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 Ultrasonic vibration-assisted hard turning of AISI 52100 steel: comparative evaluation and modeling using dimensional analysis Govind Ghule1, a,*, Sudarshan Sanap1, b, Satish Chinchanikar2, c 1 MIT-School of Engineering, MIT-ADT University, Pune - 412201, India 2 Vishwakarma Institute of Information Technology, Pune - 411048, India a https://orcid.org/0000-0003-4331-3501, govindghulemasterofengineering@gmail.com; b https://orcid.org/0000-0002-3788-0692, sudarshan.sanap@mituniversity.edu.in; c https://orcid.org/0000-0002-4175-3098, satish.chinchanikar@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. 136–150 ISSN: 1994-6309 (print) / 2541-819X (online) DOI: 10.17212/1994-6309-2023-25.4-136-150 ART I CLE I NFO Article history: Received: 03 September 2023 Revised: 17 September 2023 Accepted: 27 September 2023 Available online: 15 December 2023 Keywords: Ultrasonic vibrations Hard turning Dimensional analysis Buckingham Pi theorem Tool wear Power consumption ABSTRACT Introduction. Precision machining of hard and brittle materials is difficult, which has led to the development of novel and sustainable techniques such as ultrasonic vibration-assisted turning (UVAT) for enhanced removal rates, surface quality, and tool life. The purpose of the work. Hard turning using cost-effective coated carbide tools instead of costly to operate ceramic and CBN inserts is still not widely accepted due to tool wear and machining limitations. A group of researchers attempted hard turning using carbide tools with different coatings, different cooling techniques, etc., to achieve better machinability. However, very few attempts were made by the researchers on ultrasonic vibration-assisted hard turning (UVAHT). Moreover, comparative evaluation of UVAHT using dimensional analysis is rarely reported in the open literature. The methods of investigation. With this view, this study comparatively evaluates the tool wear and power consumption during conventional turning (CT) and ultrasonic vibration-assisted hard turning (UVAHT) of AISI 52100 steel (62 HRC) using a PVD-coated TiAlSiN carbide tool. Experiments were performed with varying cutting speed, feed, and depth of cut while keeping vibration frequency and amplitude constant at 20 kHz and 20 µm, respectively. Further, a theoretical model was developed to predict the tool wear and power consumption using the concept of Dimensional analysis, i.e., the Buckingham Pi theorem considering the effect of cutting speed, frequency, and amplitude of vibrations at constant feed and depth of cut of 0.085 mm/rev and 0.4 mm, respectively. Dimensionless groups were created to reveal complex linkages and optimize machining conditions. Tool wear and power consumption were measured experimentally and statistically analyzed using the Buckingham Pi theorem. Results and Discussion. Using dimensional analysis, the research uncovers substantial insights into the UVAHT process. The results show that ultrasonic vibration parameters have a significant impact on tool wear and power consumption. Dimensionless groups provide a methodical foundation for refining machining conditions. The tool wear and the power consumption increase with the cutting speed, depth of cut, and feed. However, this effect is more significant in CT than UVAHT. The power consumption increases with the cutting speed, vibration frequency, and amplitude. However, the increase in the power consumption is more prominent when the cutting speed changes, followed by vibration frequency and amplitude. The flank wear increases with the cutting speed and vibration amplitude and decreases with the vibration frequency. This study contributes to a better understanding of the underlying dynamics of UVAHT, which will help to improve precision machining procedures for hard materials. The paper explores the practical significance of these discoveries for hard material precision machining. For citation: Ghule G.S., Sanap S., Chinchanikar S. Ultrasonic vibration-assisted hard turning of AISI 52100 steel: comparative evaluation and modeling using dimensional analysis. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2023, vol. 25, no. 4, pp. 136–150. DOI: 10.17212/1994-6309-2023-25.4-136-150. (In Russian). ______ * Corresponding author Ghule Govind S., M.E. (Design Engineering), Assistant Professor MIT-School of Engineering, MIT-ADT University, Pune - 412201, India Tel.: +91-7020742258, E-mail: govindghulemasterofengineering@gmail.com
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 Introduction Ultrasonic vibration-assisted hard turning (UVAHT) is a potential machining technique that combines the advantages of traditional turning with the use of ultrasonic vibrations to improve hard material machining. AISI 52100 steel is a commonly used bearing steel that is noted for its excellent hardness, wear resistance, and dimensional stability. Ultrasonic vibration-assisted turning (UVAT) has demonstrated tremendous potential for improving the machinability of such hard materials, allowing for higher material removal rates, enhanced surface integrity, and reduced tool wear [1–3]. Because of its high strength and hardness, the typical hard turning method sometimes finds difficulties when machining hardened materials such as AISI 52100 steel. This results in increased cutting forces, higher tool-workpiece interface temperatures, and accelerated tool wear, all of which impair the surface polish and dimensional accuracy of the machined components. UVAHT can alleviate these issues and provide various benefits by adding high-frequency ultrasonic vibrations during the turning process. The underlying dynamics of UVAHT involve the propagation of ultrasonic vibrations through the tool and into the workpiece, which results in micro fracturing, lower cutting forces, and enhanced chip removal. These dynamic impacts on the cutting process change the material removal mechanism and affect the toolworkpiece relationship, resulting in better cutting performance. However, to take full advantage of UVAHT of AISI 52100 steel, it is necessary to understand the impact of numerous process factors and its interactions. Ultrasonic vibration-assisted hard turning (UVAHT) has received a lot of attention in recent years as a potential machining technology for hard materials such as AISI 52100 steel. Several studies have investigated the impact of ultrasonic vibration on hard turning operations and its potential advantages for increasing surface integrity, reducing cutting forces, and extending tool life. The literature study provided here gives an overview of significant research related to UVAT and its use in the machining of AISI 52100 steel. The use of ultrasonic vibrations in machining operations has received a lot of attention. Some studies have focused on ultrasonic-assisted turning of conventional materials, emphasizing the reduced cutting forces and increased surface polish attained with this technology. Liu et al. [4] studied the impact of ultrasonic vibration on the cutting performance of AISI 1045 steel and found that it improved tool life and surface quality significantly. These investigations laid the groundwork for further research into the use of UVAHT for hard materials such as AISI 52100 steel. Because of its numerous industrial uses, hard turning of AISI 52100 steel has piqued interest. To improve the machinability of this material, researchers investigated various cutting modes and tool geometries. The authors in [5], for example, investigated the effect of cutting speed and feed rate on tool wear and surface roughness during hard turning of AISI 52100 steel. These studies revealed the difficulties associated with traditional hard turning and stimulated the study of other methods such as UVAHT. The use of ultrasonic vibrations in hard turning has showed significant promise in terms of enhancing machining performance. The effects of various ultrasonic parameters, such as vibration amplitude and frequency, on cutting forces and surface integrity during UVAHT have been studied. In [6] investigated the impact of ultrasonic vibration amplitude on chip formation and surface roughness during hard turning of AISI 4140 steel, offering important insight into the dynamic effects of ultrasonic vibrations on material removal. In the field of machining, dimensional analysis has been widely employed to investigate the correlations between process parameters and performance indicators. The authors in [7] used dimensional analysis to study the effect of cutting modes on surface roughness in hard turning, laying the groundwork for applying this method to UVAHT. Similarly, Zhang et al. [8] used dimensional analysis to investigate the impacts of process parameters in ultrasonic vibration-assisted milling, emphasizing its use for optimizing machining processes. Dimensional analysis is a strong method for studying the UVAHT process and identifying the important characteristics that affect its success. This method entails identifying and formulating dimensionless groups that connect the important process variables without necessitating entire experimental research. Dimensional analysis gives important insights into the interactions between numerous process factors and its impact on cutting performance by reducing complicated relationships to dimensionless parameters.
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 The authors in [9] investigated the UVAT method for titanium alloy using dimensional analysis to study the effects of ultrasonic vibration parameters and conventional turning parameters on surface roughness and cutting forces, dimensionless groups were created. The dimensional analysis method was useful in optimizing the UVAT parameters for titanium alloy machining. Scientists in [10] presented dimensional analysis which was used in this work to investigate surface integrity during UVAT. The research examined how ultrasonic vibration parameters and conventional turning parameters affect surface roughness, residual stress, and micro hardness. The dimensional analysis method assisted in identifying the important parameters affecting surface integrity and gave guidance for enhancing surface quality using UVAT. Scientists in [11] proposed dimensional analysis which was used in this work to investigate surface integrity in UVAT of hardened AISI 4340 steel. Dimensionless groups were formed to investigate the effects of ultrasonic vibration and cutting modes on surface roughness, hardness, and residual stress. The study revealed the use of UVAT to improve surface integrity, as well as the utility of dimensional analysis in studying the process. The authors in [12] conducted an experiment which explained the dimensional analysis of ultrasonic vibration-assisted micro-cutting of silicon. Dimensionless groups were created to investigate the impact of ultrasonic vibration parameters and cutting parameters on cutting forces and surface quality. The dimensional analysis technique provided insights into the optimization of the silicon micro-cutting process. The purpose of this research paper is to comparatively evaluate the conventional hard turning and ultrasonic vibration-assisted hard turning and develop a theoretical model of tool wear and power consumption using dimensional analysis. The model will be developed using Buckingham Pi theorem considering cutting speed, density, workpiece hardness, vibrational amplitude, and frequency as the input parameters. The findings of this study will help to optimize the UVAHT of AISI 52100 steel, offering significant guidance for improving machining performance. Furthermore, the findings of the study will provide useful guidance for industry practitioners aimed at improving the efficiency and quality of hard turning operations on AISI 52100 steel employing ultrasonic vibration support. UVAHT has the potential to find widespread use in precision manufacturing sectors requiring hard and difficult-to-cut materials by expanding the understanding of this novel machining process. The methods of investigation UVAHT Equipment Configuration An ultrasonic vibration system is integrated with a conventional lathe in the experimental setup for ultrasonic vibration-assisted hard turning (UVAHT). A precision lathe with a motorized spindle and a modified tool holding fixture, specifically designed for mounting an ultrasonic vibratory tool (UVT), which is an assembly of a transducer, booster, and a horn that serves as a tool holder for performing hard turning operations conventionally and with ultrasonic vibration assistance. The rotating motion required by the workpiece and cutting tool is provided by the lathe. The total UVAHT composition is made up of several components such as a lathe machine, a workpiece, a specifically designed fixture, an ultrasonic frequency generator, and a transducer-booster assembly (fig. 1). In this sustainable cutting strategy, the cutting tool and w/p are regularly separated and get in contact (intermittent process), resulting in no BUE generation. This advanced technique consists of four major stages: 1) approach, 2) touch, 3) immersion, and 4) back off. These four steps of UVAT are recreated in fig. 2 for fully understanding this approach [13–15]. However, when vibrations are applied in the cutting velocity direction, a few limitations should be considered, namely Vc = πdn, Vt = 2πAF. Where “Vc” is cutting velocity, “n” is rotations per minute, “d” is workpiece diameter, “Vt” is tip velocity, i.e. vibrational speed of cutting, “A” is vibration amplitude, and “F” is frequency. If A = 20 m and F = 20 kHz, then the value for “Vt”, i.e., the tip velocity, should be less than 150 m/min. The relative displacements of the cutting tool and the workpiece in ultrasonic-assisted turning (UVAT) are depicted in fig. 3 [16].
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 Fig. 3. Relative displacements of the cutting tool and the workpiece in CT and UVAT Fig. 2. Four stages of UVAT Fig. 1. Schematic diagram of UVAHT systems Employing high frequency vibrations, several cycles may be completed in less than a millisecond. During conventional turning (CT), the tip of the cutting tool is constantly in contact with the surface of the workpiece. When ultrasonic vibrations are applied to the tip of the cutting tool, the interaction between the tool tip and the workpiece changes completely and becomes discontinuous (i.e., intermittent) [17].
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 Experimental Setup The workpiece material used in the experiments is AISI 52100 steel, common bearing steel known for its high hardness and wear resistance. Because of the severe hardening of the workpieces, the cutting force, required for machining AISI 52100 hardened steel, is relatively considerable. Accelerated tool wear and chip breakup are challenging tasks, thus the material for the cutting tool should be more abrasion resistant. As a result, selecting the most appropriate cutting tool material, tool form, and cutting modes is critical for enhancing the machinability of AISI 52100 hardened steel. In this experiment, a PVD-coated TiAlSiN tool with the geometry CNMG120408-MF5 was used. Actual photograph of base frame with UVAHT mounting is shown in fig. 4. Additionally, table 1 depicts the geometry of the tool insert. Fig. 4. Actual photograph of base frame with UVAHT mounting Ta b l e 1 Geometry of the cutting insert Specifications Values Insert included angle (degree) 80 Cutting edge length (mm) 12.9 Inscribed circle diameter (mm) 12.7 Insert thickness (mm) 4.76 Weight of item (kg) 0.01 Approach angle (degree) 75 Nose radius (mm) 0.8 Experiments using ultrasonic vibration-assisted hard turning (UVAHT) were carried out on a lathe with a maximum spindle speed of 1,145 rpm and a motor power supply of 2.2 kW. The pilot investigations determined the cutting speed, feed, depth of cut, ultrasonic frequency and vibrational amplitude. Experiments were planned using response surface technology, namely the central composite rotatable design (CCRD). Table 4 shows the selection of cutting modes for turning. The CCRD approach allows selecting a set of experimental runs that thoroughly covers the design space while requiring the fewest number of trials available, hence assisting in the optimization of experimental settings. Based on the pilot experiments, cutting speed, feed, depth of cut, ultrasonic frequency, and vibrational amplitude were selected. Experiments were designed using response surface methodology, specifically the central composite rotatable design. Two-sets of experiments were performed. First set of experiments comparatively evaluates the machining performance of CT and UVAHT varying with cutting speed, feed, and depth of cut. In the
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 first set, UVAHT experiments are performed using constant frequency of 20 kHz with a vibrational amplitude of 20 µm. To understand UVAHT better, a theoretical model for power consumption and flank wear were developed using dimensional analysis. The second set of experiments was performed to calibrate the developed model considering the effect of cutting speed, frequency, and amplitude of vibrations. The cutting conditions used for comparative evaluation and theoretical modeling are depicted in table 2. Ta b l e 2 Values of cutting parameters obtained by Design Expert Run order Comparative evaluation between CT and UVAHT Theoretical modelling: UVAHT Cutting speed (Vc) (m/min) Feed (f) (mm/rev) Depth of cut (d) (mm) Cutting speed (Vc) (m/min) Frequency (F) (kHz) Amplitude (A) (µm) 1 60 0.085 0.4 60 20 20 2 120 0.075 0.35 120 20 20 3 100 0.068 0.4 100 20 20 4 100 0.085 0.5 100 20 20 5 100 0.085 0.4 100 20 20 6 80 0.075 0.35 80 20 20 7 100 0.085 0.3 100 20 20 8 120 0.075 0.45 120 20 20 9 100 0.103 0.4 100 20 20 10 100 0.085 0.4 100 20 20 11 80 0.095 0.45 80 20 20 12 100 0.085 0.4 100 20 20 13 100 0.085 0.4 100 20 20 14 80 0.075 0.45 80 20 20 15 100 0.085 0.4 100 20 20 16 120 0.095 0.35 120 20 20 17 80 0.095 0.35 80 20 20 18 120 0.095 0.45 120 20 20 19 145 0.085 0.4 145 20 20 20 100 0.085 0.4 100 20 20 The focus of the present study was on tool wear and power consumption. A Dino-Lite digital microscope with a magnification of up to 240X was used to measure tool wear. A clamp meter, which looks like a clothespin, was used to measure the current carried by a live wire. A clamp meter detects the magnetic field created by a flowing current in a wire. The power consumption during turning is given by the product of voltage and measured current. The actual set of machining conditions as per the design of experiment is shown in table 3. In the case of conventional turning, frequency and amplitude were considered to be zero, and in the case of ultrasonic vibration-assisted turning, frequency and amplitude were kept constant at 20 kHz and 20 µm respectively.
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 Results and Discussion Comparative Performance: CT and UVAHT First set of twenty experiments as depicted in table 2 are performed to comparatively evaluate the power consumption and flank wear under CT and UVAHT. Experiments were performed varying the cutting speed, feed, and depth of cut and UVAHT experiments were performed using constant frequency and amplitude of vibrations of 20 kHz and 20 µm, respectively. Tool wear is the steady degradation of tool materials which leads the tool to deviate from its original shape during cutting. The wear of tools affects machining efficiency, quality, cutting power, and pricing. Additionally, tool wear has a significant influence on the surface quality of the machined component as well. The three major forms of wear are commonly believed to be abrasion, adhesion and diffusion. A Dino-Lite digital microscope with a magnification rate of up to 250X was used to monitor tool wear. Dino Capture 2.0 recognizes images and stores them in the system memory when installed on a laptop. The digital microscope images of tool wear are given below in varying degrees of detail. As previously defined, conventional turning frequency and amplitude were regarded zero, and in the case of ultrasonic vibrationassisted turning, frequency and amplitude were held constant at 20 kHz and 20 µm, respectively. Power consumption during cutting provides stability and assists in selecting appropriate modes to reduce energy consumption. Power consumption should be reduced throughout the machining process to encourage sustainable development in the machining process. This section describes how machine tools utilize power during CT and UVAHT in various cutting conditions. The power required to operate the lathe machine is calculated as the product of voltage and current. Throughout the experiment, the voltage was kept constant at roughly 420 volts (3-phase), and the current was monitored with a clap meter. The power was estimated by multiplying the voltage and current. The changes in experimentally based tool wear and power consumption in CT and UVAHT are shown in figs. 5 and 6. Fig. 5. Comparison of flank wear in CT and UVAHT Fig. 6. Comparison of power consumption in CT and UVAHT
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 Dimensional Analysis Second set of twenty experiments as depicted in table 2 are performed to calibrate a theoretically developed flank wear and power consumption models for UVAHT. Experiments were performed varying the cutting speed, frequency, and amplitude of vibrations as depicted in table 2 and at constant feed and depth of cut of 0.085 mm/rev and 0.4 mm, respectively. The Buckingham Pi Theorem, named after the physicist Edgar Buckingham, is a fundamental principle in dimensional analysis. It states that when a physical problem involves “n” variables and “m” fundamental dimensions (such as length, time, mass, etc.), the problem can be expressed using n–m dimensionless parameters i.e. (Pi terms). The Pi terms are constructed as products of the original variables raised to appropriate powers such that the resulting expression is dimensionless [18–20]. The process of determining the Pi terms involves finding dimensionally independent groups of variables that describe the physical phenomena in the problem. According to Buckingham Pi theorem, the equation linking all the variables will have (n – m) dimensionless groups if the problem has “n” variables and those variables comprise “m” fundamental dimensions (for instance, M, L, and T): π1 = f (π2, π3, …….π n–m). The resulting equation takes the following form: the groups should not be dependent on one another, and no group should be established by adding the powers of other groups together. This approach has the benefit of being easier to use than the simultaneous equation method for determining the values of the indices (the exponent values of the variables). There are two prerequisites for using this approach to solve the equation. Each of the fundamental dimensions should be represented by one of the “m” variables at a minimum. One of the variables in a recurrent set should not be able to be formed into a dimensionless group. A dimensionless group of variables known as a repeating set. Selection of Dimensionless Parameters The selection of dimensionless parameters (Pi terms) involves identifying dimensionally independent groups of variables. These groups are chosen based on the underlying physics of the problem. The goal is to capture the significant interactions and relationships between the variables that govern the behavior of the system. In the context of conventional as well as ultrasonic vibration-assisted hard turning (UVAHT) of AISI 52100 steel, several process variables play a crucial role in influencing the machining performance. This process involves identifying the fundamental dimensions (length [L], time [T], mass [M], etc.) and determining the number of dimensionless parameters (Pi terms) required to describe the behavior of the system. By examining the relevant process variables and its corresponding units, one can establish the relationships between the variables and form dimensionless groups. Modelling of Power Consumption (Pc ) After conducting the dimensional analysis, dimensionless groups were formulated to represent the relationships between the relevant process variables. These dimensionless groups provide valuable insights into the interactions between ultrasonic vibration parameters and conventional turning parameters during the UVAHT process. Power consumption is depending on four parameters namely: material removal rate (MRR), density of the material (ρ), vibrational amplitude (A), and frequency of vibration (F). Now by selecting M (mass), L (length), and T (time) as the basic dimensions, the dimensions of the foregoing quantities would then be (table 3). Furthermore, Pc = φ (MRR, ρ, A, F)
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 Ta b l e 3 Dimensional analysis Parameter Representation Power consumption (Pc) (Watt) M1 L2 T-3 Material removal rate (MRR) (mm3/s) M0 L3 T-1 Density of the material (ρ) (kg/m3) M1 L-3 T0 Vibrational amplitude (A) (µm) M0 L1 T0 Frequency of vibration (F) (kHz) M0 L0 T-1 Here, “n” is 5 and “m” is 3 and hence in view of the same, (n-m = 2) i.e., π₁ and π2 are the two dimensionless groups that will be obtained. Now, Taking MRR, ρ and A as the quantities which directly go in π1, and π2 respectively, we obtain: 1 1 1 1 [ ] [ ] [ ] . a b c c MRR A P π = × ρ × × Hence, 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 3 0 0 1 0 2 3 0 0 0 3 1 1 3 1 2 3 (1 0 3 1 1 ) (3 3 2) ( 3) 0 1 0 0 [ ] [ ] [ ] [ ] [ ]; [ ] [ ]; [ . ] a b c a b c b a b c a M L T M L T M LT M L T M L T L T M L L M L T M L M L M T T L T - - - - - + - + + - - - × × × × × × = = = By equality, it can be found that a1 = -3, b1 = -1, and c1 = 4. Hence, we get, 3 1 4 1 [ ] [ ] [ ] . c MRR A P - - π = × ρ × × In similar way, 2 2 2 2 [ ] [ ] [ ] ; a b c MRR A F π = × ρ × × 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 3 1 1 3 0 0 1 0 0 0 1 0 0 0 3 1 1 3 1 0 0 1 (3 3 ) ( 1) 0 0 0 [ ] [ ] [ ]; [ [ ] [ ] ] [ ] [ ]; . a b c a b c b a b c a M L T M L T M L T M LT M L T M L T L T M L L M L T M L T M L T - - - - - - - + - - × × × × = × × = = By equality, it can be found that a2 = -1, b2 = 0, and c2 = 3. Hence, we get, 1 0 3 2 [ ] [ ] [ ] . MRR A F - π = × ρ × × This can now be written as, 1 2 [ ] , n k π = π where k and n are constants. { } 3 1 4 1 3 [ ] [ ] [ ] [ ] [ ] , n c MRR A P k MRR A F - - - × ρ × × = × × where k and n are constants. The material removal rate (MRR) is a product of a cutting speed (V), feed (f), and depth of cut (d). After simplifying the term, the power consumption can be represented as: (3 ) (3 4) ( ) . n n n c P k fd V F A - - = ρ
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 Experiments were performed at constant feed and depth of cut. The density (ρ) of a material is also constant. Therefore, let’s define k1 as a new constant, which is a product of k, ρ, f, and d. Hence, the final model to predict the power consumption under UVAHT is shown below. (3 ) (3 4) 1 . n n n c P k V F A - - = The constant “n” can be obtained by calibrating the model with the experimental power consumption values under UVAHT, obtained at different cutting conditions as depicted in table 2. 1.5987 1.4013 0.2039 0.00222 . c P V F A = (1) Modelling tool wear (Vb ) Tool wear is determined by four parameters: cutting speed (V), material hardness (H), vibrational amplitude (A), and frequency of vibration (F). Using M (mass), L (length), and T (time) as the fundamental dimensions, the dimensions of the previous values will be as follows: given that Vb = φ (V, H, A, F), for “n” is 5, and “m” is 3, and therefore n-m = 2. Thus, π1 and π2, which are two dimensionless groups, can be defined. Now, taking V, H and A as the quantities that are directly included in π1 and π2, respectively, we get 1 1 1 1 [ ] [ ] [ ] . a c b V H A Vb π = × × × Hence, 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 0 1 0 1 0 0 0 0 1 1 1 1 1 1 ( ) ( 1) 0 1 1 2 0 ( 2 ). 0 0 0 2 [ ] [ ] [ ] [ ] [ ]; [ ] [ ] [ ] ; a b c a b c b a b c a b M L T M L T M LT M LT M L T LT M L T L L M L T T T M L M L - - - - + + - - - - - × × × = = × = × × By equality, it can be found that a1 = 0, b1 = 0, and c1 = -1. Hence, we get: 0 0 1 1 [ ] [ ] [ ] . V H A Vb - π = × × × In similar way: 2 2 2 2 [ ] [ ] [ ] ; a b c V H A F π = × × × 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 1 1 0 1 0 1 0 0 0 1 1 1 1 1 1 ( ) ( ) ( 0 2 1) 0 0 0 1 1 2 0 0 2 [ ] [ ] [ ] [ ] [ ]; [ ] [ ] [ ]; . a b c a b c b a b c a b M L T M L T M LT M L T M L T M LT M L T L T M L T M L L T T - - - - - - + - - - - - - × × × × × × = = = By equality, it can be found that a2 = -1, b2 = 0, and c2 = 1. Hence, we get: 1 0 1 1 [ ] [ ] [ ] . V H A F - π = × × × This can now be written as: 1 2 [ ] ; n k π = π { } 1 1 1 [ ] [ ] [ ] . n A Vb k V A F - - × = × × After simplifying the term, it can be represented as: (1 ) ; n n n Vb kV A F - + = 0.1967 0.8033 0.1967 0.011336 . Vb V A F- = (2)
OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 The power consumption and flank wear are plotted using the developed theoretical models, Eqs. 1 and 2, varying the cutting speed, vibration frequency, and amplitude. Fig. 7, a depicts the variation in the power consumption and flank wear with the cutting speed at constant vibration frequency and amplitude of 20 kHz and 20 µm, respectively. a b c Fig. 7. Power consumption and flank wear varying with cutting speed (a), frequency of vibration (b), amplitude of vibration (c) Fig. 7, b depicts the variation in the power consumption and flank wear with the vibration frequency at constant cutting speed and vibration amplitude of 100 m/min and 20 µm, respectively. Fig. 7, c shows the variation in the power consumption and flank wear with the vibration amplitude at constant cutting speed and vibration frequency of 100 m/min and 20 kHz, respectively. The power consumption increases with the cutting speed, vibration frequency, and amplitude. However, an increase in the power consumption can be seen as prominently with the cutting speed followed by vibration frequency, and amplitude. This can be also confirmed from the higher values of the exponent observed for the cutting speed followed by vibration frequency, and amplitude. The flank wear can be seen as increasing with the cutting speed and vibration amplitude and decreasing with the frequency of vibration. Conclusion This study comparatively evaluates the tool wear and power consumption during conventional turning (CT) and ultrasonic vibration-assisted hard turning (UVAHT) of AISI 52100 steel (62 HRC) using a PVD-coated TiAlSiN carbide tool. A theoretical model to predict the tool wear and power consumption is developed using the concept of Dimensional analysis, i.e., the Buckingham Pi theorem considering the effect of cutting speed, frequency, and amplitude of vibrations. Dimensionless groups are created to reveal complex linkages and optimize machining conditions. Tool wear and power consumption are measured experimentally and statistically analysed using the Buckingham Pi theorem. The following conclusion can be drawn from the present study. 1. Tool wear is significantly affected by the cutting speed. How, this effect is more prominent with conventional turning (CT). This could be attributed to an increase in the cutting temperature during cutting.
OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 5 No. 4 2023 However, this effect is less prominent in UVAHT due to intermittent contact of the tool with the workpiece, which allows the tool to cool naturally and hence, lowers tool wear. 2. UVAHT consumes negligibly higher power than CT. Additional power is required in UVAHT to drive the ultrasonic generator, which is not necessary in CT. 3. The tool wear and the power consumption increase with the cutting speed, depth of cut, and feed. However, this effect is more significant in CT than UVAHT. 4. The power consumption increases with the cutting speed, vibration frequency, and amplitude. However, an increase in the power consumption is more prominent with the cutting speed followed by vibration frequency, and amplitude. 5. The flank wear increases with the cutting speed and vibration amplitude and decreases with the frequency of vibration. References 1. Babitsky V.I., Kalashnikov A.N., Meadows A., Wijesundara A.A.H.P. Ultrasonically assisted turning of aviation materials. Journal of Materials Processing Technology, 2003, vol. 132, pp. 157–167. DOI: 10.1016/s09240136(02)00844-0. 2. Babitsky V.I., Mitrofanov A.V., Silberschmidt V.V. Ultrasonically assisted turning of aviation materials: simulations and experimental study. Ultrasonics, 2004, vol. 42, pp. 81–86. DOI: 10.1016/j.ultras.2004.02.001. 3. Vivekananda K., Arka G.N., Sahoo S.K. Design and analysis of ultrasonic vibratory tool (UVT) using FEM, and experimental study on ultrasonic vibration-assisted turning (UAT). Procedia Engineering, 2014, vol. 97, pp. 1178– 1186. DOI: 10.1016/j.proeng.2014.12.396. 4. Liu Y., Li J., Zhang L. Effects of ultrasonic vibration on cutting forces and machined surface quality in turning of AISI 1045 steel. International Journal of Advanced Manufacturing Technology, 2019, vol. 101, pp. 1137–1147. DOI: 10.1038/s41598-022-21236-x. 5. Muhammad R., Maurotto A., Roy A., Silberschmidt V.V. Analysis of forces in vibro-impact and hot vibroimpact turning of advanced alloys. Applied Mechanics and Materials, 2011, vol. 70, pp. 315–320. DOI: 10.4028/ www.scientific.net/AMM.70.315. 6. Lotfi M., Amini S., Akbari J. Surface integrity and microstructure changes in 3D elliptical ultrasonic assisted turning of Ti–6Al–4V: FEM and experimental examination. Tribology International, 2020, vol. 151, p. 106492. DOI: 10.1016/j.triboint.2020.106492. 7. Celaya A., Luis N.N.L., Francisco J.C., Lamikiz A. Ultrasonic Assisted Turning of mild steels. International Journal of Materials and Product Technology, 2010, vol. 37. DOI: 10.1504/IJMPT.2010.029459. 8. Jiao F., Liu X., Zhao C., Zhang X. Experimental study on the surface micro-geometrical characteristics of quenched steel in Ultrasonic Assisted Turning. Advanced Materials Research, 2011, vol. 189–193, pp. 4059–4063. DOI: 10.4028/www.scientific.net/AMR.189-193.4059. 9. MaurottoA., Muhammad R., RoyA., Babitsky V.I., Silberschmidt V.V. Comparing machinability of Ti-15-3-33 and Ni-625 alloys in UAT. Procedia CIRP, 2012, vol. 1, pp. 330–335. DOI: 10.1016/j.procir.2012.04.059. 10. Zou P., Xu Y., He Y., Chen M., Wu H. Experimental investigation of ultrasonic vibration assisted turning of 304 austenitic stainless steel. Shock and Vibration, 2015, art. 817598. DOI: 10.1155/2015/817598. 11. Kumar J., Khamba J.S. Modelling the material removal rate in ultrasonic machining of titanium using dimensional analysis. International Journal of Advanced Manufacturing Technology, 2010, vol. 48, pp. 103–119. DOI: 10.1007/s00170-009-2287-1. 12. Kugaevskii S.S., Ashikhmin V.N. Using local coordinate systems for dimensional analysis in the machining. Proceedings of the 4th International Conference on Industrial Engineering. ISIE 2018. Springer, 2018, pp. 301–309. DOI: 10.1007/978-3-319-95630-5_33. 13. Skelton R.C. Turning with an oscillating tool. International Journal of Machine Tool Design and Research, 1968, vol. 8, pp. 239–259. DOI: 10.1016/0020-7357(68)90014-0. 14. MitrofanovA.V., BabitskyV.I., SilberschmidtV.V. Thermomechanical finite element simulations of ultrasonically assisted turning. Computational Materials Science, 2005, vol. 32, pp. 463–471. DOI: 10.1016/j.commatsci.2004.09.019. 15. Ghule G.S., Sanap S. Ultrasonic vibrations assisted turning (UAT): A review. Advances in Engineering Design: Select proceedings of FLAME 2020. Springer, 2021, pp. 275–285. DOI: 10.1007/978-981-33-4684-0_28. 16. Nath C., Rahman M., Andrew S.S.K. A study on ultrasonic vibration cutting of low alloy steel. Journal of Materials Processing Technology, 2007, pp. 159–165. DOI: 10.1016/j.jmatprotec.2007.04.047.
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