 0.47 18.6 12 61 33 14 0.66 15.3 59 40 19 0.70 16.3 78 40 27 0.72 20.8 13 56 31 13 0.51 10.6 59 33 18 0.52 11.8 59 45 26 0.65 15.7 14 54 23 12 0.57 17.6 39 28 14 0.61 21.8 49 28 22 0.62 26.6 15 39 17 10 0.37 16.4 29 24 13 0.40 17.4 29 23 21 0.46 22.6
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 created and its coefficient values were calculated using DataFit software. The developed mathematical models are shown in tables 4, 5, and 6 for PVD-AlTiN coated (C) tools, PVD-AlTiN coated-microblasted (CMB) tools, and MTCVD-TiCN/Al2O3 coated (MTCVD) tools, respectively. The developed models have R-squared values closer to 0.95, indicating its reliability in predicting responses based on the variation proportion in the data points during turning of SS 304 when using PVDAlTiN coated (C) tools (Eqs. 1 to 5), PVD-AlTiN coated-microblasted (CMB) tools (Eqs. 6 to 10), and MTCVD-TiCN/Al2O3 coated (MTCVD) tools (Eqs. 11 to 15). Ta b l e 4 Mathematical models for PVD-AlTiN coated (C) tool Responses Developed model R-squared value Eq. no. Tangential force (Fc) 0.195 0.426 0.652 1271.76V f d − = 0.92 (1) Feed force (Ff) 0.321 0.913 0.547 3218.41V f d − = 0.95 (2) Radial force (Fr) 0.192 0.263 0.350 121.93V f d − = 0.91 (3) Surface roughness (Ra) 0.902 0.482 0.513 620.52V f d − = 0.93 (4) Tool life (T) 0.853 0.618 0.371 231.25V f d − − − = 0.91 (5) Ta b l e 5 Mathematical models for PVD-AlTiN coated-microblasted (CMB) tool Responses Developed model R-squared value Eq. no. Tangential force (Fc) 0.559 0.821 0.980 38002.71V f d − = 0.96 (6) Feed force (Ff) 0.333 0.786 0.432 2445.18V f d − = 0.95 (7) Radial force (Fr) 0.171 0.739 0.272 369.13V f d − = 0.97 (8) Surface roughness (Ra) 0.866 0.524 0.470 543.49V f d − = 0.98 (9) Tool life (T) 0.754 0.647 0.348 141.73V f d − − − = 0.92 (10) Ta b l e 6 Mathematical models for MTCVD-TiCN/Al2O3 coated (MTCVD) tool Responses Developed model R-squared value Eq. no. Tangential force (Fc) 0.485 0.932 0.819 29772.68V f d − = 0.96 (11) Feed force (Ff) 0.093 0.874 0.463 927.66V f d − = 0.97 (12) Radial force (Fr) 0.142 0.618 0.079 250.89V f d − = 0.92 (13) Surface roughness (Ra) 0.602 0.523 0.554 153.75V f d − = 0.95 (14) Tool life (T) 0.917 0.579 0.324 551.62V f d − − − = 0.91 (15)
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 а b с Fig. 3. Tangential force (Fc) for different tools varying with (a) V, (b) f, and (c) d Further, for a better understanding, cutting forces (figs. 3–5), surface roughness (fig. 6), and tool life (fig. 7) are plotted using the developed models varying with cutting parameters for coated (C), coatedmicroblasted (CMB), and MTCVD tools. Fig. 3, a depicts tangential cutting forces for coated (C), coatedmicroblasted (CMB), and MTCVD tools varying with cutting speed at f = 0.1 mm/rev and d = 0.3 mm, respectively. The cutting forces can be seen as decreasing with the cutting speed. It could be attributed to an increase in the cutting speed increases the cutting temperature making the material soft and lowering the cutting force. Lower cutting forces can be seen for PVD-AlTiN coated (C) tools and higher forces for MTCVD-TiCN/Al2O3 coated (MTCVD) tools. However, no prominent difference in the tangential cutting force can be seen for the different tools. Fig. 3, b displays the tangential cutting forces that vary with feed for coated (C), coated-microblasted (CMB), and MTCVD tools at V = 300 m/min and d = 0.3 mm. And fig. 3, c depicts tangential cutting forces for coated (C), coated-microblasted (CMB), and MTCVD tools varying with depth of cut at V = 300 m/min and f = 0.1 mm/rev, respectively. Cutting forces increase with feed and depth of cut, and the effect is more pronounced for MTCVD-TiCN/ Al2O3 coated tools than for PVD-AlTiN coated tools (C) and PVD-AlTiN coated microblasted (CMB) tools. The lower cutting forces using PVD-AlTiN coated tools (С) and PVD-AlTiN coated microblasted (CMB) tools can be explained by the lower coefficient of friction and sharper edge radius of the single-layer PVDAlTiN coated tool compared to multilayer MTCVD-TiCN/Al2O3 coated (MTCVD) tools. The phenomenon of lower friction for PVD-AlTiN coated tools results in lower cutting force compared to MTCVD-TiCN/Al2O3 coated tools. Fig. 4, a and fig. 5, a depict feed and radial forces, respectively, for coated (C), coated-microblasted (CMB), and MTCVD tools, varying with cutting speed at f = 0.1 mm/rev and d = 0.3 mm, respectively. Fig. 4, b and fig. 5, b show the dependence of the feed force and radial force on the feed value at V = 300 m/min and d = 0.3 mm, respectively. Fig. 4, c and fig. 5, c depict feed and radial forces, respectively, for coated (C), coated-microblasted (CMB), and MTCVD tools, varying with depth of cut at V = 300 m/min and a b c Fig. 4. Feed force (Ff ) for different tools varying with (a) V, (b) f, and (c) d
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 a b c Fig. 5. Radial force (Fr) varying with (a) V, (b) f, and (c) d f = 0.1 mm/rev, respectively. The feed forces can be noticed as increasing with the feed and depth of cut and being negligibly affected by the cutting speed. Lower feed forces are observed for PVD-AlTiN coated (C) tools and higher forces are observed for MTCVD-TiCN/Al2O3 coated (MTCVD) tools. However, no prominent difference in the feed force can be noticed for coated and coated-microblasted tools. The radial forces can be noticed as negligibly affected by the cutting parameters. Higher radial forces can be seen for MTCVD-TiCN/Al2O3 coated (MTCVD) tools. Figs. 6 and 7 depict surface roughness and tool life, respectively, for coated (C), coated-microblasted (CMB), and MTCVD tools, varying with V = 300 m/min, f = 0.1 mm/rev, and d = 0.3 mm, respectively. It can be seen that the surface roughness decreases with increasing V (fig. 6, a) and increases with increasing f (fig. 6, b) and d (fig. 6, c). Lower surface roughness can be seen for PVD-AlTiN coated (C) tools and higher surface roughness for MTCVD-TiCN/Al2O3 coated (MTCVD) tools. Surface roughness is significantly affected by feed, especially for MTCVD-coated tools. However, there is no significant difference between coated tools and microblasted tools. a b c Fig. 6. Surface roughness (Ra) varying with (a) V, (b) f, and (c) d a b c Fig. 7. Tool life (T) varying with (a) V, (b) f, and (c) d
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 When changing parameters, one may observe a decrease in tool life parameters. Cutting speed can be considered as having the greatest impact on tool life, followed by feed and depth of cut. The highest tool life can be seen for MTCVD tools, followed by coated-microblasted and coated tools. This can be attributed to the thicker coating with an average thickness of 22 µm compared to the thinner coating with an average thickness of 3 µm. Further, the Al2O3 coating layer assisted to increase tool life by forming a protective aluminum oxide layer on the coated tool during machining, which has protected the tool from oxidation and the loss of cutting elements from the tool. Further, the TiCN layer of the coating provided higher adhesion between the coating and the substrate. Multi-objective optimization Researchers have made several attempts to optimize turning process parameters. However, limited studies optimized the turning of AISI 304 using coated, coated-microblasted, and MTCVD tools. The study uses a desirability function technique to optimize turning parameters to achieve minimal cutting forces, surface roughness, and maximum tool life. Using Eq. 16, each response variable (Ri) is converted into a desirability function (Di), and Eq. 17 transforms the optimization of multiple response variables into the optimization of a single desirability function (DM). The process variables and a variety of possible response functions are shown in table 7. min min min max max min max 0,1 if if ; 1, 0 if i i i i i R R R R D R R R R R R R ≤ − = ≤ ≤ − ≥ (16) ( )1 1 2 3 . n M n D D D D D = × × × − − − × (17) The one-sided transformation is used to transform each response Ri into its corresponding Di [23, 24]. By substituting all conceivable combinations and permutations of cutting parameters (around 10,000 data Ta b l e 7 Process variables and the range of response functions Process variables and responses Goal PVD-AlTiN coated (C) tool PVD-AlTiN coated-microblasted (CMB) MTCVD-TiCN/Al2O3 coated (MTCVD) Min. limit Max. limit Min. limit Max. limit Min. limit Max. limit Cutting speed (V) (m/min) Is in range 200 400 200 400 200 400 Feed (f) (mm/rev) Is in range 0.05 0.15 0.05 0.15 0.05 0.15 Depth of cut (d) (mm) Is in range 0.1 0.5 0.1 0.5 0.1 0.5 Tangential cutting force (Fc) (N) Minimize 24.5 128.3 11.9 209.9 15.1 220.4 Feed force (Ff) (N) Minimize 8.7 71.1 11.7 69.9 13.3 78.3 Radial force (Fr) (N) Minimize 7.8 21 7.7 30.4 14 34.6 Surface roughness (Ra) (mm) Minimize 0.20 1.46 0.21 1.47 0.24 1.59 Tool life (T) (min) Maximize 5.82 37.7 6.7 40.3 8.5 51.1
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 points) in the developed mathematical models that fall within the parameters chosen in the current study, minimum and maximum limits of response functions are obtained. One-sided transformation for different responses for PVD-AlTiN coated (C), PVD-AlTiN coated-microblasted (CMB), and MTCVD-TiCN/Al2O3 (MTCVD) tools can be represented considering the lower and higher limits of the respective responses. One-sided transformation for different responses for PVD-AlTiN coated (C) tools (Eqs. 18–22), PVDAlTiN coated-microblasted (CMB) tools (Eqs. 23–27), and MTCVD-TiCN/Al2O3 coated tools (MTCVD) (Eqs. 28–32) are given in tables 8, 9, 10, respectively. For each level of independent parameters, DFc, DFf, DFr, Dra and DT were calculated using Eqs. 18–22 for PVD-AlTiN coated tools, Eqs. 23–27 for PVD-AlTiN coated-microblasted tools, and Eqs. 28–32 for MTCVD-TiCN/Al2O3 coated tools. Then, a single desirability function, DM was calculated by substituting DFc, DFf, DFr, Dra and DT in Eq. 17. The optimal parameter was chosen based on the solution with the highest desirability (DM). In the present study a family of optimal solutions having single desirability function (DM) of above 0.9 are selected and are shown in tables 11, 12, and 13 for PVD-AlTiN coated (C) tools, PVD-AlTiN coatedmicroblasted (CMB) tools, and MTCVD-TiCN/Al2O3 coated tools, respectively. In the present study, V = 200–290 m/min, f = 0.05–0.055 mm/rev, and d = 0.1–0.12 mm were found to be the optimal parameters when using PVD-AlTiN coated (C) tools and MTCVD-TiCN/Al2O3 coated tools. However, V = 200–320 m/min, f = 0.05–0.055 mm/rev and d = 0.1–0.12 mm, are the optimal cutting condition when using PVD-AlTiN coated-microblasted (CMB) tools. The optimization study reveals that in comparison with C-coated and CMB-coated tools, when turning AISI 304 stainless steel with MTCVD coated tools, the cutting forces are significantly less and amount to 18–27 N, and the minimum surface roughness reaches 0.3–0.44 µm, while the tool life increases to 36–51 min. Ta b l e 8 One-sided transformation for PVD-AlTiN coated (C) tools Desirability for tangential cutting force (DFc) (Eq. 18) Desirability for feed force (DFf) (Eq. 19) max min max max min 0, 128.3 , 1, 24.5 i i c c c c c c c c c c F F F DF F F F F F F ≥ − = ≤ ≤ − ≤ max min max max min 0, 71.1 , 1, 8.7 i i f f f f f f f f f f F F F DF F F F F F F ≥ − = ≤ ≤ − ≤ Desirability for radial force (DFr) (Eq. 20) Desirability for surface roughness (DRa) (Eq. 21) max min max max min 0, 21 , 1, 7.8 i i r r r r r r r r r r F F F DF F F F F F F ≥ − = ≤ ≤ − ≤ max min max max min 0, 1.46 , 1, 0.2 i i a a a a a a a a a a R R R DR R R R R R R ≥ − = ≤ ≤ − ≤ Desirability for tool life (DT) (Eq. 22) min min max max min 0, 5.82 , 1, 37.7 i T i T T T D T T T T T T ≤ − = ≤ ≤ − ≥
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 Ta b l e 9 One-sided transformation for PVD-AlTiN coated-microblasted (CMB) tools Desirability for tangential cutting force (DFc) (Eq. 23) Desirability for feed force (DFf) (Eq. 24) max min max max min 0, 209.9 , 1, 11.9 i i c c c c c c c c c c F F F DF F F F F F F ≥ − = ≤ ≤ − ≤ max min max max min 0, 69.9 , 1, 11.7 i i f f f f f f f f f f F F F DF F F F F F F ≥ − = ≤ ≤ − ≤ Desirability for radial force (DFr) (Eq. 25) Desirability for surface roughness (DRa) (Eq. 26) max min max max min 0, 30.4 , 1, 7.7 i i r r r r r r r r r r F F F DF F F F F F F ≥ − = ≤ ≤ − ≤ max min max max min 0, 1.47 , 1, 0.21 i i a a a a a a a a a a R R R DR R R R R R R ≥ − = ≤ ≤ − ≤ Desirability for tool life (DT) (Eq. 27) min min max max min 0, 6.7 , 1, 40.3 i T i T T T D T T T T T T ≤ − = ≤ ≤ − ≥ Ta b l e 1 0 One-sided transformation for MTCVD-TiCN/Al2O3 coated tools Desirability for tangential cutting force (DFc) (Eq. 28) Desirability for feed force (DFf) (Eq. 29) max min max max min 0, 220.4 , 1, 15.1 i i c c c c c c c c c c F F F DF F F F F F F ≥ − = ≤ ≤ − ≤ max min max max min 0, 78.3 , 1, 13.3 i i f f f f f f f f f f F F F DF F F F F F F ≥ − = ≤ ≤ − ≤ Desirability for radial force (DFr) (Eq. 30) Desirability for surface roughness (DRa) (Eq. 31) max min max max min 0, 34.6 , 1, 14 i i r r r r r r r r r r F F F DF F F F F F F ≥ − = ≤ ≤ − ≤ max min max max min 0, 1.59 , 1, 0.24 i i a a a a a a a a a a R R R DR R R R R R R ≥ − = ≤ ≤ − ≤ Desirability for tool life (DT) (Eq. 32) min min max max min 0, 8.5 , 1, 51.1 i T i T T T D T T T T T T ≤ − = ≤ ≤ − ≥
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 Ta b l e 1 1 Family of optimal solutions [V (m/min), f (mm/rev), d (mm)] for PVD-AlTiN coated (C) tools Optimum parameters Optimum responses Desirability Single desirability (DM) Fc (N) Ff (N) Fr (N) Ra (µm) T (min) DFc DFf DFr DRa DT [200, 0.05, 0.1] 28.15 10.82 8.96 0.38 37.70 0.97 0.97 0.92 0.86 1.00 0.94 [210, 0.05, 0.1] 27.88 10.65 8.87 0.36 36.16 0.97 0.97 0.92 0.87 0.95 0.94 [220, 0.05, 0.1] 27.63 10.49 8.79 0.35 34.76 0.97 0.97 0.93 0.89 0.91 0.93 [230, 0.05, 0.1] 27.39 10.34 8.72 0.33 33.46 0.97 0.97 0.93 0.90 0.87 0.93 [240, 0.05, 0.1] 27.17 10.20 8.65 0.32 32.27 0.98 0.98 0.94 0.91 0.83 0.92 [250, 0.05, 0.1] 26.95 10.07 8.58 0.31 31.17 0.98 0.98 0.94 0.92 0.79 0.92 [260, 0.05, 0.1] 26.75 9.94 8.52 0.30 30.14 0.98 0.98 0.95 0.92 0.76 0.91 [270, 0.05, 0.1] 26.55 9.83 8.46 0.29 29.19 0.98 0.98 0.95 0.93 0.73 0.91 [280, 0.05, 0.1] 26.36 9.71 8.40 0.28 28.29 0.98 0.98 0.96 0.94 0.70 0.91 [290, 0.05, 0.1] 26.18 9.60 8.34 0.27 27.46 0.98 0.98 0.96 0.95 0.68 0.90 [200, 0.055, 0.1] 29.32 11.80 9.18 0.40 35.54 0.95 0.95 0.90 0.85 0.93 0.92 [210, 0.055, 0.1] 29.04 11.62 9.10 0.38 34.09 0.96 0.95 0.90 0.86 0.89 0.91 [220, 0.055, 0.1] 28.78 11.45 9.02 0.36 32.77 0.96 0.96 0.91 0.87 0.85 0.91 [230, 0.055, 0.1] 28.53 11.28 8.94 0.35 31.55 0.96 0.96 0.92 0.88 0.81 0.90 Ta b l e 1 2 Family of optimal solutions [V (m/min), f (mm/rev), d (mm)] for PVD-AlTiN coated-microblasted (CMB) tools Optimum parameters Optimum responses Desirability Single desirability (DM) Fc (N) Ff (N) Fr (N) Ra (µm) T (min) DFc DFf DFr DRa DT [200, 0.05, 0.1] 17.60 14.70 8.71 0.39 40.36 0.97 0.95 0.96 0.86 1.00 0.95 [210, 0.05, 0.1] 17.12 14.47 8.64 0.37 38.90 0.97 0.95 0.96 0.87 0.96 0.94 [220, 0.05, 0.1] 16.68 14.25 8.57 0.36 37.56 0.98 0.96 0.96 0.89 0.92 0.94 [230, 0.05, 0.1] 16.27 14.04 8.51 0.34 36.32 0.98 0.96 0.97 0.90 0.88 0.94 [240, 0.05, 0.1] 15.89 13.84 8.45 0.33 35.17 0.98 0.96 0.97 0.91 0.85 0.93 [250, 0.05, 0.1] 15.53 13.65 8.39 0.32 34.10 0.98 0.97 0.97 0.91 0.81 0.93 [260, 0.05, 0.1] 15.19 13.47 8.33 0.31 33.11 0.98 0.97 0.97 0.92 0.78 0.92 [270, 0.05, 0.1] 14.88 13.31 8.28 0.30 32.18 0.99 0.97 0.98 0.93 0.76 0.92 [200, 0.055, 0.1] 19.03 15.85 9.35 0.41 37.94 0.96 0.93 0.93 0.84 0.93 0.92 [280, 0.05, 0.1] 14.58 13.15 8.23 0.29 31.31 0.99 0.97 0.98 0.94 0.73 0.92 [210, 0.055, 0.1] 18.52 15.59 9.27 0.39 36.57 0.97 0.93 0.93 0.86 0.89 0.91 [200, 0.055, 0.12] 21.04 15.91 9.16 0.42 37.88 0.95 0.93 0.94 0.83 0.93 0.91 [290, 0.05, 0.1] 14.30 12.99 8.18 0.28 30.49 0.99 0.98 0.98 0.95 0.71 0.91 [210, 0.05, 0.12] 20.47 15.65 9.08 0.40 36.51 0.96 0.93 0.94 0.85 0.89 0.91 [220, 0.055, 0.1] 18.04 15.35 9.20 0.38 35.31 0.97 0.94 0.94 0.87 0.85 0.91 [300, 0.05, 0.1] 14.03 12.85 8.13 0.27 29.72 0.99 0.98 0.98 0.95 0.68 0.91 [220, 0.05, 0.12] 19.95 15.41 9.01 0.39 35.25 0.96 0.94 0.94 0.86 0.85 0.91
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 T h e E n d Ta b l e 1 2 Optimum parameters Optimum responses Desirability Single desirability (DM) Fc (N) Ff (N) Fr (N) Ra (µm) T (min) DFc DFf DFr DRa DT [230, 0.055, 0.1] 17.60 15.13 9.13 0.36 34.15 0.97 0.94 0.94 0.88 0.82 0.91 [310, 0.05, 0.1] 13.77 12.71 8.09 0.27 28.99 0.99 0.98 0.98 0.96 0.66 0.91 [230, 0.05, 0.12] 19.46 15.19 8.94 0.37 34.08 0.96 0.94 0.95 0.87 0.81 0.90 [240, 0.055, 0.1] 17.18 14.92 9.06 0.35 33.07 0.97 0.94 0.94 0.89 0.78 0.90 [320, 0.05, 0.1] 13.53 12.57 8.04 0.26 28.31 0.99 0.98 0.99 0.96 0.64 0.90 [240, 0.05, 0.12] 19.00 14.97 8.88 0.36 33.01 0.96 0.94 0.95 0.88 0.78 0.90 [250, 0.055, 0.1] 16.80 14.71 9.00 0.34 32.06 0.98 0.95 0.94 0.90 0.75 0.90 Ta b l e 1 3 Family of optimal solutions [V (m/min), f (mm/rev), d (mm)] for MTCVD-TiCN/Al2O3 coated tools Optimum parameters Optimum responses Desirability Single desirability (DM) Fc (N) Ff (N) Fr (N) Ra (µm) T (min) DFc DFf DFr DRa DT [200, 0.05, 0.1] 21.20 14.23 15.48 0.37 51.14 0.97 0.99 0.93 0.91 1.00 0.96 [210, 0.05, 0.1] 20.70 14.17 15.37 0.36 48.90 0.97 0.99 0.93 0.92 0.95 0.95 [220, 0.05, 0.1] 20.24 14.11 15.27 0.35 46.86 0.98 0.99 0.94 0.92 0.90 0.94 [230, 0.05, 0.1] 19.81 14.05 15.17 0.34 44.98 0.98 0.99 0.94 0.93 0.86 0.94 [240, 0.05, 0.1] 19.40 13.99 15.08 0.33 43.26 0.98 0.99 0.95 0.94 0.82 0.93 [200, 0.05, 0.12] 24.61 15.49 15.70 0.41 48.20 0.95 0.97 0.92 0.88 0.93 0.93 [200, 0.055, 0.1] 23.17 15.47 16.42 0.39 48.39 0.96 0.97 0.88 0.89 0.94 0.93 [250, 0.05, 0.1] 19.02 13.94 14.99 0.32 41.67 0.98 0.99 0.95 0.94 0.78 0.93 [210, 0.05, 0.12] 24.03 15.42 15.59 0.40 46.09 0.96 0.97 0.92 0.89 0.88 0.92 [210, 0.055, 0.1] 22.62 15.40 16.30 0.38 46.27 0.96 0.97 0.89 0.90 0.89 0.92 [260, 0.05, 0.1] 18.66 13.89 14.91 0.32 40.20 0.98 0.99 0.96 0.95 0.74 0.92 [220, 0.05, 0.12] 23.50 15.35 15.49 0.39 44.17 0.96 0.97 0.93 0.90 0.84 0.92 [220, 0.055, 0.1] 22.12 15.33 16.20 0.37 44.34 0.97 0.97 0.89 0.91 0.84 0.91 [270, 0.05, 0.1] 18.33 13.84 14.83 0.31 38.83 0.98 0.99 0.96 0.95 0.71 0.91 [230, 0.05, 0.12] 23.00 15.29 15.39 0.38 42.40 0.96 0.97 0.93 0.90 0.80 0.91 [230, 0.055, 0.1] 21.65 15.27 16.09 0.36 42.57 0.97 0.97 0.90 0.92 0.80 0.91 [280, 0.05, 0.1] 18.00 13.79 14.76 0.30 37.56 0.99 0.99 0.96 0.96 0.68 0.91 [240, 0.05, 0.12] 22.53 15.23 15.30 0.37 40.78 0.96 0.97 0.94 0.91 0.76 0.90 [200, 0.05, 0.14] 27.92 16.63 15.89 0.44 45.85 0.94 0.95 0.91 0.85 0.88 0.90 [240, 0.055, 0.1] 21.20 15.21 16.00 0.35 40.94 0.97 0.97 0.90 0.92 0.76 0.90 [290, 0.05, 0.1] 17.70 13.75 14.68 0.30 36.37 0.99 0.99 0.97 0.96 0.65 0.90 Validatory experiments are conducted under optimal cutting conditions for the different tools considered in the present study. Table 14 depicts that the predicted results of cutting forces at optimal cutting conditions for different tools using developed mathematical models are in good agreement with the experimental results. The error in the predicted and experimental results is less than 15 % for cutting forces and less than
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 10 % for surface roughness and tool life. It demonstrates that, within the range of the chosen parameters and using different tools taken into account in the current study, the developed model could be used to accurately predict AISI 304 turning responses. Ta b l e 1 4 Validatory experimental matrix at optimum parameters [V (m/min), f (mm/rev), d (mm)] Optimum parameters Tool type Model results (Eq. 11–13) Experimental results Fc (N) Ff (N) Fr (N) Ra (µm) T (min) Fc (N) Ff (N) Fr (N) Ra (µm) T (min) [230, 0.055, 0.1] C 28.53 11.28 8.94 0.35 31.55 29 11 11 0.39 34 [200, 0.05, 0.1] C 28.15 10.82 8.96 0.38 37.70 33 14 10 0.33 36 [250, 0.055, 0.1] CMB 16.80 14.71 9.00 0.34 32.06 21 18 11 0.29 27 [200, 0.15, 0.2] CMB 17.60 14.70 8.71 0.39 40.36 21 17 12 0.36 36 [290, 0.05, 0.1] MTCVD 17.70 13.75 14.68 0.30 36.37 23 16 16 0.33 33 [200, 0.05, 0.1] MTCVD 21.20 14.23 15.48 0.37 51.14 24 19 17 0.39 47 This study strongly recommends MTCVD-TiCN/Al2O3 coated tools for finishing turning of AISI 304 stainless steel using V = 200–290 m/min and lower values of f and d. This study did not consider the tool wear effect on cutting forces and finds scope to model forces considering the tool wear effect in the turning of AISI 304 with differently pre-and post-treated coated tools. Conclusions In the current study, the dry turning performance of AISI 304 stainless steel with single-layer PVDAlTiN coated, single-layer PVD-AlTiN coated and microblasted, and MTCVD-TiCN/Al2O3 coated (MTCVD) tools is evaluated. The following conclusions can be drawn from the present study. 1. PVD-AlTiN coated tools provide the lowest cutting forces and surface roughness, followed by PVD-AlTiN coated-microblasted and MTCVD-TiCN/Al2O3 coated tools. However, these responses were marginally differed for coated and coated-microblasted tools. 2. The cutting forces decrease with the cutting parameters. However, this effect is significant for MTCVD-TiCN/Al2O3 coated tools. On the other hand, higher tool life is observed for MTCVD-TiCN/Al2O3 coated tools, followed by PVD-AlTiN coated-microblasted and PVD-AlTiN coated tools. 3. The correlation coefficients observed above 0.9 for the developed models showed that the developed models can be used reliably to predict the responses studied during turning AISI 304 within the range of the parameters considered in this study. 4. The optimization study reveals that turning of AISI 304 with MTCVD-TiCN/Al2O3 coated tools incurs lower cutting forces of 18–27 N, produces a minimum surface roughness of 0.3–0.44 μm, and has a better tool life of 36–51 min compared to PVD-AlTiN coated (C) and PVD-AlTiN coated-microblasted (CMB) tools. 5. This study strongly recommends MTCVD-TiCN/Al2O3 coated tools for finishing turning of AISI 304 stainless steel using V = 200–290 m/min and lower values of f and d. References 1. He H.B., Li H.Y., Yang J., Zhang X.Y., Yue Q.B., Jiang X., Lyu S.K. A study on major factors influencing dry cutting temperature of AISI 304 stainless steel. International Journal of Precision Engineering and Manufacturing, 2017, vol. 18, pp. 1387–1392. DOI: 10.1007/s12541-017-0165-6.
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