Satish Suresh Chinchanikar
@viit.ac.in
Professor, Department of Mechanical Engineering
Vishwakarma Institute of Information Technology
Satish Chinchanikar is currently working as a Professor at Vishwakarma Institute of Information Technology, India. He received his Ph.D. from the Indian Institute of Technology Kanpur and received a master’s from Pune University. His main research interest is in advanced manufacturing processes and machining of hard alloys using coated tools. He has 25+ years of teaching and Industry experience and published 100+ papers in International Journals and Conferences. He has authored a book chapter on Finish machining of hardened steels published by Elsevier and a textbook on Advanced Manufacturing Processes. He has been awarded an excellent paper certificate at International Conference in Key Engineering Materials in Malaysia. He is working as a reviewer of many peer-reviewed International Journals. He has received 1200+ citations for his work and published to date five Patents and three Copyrights. He strongly believes that teaching and research should go hand in hand.
EDUCATION
Ph.D. (Mechanical Engineering)
RESEARCH INTERESTS
Advance manufacturing processes, Sustainable machining, Hard machining, Friction stir welding, Multi-objective optimization using evolution algorithms
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Satish Chinchanikar, Sourabh Shinde, Avez Shaikh, Vaibhav Gaikwad, and N. H. Ambhore
Springer Science and Business Media LLC
Satish Chinchanikar and Mahendra Gadge
Informa UK Limited
Govind S. Ghule, Sudarshan Sanap, Satish Chinchanikar, Robert Cep, Ajay Kumar, Suresh Y. Bhave, Rakesh Kumar, and Faisal Altarazi
Frontiers Media SA
This study compares conventional turning (CT) and ultrasonic vibration-assisted turning (UVAT) in machining hardened AISI 52100 steel (62 HRC) with a PVD-coated TiAlSiN carbide tool. UVAT experiments, utilizing an ultrasonic frequency of 20 kHz and vibration amplitude of 20 µm, varied the cutting speed, feed, and depth of cut. Remarkably, UVAT reduced tool wear, extending tool longevity. Surprisingly, power consumption showed no significant differences between CT and UVAT. Mathematical models based on experimental data highlight the substantial impact of the cutting speed on tool wear, followed closely by the depth of cut. For power consumption, the depth of cut took precedence, with the cutting speed and feed rate playing pronounced roles in UVAT. This emphasizes the potential for further research on machinability, particularly exploring different vibration directions on the tool in feed, tangential, and radial aspects.
Dhruv Sawant, , Rujuta Bulakh, Vijaykumar Jatti, Satish Chinchanikar, Akshansh Mishra, Eyob Messele Sefene, , , ,et al.
Novosibirsk State Technical University
Introduction. In modern manufacturing world, industries should adapt technological advancements for precision machining of difficult-to-machine metals, especially for beryllium copper (BeCu) alloys. The electrical discharge machining of alloys has proven its viability. The purpose of the work. A literature review indicated that the investigation of electrical discharge machining of BeCu alloys is still in its infancy. Furthermore, the cryogenic treatment of workpieces and electrodes in electrical discharge machining has not received much attention from researchers. Moreover, the impact of magnetic field strength on surface integrity and productivity during electrical discharge machining has not attracted much attention from researchers. The methods of investigation. This paper describes the use of electrolytic copper with different gap current values, pulse on periods, and external magnetic strength for electrical discharge machining of BeCu alloys. This paper examines how the material removal rate, the thickness of the white layer, and the formation of surface cracks are affected by cryogenic treatment of the workpiece and tool, pulse-on time, gap current, and magnetic strength. Results and Discussion. The combination of the cryogenically treated BeCu workpiece and the untreated Cu electrode had the highest material removal rate among all the combinations of workpieces and tools used in this study. The pulse on-time and the strength of the magnetic field had little influence on material removal rate, whereas the gap current had the greatest effect. The maximum achieved material removal rate was 11.807 mm3/min. At a high material removal rate, the observed thickness of the white layer on the horizontal surface ranged from 12.92 µm to 14.24 µm. In the same way, the maximum and minimum values for the vertical surface were determined to be 15.58 µm and 11.67 µm, respectively. According to scanning electron microscopy, the layer thickness was less than 20 µm, and barely noticeable surface cracks were observed in specimens with low, medium and high material removal rates. Obviously, due to the cryogenic processing of the workpiece and the external magnetic strength, there was a slight cracking of the surface and the formation of a white layer.
Ganesh Narkhede, Satish Chinchanikar, Rupesh Narkhede, and Tansen Chaudhari
Emerald
PurposeWith ever-increasing global concerns over environmental degradation and resource scarcity, the need for sustainable manufacturing (SM) practices has become paramount. Industry 5.0 (I5.0), the latest paradigm in the industrial revolution, emphasizes the integration of advanced technologies with human capabilities to achieve sustainable and socially responsible production systems. This paper aims to provide a comprehensive analysis of the role of I5.0 in enabling SM. Furthermore, the review discusses the integration of sustainable practices into the core of I5.0.Design/methodology/approachThe systematic literature review (SLR) method is adopted to: explore the understanding of I5.0 and SM; understand the role of I5.0 in addressing sustainability challenges, including resource optimization, waste reduction, energy efficiency and ethical considerations and propose a framework for effective implementation of the I5.0 concept in manufacturing enterprises.FindingsThe concept of I5.0 represents a progressive step forward from previous industrial revolutions, emphasizing the integration of advanced technologies with a focus on sustainability. I5.0 offers opportunities to optimize resource usage and minimize environmental impact. Through the integration of automation, artificial intelligence (AI) and big data analytics (BDA), manufacturers can enhance process efficiency, reduce waste and implement proactive sustainability measures. By embracing I5.0 and incorporating SM practices, industries can move towards a more resource-efficient, environmentally friendly and socially responsible manufacturing paradigm.Research limitations/implicationsThe findings presented in this article have several implications including the changing role of the workforce, skills requirements and the need for ethical considerations for SM, highlighting the need for interdisciplinary collaborations, policy support and stakeholder engagement to realize its full potential.Originality/valueThis article aims to stand on an unbiased assessment to ascertain the landscape occupied by the role of I5.0 in driving sustainability in the manufacturing sector. In addition, the proposed framework will serve as a basis for the effective implementation of I5.0 for SM.
Paresh Kulkarni and Satish Chinchanikar
Informa UK Limited
Satish Chinchanikar and Mahendra Gadge
Gruppo Italiano Frattura
Machining with a cutting edge with extensive damage or a fractured cutting edge significantly influences the machining performance. Therefore, investigations on tool wear behavior, their forms, and wear mechanisms will be very helpful in the current environment of sustainable manufacturing. On the other hand, the machining economy is negatively impacted by replacing the tool well before its useful life. This proactive maintenance planning reduces the risk of sudden tool failure and potential workpiece damage. Accordingly, the current work creates empirical and ANN models to predict flank wear growth for turning AISI 304 stainless steel using a MTCVD-TiCN/Al2O3 coated carbide tool. The experiments were designed to cover a broad range of operating conditions to ensure the model's accuracy and applicability in practical machining scenarios. An ANN was modeled using a feedforward backpropagation machine learning technique. In this study, a higher prediction accuracy of 0.9975 was achieved with ANN model as compared to the empirical model. The most common wear mechanism observed is metal adhesion, followed by fracture due to the pulling away of adhered material. The developed models have been found to be valuable for optimizing cutting parameters and enhancing tool life in machining.
Avadhoot Rajurkar and Satish Chinchanikar
Informa UK Limited
Satish Chinchanikar, Sourabh Shinde, Vaibahv Gaikwad, Avez Shaikh, Mayur Rondhe, and Mohit Naik
Informa UK Limited
Satish Chinchanikar and Yash Kolte
Informa UK Limited
Govind Ghule, , Sudarshan Sanap, Satish Chinchanikar, , and
Novosibirsk State Technical University
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.
Satish Chinchanikar, , Mahendra Gadge, and
Novosibirsk State Technical University
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 pre-and 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.
Shubham Dhurjad, Avez Shaikh, and Satish Chinchanikar
AIP Publishing
Shivaji S. Gadadhe, Nilesh Diwakar, and Satish Chinchanikar
Seventh Sense Research Group Journals
Paresh Kulkarni and Satish Chinchanikar
Springer Science and Business Media LLC
Avadhoot Rajurkar and Satish Chinchanikar
Springer Science and Business Media LLC
Vaibhav Gaikwad, Satish Chinchanikar, and Omkar Manav
Informa UK Limited
Suhas Prakashrao Patil, Sandeep Sadashiv Kore, Satish Suresh Chinchanikar, and Shital Yashwant Waware
Akademia Baru Publishing
Metal matrix composites (MMCs) are attracting automobile and aeronautical sector because of their superior mechanical and physical characteristics which ultimately reduce the weight of components and hence the energy requirements. These composites are prepared by adding various reinforcements into the base metal by the methods like stir casting, squeeze casting, stir and squeeze casting, sand casting, in-setu method, powder metallurgy etc. When more than one particle is added into the base metal; these composites are called as Hybrid Metal Matrix Composites (HMMCs). The machinability of these hard to cut materials is a challenging task in front of manufacturing industry. Present study considers turning operation of HMMC done on either lathe or CNC machine by using different cutting tool materials. This review focuses on effect of various cutting parameters like speed, depth of cut, feed and also the parameters like reinforcement particle type, particle size and weight percentage on the machinability issues like surface roughness, MRR, cutting forces, tool wear etc. Further the various optimization methods used to suggest the cutting parameters to obtain minimum surface roughness, minimum cutting forces, minimum tool wear and maximum Material Removal Rate (MRR) are addressed.
Avez Shaikh, Sourabh Shinde, Mayur Rondhe, and Satish Chinchanikar
Springer Nature Singapore
Satish Chinchanikar and
Novosibirsk State Technical University
Introduction. Over the last decade, composite materials based on polytetrafluoroethylene (PTFE) have been increasingly used as alternative materials for automotive applications. PTFE is characterized by a low coefficient of friction, hardness and corrosion resistance. However, this material has a high wear rate. A group of researchers attempted to improve the wear resistance of PTFE material by reinforcing it with different fillers. The purpose of the work: This study experimentally investigates the dry sliding wear characteristics of a PTFE composite reinforced with carbon fiber (35 wt.%) compared to SS304 stainless steel. In addition, experimental mathematical and ANN models are developed to predict the specific wear rate, taking into account the influence of pressure, sliding speed, and interface temperature. The methods of investigation. Dry sliding experiments were performed on a pin-on-disk wear testing machine with varying the normal load on the pin, disk rotation, and interface temperature. Experiments were planned systematically to investigate the effect of input parameters on specific wear rates with a wide range of design space. In total, fifteen experiments were carried out at a 5-kilometer distance without repeating the central run experiment. Sliding velocities were obtained by selecting the track diameter on the disk and corresponding rotation of the disk. A feedforward back-propagation machine learning algorithm was used to the ANN model. Results and Discussion. This study finds better prediction accuracy with the ANN architecture having two hidden layers with 150 neurons on each layer. This study finds an increase in specific wear rates with normal load, sliding velocity, and interface temperature. However, the increase is more prominent at higher process parameters. The normal load followed by sliding velocity most significantly affects the specific wear rate. The results predicted by the developed models for specific wear rates are in good agreement with the experimental values with an average error close to 10%. This shows that the model could be reliably used to obtain the wear rate of PTFE composite reinforced with carbon fiber (35 wt.%) compared to SS304 stainless steel. This study finds scope for further studies considering the effect of varying ANN architectures, different amount of neurons, and hidden layers on the prediction accuracy of the wear rate.
Avadhoot Rajurkar and Satish Chinchanikar
Springer Science and Business Media LLC
The machining of superalloys being challenging is continuously evolving due to development in cutting tool technology and tool materials. This study comparatively evaluates through mathematical models the machining performance of nanosecond fiber laser-processed micro-dimple and micro-channel textured carbide tools having average diameter/width and depth of 80 and 70 µm, respectively, during dry turning of Inconel 718. This study finds mixed results with both the micro-textured tools. Micro-channel textured tools showed notable improvement in tool life up to 60% over micro-dimple textured tools at lower cutting speeds. However, we found almost the same tool life with both tools at higher cutting speeds. Micro-dimple textured tools produced a better surface finish and lower cutting forces. However, micro-channel textured tools produced a better surface finish at higher cutting speeds. EDS analysis and subsequent elemental mapping affirm a strong adhesion of chip particles and debris on micro-textured tools leading to quick failure of tools. However, this effect was more prominent for micro-dimple textured tools. This study concludes that micro-channel textured tools are the better alternative for dry turning of Inconel 718. However, we find scope for the machinability studies of Inconel 718 with hybrid micro-textured patterns on the rake and flank surfaces.
N Deshmukh, S Chinchanikar, C Garde, A Kulkarni, S Garode, T Lindner, A Konaka, and M Hartz
IOP Publishing
Approximately 500 multi-PMTs (mPMTs) will be used as the photosensors for the Intermediate Water Cherenkov Detector (IWCD), a new near detector for the approved Hyper-Kamiokande experiment that will be built by 2025. The IWCD mPMT design has nineteen 3” PMTs enclosed in a water-tight pressure vessel, along with the associated electronics. The 3” PMTs provide excellent spatial imaging of the neutrino-induced Cherenkov light ring. This work will focus on the mechanical design of the mPMT vessel. In particular, design of the acrylic dome, use of optical gel to couple the dome to the PMTs, assembly procedures of dome and PMT sub-assembly (including the necessary jigs / fixtures), design of water-tight feed-through & plans for testing and results from several mPMT prototypes.