Satish Suresh Chinchanikar

Scopus Publications

Sustainability evaluation using an eco-index for Inconel 718 EDM with a hybrid al2 o3-graphene nano-dielectric fluid
Paresh Kulkarni, Satish Chinchanikar
Obrabotka Metallov, 2026
Introduction. Environmentally sustainable machining is crucial to improve the manufacturing sector's cost-effectiveness and resource efficiency while mitigating its negative environmental impact. The “eco-index” is a multi-criteria metric that assesses the sustainability of the electrical discharge machining (EDM) of Inconel 718 by quantifying its total environmental and economic impact using a normalized and weighted approach. The purpose of this work is to describe the eco-index for Inconel 718 EDM, which assesses sustainability through environmental indicators such as energy and material consumption, waste generation, emissions, and toxicity, as well as economic indicators including operating and disposal costs along with productivity metrics. However, there are limited studies on sustainability evaluation using the eco-index for Inconel 718 EDM processed with a hybrid nano-dielectric fluid. The methods of investigation. This study investigates the machining performance and environmental sustainability of the EDM process of Inconel 718 using a hybrid nanoparticle-mixed dielectric fluid. A hybrid nano-dielectric fluid was prepared by dispersing Al2O3 and graphene nanoparticles in an equal proportion (total concentration of 0.1%) in EDM oil using a two-step method involving SDS as a surfactant, magnetic stirring, and ultrasonication to ensure a stable suspension. Experiments were conducted on an EDM machine with a copper electrode by varying the pulse on-time (50–150 µs), peak current (3–10 A), and discharge voltage (40–50 V). Key performance responses, including material removal rate (MRR), surface roughness (Ra), tool wear rate (TW), hole cylindricity (ρ), energy consumption (E), and a weighted eco-index (EI), were evaluated to quantify the combined productivity, quality, and sustainability performance. Results and Discussion. The results demonstrate that the hybrid nano-dielectric fluid improves overall EDM efficiency compared to conventional EDM oil by promoting stable discharge behaviour, enhanced heat transfer, and efficient debris flushing, which increases MRR, improves surface finish, reduces tool wear, enhances the cylindricity of the machined hole, and lowers energy consumption, leading to a higher eco-index across most machining conditions. Surface integrity analysis using SEM revealed a substantial reduction in recast layer thickness, which decreased from 17.05 µm (base oil) to 3.91 µm (hybrid nano-dielectric fluid), indicating reduced thermal damage and resolidification. EDX further confirmed nanoparticle involvement through carbon enrichment (graphene deposition) and Al–O signatures (alumina contribution), supporting the proposed mechanisms for improved plasma stability and reduced metallic redeposition. Overall, the hybrid Al2O3–graphene nano-dielectric fluid provides an effective and sustainable approach for the EDM of Inconel 718 by balancing precision, productivity, and environmental efficiency.
Evaluation of flank wear of a self-propelled rotary tool during turning using nanofluid under MQL
Nitin Motgi, Satish Chinchanikar, Ashok Mache, Paresh Kulkarni
EPJ Web of Conferences, 2026
Inconel 718, a heat-resistant nickel alloy, is employed in aerospace, marine, and defence applications due to its unique properties. However, these alloys are difficult to cut due to their low heat conductivity and proclivity for work-hardening. With a focus on sustainability, ongoing efforts are underway to enhance the manufacturability of these alloys. This study assesses the flank wear progression of a self-propelled rotary tool (SPRT) while turning Inconel 718 using a hybrid nanofluid under minimum quantity lubrication (NFMQL) conditions. To create a hybrid nanofluid, multi-walled carbon nanotubes (MWCNTs) and aluminium oxide (Al2O3) nanoparticles were mixed with 0.25% in a commercially available palm oil. Experiments were carried out by changing the process parameters. Flank wear was monitored and analysed with digital and electron microscopes. Experimental-based models were created to analyse and compare the influence of cutting conditions and machining time on SPRT flank wear under NFMQL conditions. Additionally, an ANN model is created to predict how flank wear will change over time. To provide precise forecasts, the ANN model makes use of past tool wear rate data. Lastly, the processes of tool wear for SPRTs under NFMQL are investigated.
Machinability of stir-cast Al7075-based hybrid nanocomposites under dry and compressed-air cooling conditions
Suhas Patil, Satish Chinchanikar, Paresh Kulkarni, Sandeep Kore, Nitin Ambhore
EPJ Web of Conferences, 2026
In this study, the machinability of the stir-cast Al7075-based hybrid nanocomposites is evaluated during turning under dry and compressed air-cooling conditions. Based on experimental findings, mathematical models were created that can forecast the machining performances, namely cutting force, surface roughness, and flank wear. Using the ANOVA technique, the impact of different Al7075-based hybrid nanocomposites and cutting parameters, specifically, cutting speed, feed, and depth of cut, on various responses was examined. According to experimental findings, higher cutting forces and lower surface roughness were obtained while turning harder Al7075-based nanocomposites. Under compressed air machining conditions, the surface roughness, cutting force, and flank wear were observed to decrease by 4.74%, 8.84% and 43.59% respectively. The flank wear analysed for different cutting conditions showed a substantial reduction in the flank wear while turning under compressed air-cooling conditions. Moreover, lower flank wear could also be attributed to the displacement of the abrasive particles from the cutting edge. The chip morphology is studied for the various cutting conditions as well as different machining environments. SEM analysis was carried out to compare the surface texture of the chips produced under dry and compressed air conditions.
Turning Inconel 718 with a self-propelled rotary tool using a hybrid nanofluid under minimum quantity lubrication
Satish Chinchanikar, Nitin Motgi
Obrabotka Metallov, 2026
Introduction. Superalloys like nickel ones are crucial in aircraft construction, rocket production, and, more broadly, in the aviation industry due to their hard-wearing, and high-strength properties, but high machining temperatures pose challenges to their machinability. Manufacturers are always looking for new ways to improve these materials' machinability using cutting-edge cutting tool technologies and suitable cooling methods. In this context, rotary tools have shown significant potential for better performance in machining challenging materials. The purpose of the work. It is essential to comprehend geometric dimensioning and tolerance (GD&T) parameters when machining aerospace alloys to ensure precision and interchangeability in parts manufacturing. However, limited studies have investigated these parameters while considering the effect of nanofluids during turning with rotary tools. Methods of investigation. This study explores the turning of Inconel 718 with a hybrid nanofluid under minimum quantity lubrication (NFMQL) conditions using a self-propelled rotary tool (SPRT). Nanofluids were prepared by mixing Al₂O₃ and multi-walled carbon nanotubes in palm oil. The analysis of worn tools was performed through optical and SEM images. Further, the radial GD&T parameters, such as circularity, cylindricity, radial runout, surface roughness, tool life, and workpiece hardness, are discussed as they vary with the cutting conditions. Additionally, the technique for order of preference by similarity to the ideal solution (TOPSIS) in association with a genetic algorithm (GA) was used to generate Pareto solutions and select the optimal compromise solution. The work with the optimized parameters is finally summarized. Results and Discussion. A hybrid nanofluid under NFMQL conditions was used to assess the processability of Inconel 718 during turning with an SPRT. The circularity, cylindricity, radial runout, and machined surface characteristics were investigated. The worn tools have been examined through optical and scanning electron microscopy images. Surface roughness and tool life are significantly affected by feed and cutting speed, while cylindricity is strongly impacted by the depth of cut. Pareto fronts and the best compromise solutions were obtained using a genetic algorithm integrated with TOPSIS. This study found that turning Inconel 718 at a feed rate and depth of cut of 0.1 mm/rev and 0.2 mm, respectively, and a cutting speed between 30–60 m/min could achieve circularity and cylindricity deviations of up to 5.68 µm and radial runout of up to 0.43 mm, as well as surface roughness, tool life, and workpiece hardness in the ranges of 1.07–1.54 µm, 3.46–8.44 min, and 36–38 HRC, respectively. This research provides valuable insights for designing an SPRT and promoting its wide adoption and application in the machining domain for machining superalloys. This study suggests exploring nanoparticle agglomeration in nanofluids and the use of additives to improve machining efficiency. Additionally, this research identifies opportunities to enhance machining performance under NFMQL conditions by utilizing micro-textured SPRTs with nanofluids, addressing concerns related to machined surface integrity.
Modeling Chip Thickness Ratio and Shear Angle Using Hybrid Nanofluids While Machining Inconel 718 Under Minimum Quantity Lubrication
Paresh Vijay Kulkarni, Satish Suresh Chinchanikar, Maheshwar Jaybhaye
Lecture Notes in Mechanical Engineering, 2026
Investigating Chip Morphology and Surface Roughness Under Dry and Wet Turning Using Sunflower Oil
Mahendra Gadge, Praveen Rathod, Satish Chinchanikar, Abdullah Alqammaz, Neeraj Sunheriya, Jayant Giri, Rajkumar Chadge
Studies in Systems Decision and Control, 2026
ANFIS modeling of turning Al7075 hybrid nanocomposites under compressed air cooling
, Satish Chinchanikar, Suhas Patil, , Paresh Kulkarni, and
Obrabotka Metallov, 2025
Introduction. Hybrid metal matrix composites (HMMCs) are increasingly used in the aviation and automotive industries due to their low density, high stiffness, and exceptional specific strength. Among aluminum MMCs, Al7075-based composites are gaining wider acceptance. Continuous research and development in this field focuses on improving the durability and performance of these advanced materials. Purpose of the work. Machinability of Al7075 is a significant challenge because the abrasive reinforcement phase causes rapid tool deterioration, increased machining forces, and a poor surface finish. Moreover, the industrial focus on green manufacturing has led to a shift from traditional coolant-based machining to sustainable alternatives. In this context, researchers have optimized machining performance using advanced technological advancements and techniques. However, limited work is reported on modeling the machining performance of Al7075 nanocomposites during turning under compressed air cooling. Methods of investigation. Manufacturers can gain a better understanding of increasing the effectiveness of turning processes for Al7075 nanocomposites by creating a comprehensive model. Therefore, this work models the machining performance of hybrid Al7075 nanocomposites during turning under compressed air-cooling conditions with an artificial neuro-fuzzy inference system (ANFIS) to predict tool wear (TW), surface roughness (Ra), and cutting force (Fc) as a function of process parameters. Results and discussion. In this work, an ANFIS model was developed to predict the machining performance considering the effect of process parameters such as cutting speed, feed rate, and depth of cut for different Al7075-based nanocomposites. These nanocomposites were prepared using silicon carbide (30–50 nm) and graphene (5–10 nm) nanoparticles as reinforcements by the stir casting process. Reinforcement materials affect the mechanical and physical properties of composites. For engineering applications, SiC and graphene are preferred reinforcements with distinctive features. ANFIS models were developed to predict Ra, Fc, and TW based on the experimental results. The Sugino method was used to represent fuzzy rules and membership functions, as it utilizes weighted averages in the defuzzification process and offers better processing efficiency. The MATLAB ANFIS toolbox was used to design and tune fuzzy inference systems. The developed ANFIS model predicts machining responses effectively and offers a practical approach for optimizing process parameters with high reliability. The results of this research show good agreement between the experimental results and the predicted ANFIS outcomes, with an average prediction error below 8%. Specifically, the ANFIS model yielded errors of 5.1% for Ra, 13.45% for Fc, and 7.92% for TW. The model exhibited excellent agreement with experimental data, demonstrating high prediction accuracy and generalization capability. 3-D graphs are plotted for a better understanding of the effect of process parameters on Fc, Ra, and TW for different nanocomposites. The findings affirm the efficacy of compressed air cooling in improving machinability while minimizing environmental impact. Furthermore, the developed ANFIS model serves as a reliable tool for optimizing turning parameters for Al7075 composites, supporting the advancement of green manufacturing strategies. This research warrants further investigation into the application of ANFIS in machining processes, specifically exploring various metal matrix composite types and rigorously assessing the long-term effects of compressed air cooling on both environmental sustainability and tool life.
Investigation on the mechanical properties of stir-cast Al7075-T6-based nanocomposites with microstructural and fractographic surface analysis
, Suhas Patil, Satish Chinchanikar, and
Obrabotka Metallov, 2025
Introduction. Aluminum-based metal matrix composites (MMCs) have garnered considerable attention recently due to their enhanced mechanical properties, making them suitable for a wide range of industrial applications. While other methods exist for incorporating reinforcements into the base metal, stir casting is a particularly efficient process as it promotes a more uniform distribution of reinforcement particles throughout the matrix. The purpose of this work. It has been demonstrated that adding silicon carbide (SiC) reinforcements to alloys from the 7XXX series enhances their fatigue strength. The impact of SiC reinforcements on the mechanical properties of A356 composites, such as elongation, compressive strength, tensile strength, and hardness, has also been investigated. However, there is a need for more research on how hybrid reinforcement particles affect the mechanical properties of Al7075-T6 alloy. Methods. Considering the broad application spectrum of aluminum matrix composites (AMCs) in the automotive and aerospace sectors, this study examines the influence of varying ratios of nano-sized SiC and graphene reinforcements on the hardness and tensile strength of stir-cast Al7075-T6 aluminum alloy. The scanning electron microscopy — energy-dispersive X-ray spectroscopy (SEM-EDS) analysis of the composites' microstructural and fractographic surfaces is also included. The objectives of this work are to develop lightweight, high-performance hybrid metal matrix nanocomposite materials and to explore the feasibility of integrating graphene and SiC nanoparticles into Al7075 alloy. Particular emphasis is placed on the discussion of the mechanical characteristics of these hybrid materials. Results and discussion. This study found that mechanical stirring improved the bonding, wetting, and cohesion between the reinforcements and matrix while reducing porosity. Compared to composites produced without stirring, stirred composites exhibited improved strength and toughness due to microstructural changes. The study suggests that appropriate mixing strategies can significantly impact the mechanical properties and surface morphology of Al7075 nanocomposites. The results indicated that the hybrid reinforcement nanoparticles significantly improved both the hardness and tensile strength of the Al7075-T6 alloy. Moreover, a distinct correlation between the ratio of silicon carbide to graphene nanoparticles and the mechanical properties of the specimens was observed. Specifically, an Al7075 specimen reinforced with 0.5 wt.% graphene and 3 wt.% silicon carbide nanoparticles demonstrated superior hardness and tensile strength compared to unreinforced Al7075 and other combinations of silicon carbide and graphene nanoparticles considered in this study. With a 0.5 wt.% graphene content and 1–3 wt.% SiC content, the Al7075-based nanocomposites consistently exhibited a well-defined grain structure with distinct, continuous grain boundaries. The resulting finely dispersed nanoparticles, ranging in size from 62.57 to 91.54 nm, facilitated effective load transfer, grain refinement, and impeded dislocation motion, leading to enhanced mechanical properties. An Al7075-based nanocomposite exhibited superior mechanical performance characterized by a dense, dimpled surface featuring uniform microvoids and minimal particle pull-out. This behavior was attributed to ductile fracture resulting from strong matrix-reinforcement bonding and efficient load transfer. Consistent with these observations, the study indicates that the mechanical behavior of hybrid Al7075-based nanocomposites is significantly influenced by the reinforcement ratio, particle size, and dispersion quality. This information is valuable for advanced industrial applications. The study further demonstrates that a balanced combination of graphene and silicon carbide nanoparticle reinforcements can enhance the mechanical properties of Al7075, emphasizing the need for further investigation into these synergistic effects.
Cutting force modeling during turning Inconel 718 using unitary Al2O3 and hybrid MWCNT + Al2O3 nanofluids under minimum quantity lubrication
Paresh Kulkarni, Satish Chinchanikar
International Journal on Interactive Design and Manufacturing, 2025
Machinability of Inconel 718 using unitary and hybrid nanofluids under minimum quantity lubrication
Paresh Kulkarni, Satish Chinchanikar
Advances in Materials and Processing Technologies, 2025
In the current study, unitary and hybrid nanofluids are used with minimal lubrication to examine Inconel 718's machinability. Nanofluids are obtained by dispersing unitary and mixed amounts of aluminium oxide, multi-walled carbon nanotubes, and graphene nanoparticles into palm oil. Initially, turning experiments were performed with pure palm oil and different unitary and hybrid nanofluids using differently coated carbide tools to obtain the best combination of the type of nanofluid(s) and coated tool for the lowest tool wear. Further, the cutting forces, surface roughness, chip thickness ratio, chip morphology, and shear angle were obtained, varying with the cutting parameters for the best combination of nanofluid(s) and the tool. The analysis of worn-out tools has been performed through images captured using optical and scanning electron microscopes. The study indicates that aluminium titanium nitride-coated tools outperform titanium aluminium nitride-coated tools with hybrid aluminium oxide and multi-walled carbon nanotube-based nanofluid, followed by a unitary aluminium oxide-based nanofluid. It could be attributed to the higher thermal conductivity and surface tension of aluminium oxide nanoparticles and the better lubricating and cooling capabilities of multi-walled carbon nanotubes. Comparatively lower performance was observed with graphene-based nanofluid due to severe agglomeration that adversely affected the homogeneity of the fluid.
EXPERIMENTAL INVESTIGATION AND DEVELOPMENT OF NOVEL FLAME-RETARDANT COMPOSITES FOR MICROGRAVITY ENVIRONMENT
Shravani Tembare, Satish Chinchanikar
Microgravity Science and Experiments Held at the Global Space Exploration Conference Glex 2025, 2025
Machinability studies with radial GD&T parameters during turning inconel 718 using a custom-designed self-propelled rotary tool: a GA-TOPSIS multi-objective optimisation approach
Satish Chinchanikar, Nitin Motgi
Advances in Materials and Processing Technologies, 2025
Modelling cutting force for turning AISI 304 stainless steel with PVD-AlTiN coated, PVD-AlTiN coated-microblasted, and MTCVD-TiCN/Al2O3 coated tools
Satish Chinchanikar, Mahendra Gadge
Advances in Materials and Processing Technologies, 2025
Design and Optimization of Railway Power Axle System for Structural Safety
Praveen Rathod, Satish Chinchanikar, Mahendra Gadge
Lecture Notes in Mechanical Engineering, 2025
Investigation on the effect of laser parameters and hatch patterns on the dimensional accuracy of micro-dimple and micro-channel texture geometries
Avadhoot Rajurkar, Satish Chinchanikar
International Journal on Interactive Design and Manufacturing, 2024
A review of emerging hydroforming technologies: design considerations, parametric studies, and recent innovations
Satish Chinchanikar, Harsh Mulik, Param Varude, Sameer Atole, Neha Mundada
Journal of Engineering and Applied Science, 2024
Modeling turning performance of Inconel 718 with hybrid nanofluid under MQL using ANN and ANFIS
Paresh Kulkarni, Satish Chinchanikar
Frattura Ed Integrita Strutturale, 2024
Comparative evaluation of roller burnishing of Al6061-T6 alloy under dry and nanofluid minimum quantity lubrication conditions
, Avinash Somatkar, , Rashmi Dwivedi, , Satish Chinchanikar, and
Obrabotka Metallov, 2024
Modeling and optimization of roller burnishing of Al6061-T6 process for minimum surface roughness, better microhardness and roundness
, Rashmi Dwivedi, Avinash Somatkar, , , Satis Chinchanikar, and
Obrabotka Metallov, 2024
Investigations on ultrasonic vibration-assisted friction stir welded AA7075 joints: Mechanical properties and fracture analysis
, Vaibhav Gaikwad, Satish Chinchanikar, and
Obrabotka Metallov, 2024
Multi-objective Optimization of FDM Using Hybrid Genetic Algorithm-Based Multi-criteria Decision-Making (MCDM) Techniques
Satish Chinchanikar, Sourabh Shinde, Avez Shaikh, Vaibhav Gaikwad, N. H. Ambhore
Journal of the Institution of Engineers India Series D, 2024
A Review on Self-propelled Rotary Tools: A Comparative with Fixed-Tool Machining, Modeling, Design, and Developments
Nitin Motgi, Satish Chinchanikar
Lecture Notes in Mechanical Engineering, 2024
A review on experimental and numerical studies on micro deep drawing considering size effects and key process parameters
Satish Chinchanikar, Yash Kolte
Australian Journal of Mechanical Engineering, 2024
Investigations on tool wear behavior in turning AISI 304 stainless steel: An empirical and neural network modeling approach
Satish Chinchanikar, Mahendra Gadge
Frattura Ed Integrita Strutturale, 2024
Machining effects and multi-objective optimization in Inconel 718 turning with unitary and hybrid nanofluids under MQL
Satish Chinchanikar, Paresh Kulkarni
Frattura Ed Integrita Strutturale, 2024
Investigations on homothetic and hybrid micro-textured tools during turning Inconel-718
Avadhoot Rajurkar, Satish Chinchanikar
Materials and Manufacturing Processes, 2024
Investigation on polyvinyl butyral interlayered and ultrasonic vibration-assisted friction stir welded AA7075-T651 joints
Advances in Materials Research South Korea, 2024
Investigation on Tool Life and Resultant Force During Turning of Hardened EN24 Steel Using Multilayer Coated Carbide Tool
Satish Chinchanikar, Ganesh Narkhede, Shubham Sasane
Lecture Notes in Mechanical Engineering, 2024
Enhancing Surface Integrity and Quality through Roller Burnishing: A Comprehensive Review of Parameters Optimization, and Applications.
Avinash A. Somatkar
Communications on Applied Nonlinear Analysis, 2024
Comparative Evaluation of Modal and Harmonic Analysis of Stepped Horn for Ultrasonic Vibration Assisted Turning
Vijay Kumar S Jatti, Vinay Kumar S. Jatti, Savita V. Jatti, Pawandeep Dhall, Satish Chinchanikar
Smart Innovations and Technological Advancements in Civil and Mechanical Engineering, 2024
Smart Innovations and Technological Advancements in Civil and Mechanical Engineering
Satish Chinchanikar, Ashok Mache, Shardul G. Joshi, Preeti Kulkarni
Smart Innovations and Technological Advancements in Civil and Mechanical Engineering, 2024
Role of Industry 5.0 for driving sustainability in the manufacturing sector: an emerging research agenda
Ganesh Narkhede, Satish Chinchanikar, Rupesh Narkhede, Tansen Chaudhari
Journal of Strategy and Management, 2024
Investigating Cutting Forces During Hard Turning of EN 24 Steel: A Comparative Evaluation of MQL and Dry Cutting
Satish Chinchanikar, Om Kulkarni, Pushkar Dhond, Mohit Kumawat, Shivam Chaudhari
Lecture Notes in Mechanical Engineering, 2024
Electrical Discharge Machining Process Optimization During Machining of EN19 Alloy Steel Using Desirability Concept
M. B. Kulkarni, R. Kumbhakarna, D. S. Bhutada, Bhushan Hazare, S. Thorat, S. Radhakrishnan, Y. S. Munde
Smart Innovations and Technological Advancements in Civil and Mechanical Engineering, 2024
Investigation on the electrical discharge machining of cryogenic treated beryllium copper (BeCu) alloys
Dhruv Sawant, , Rujuta Bulakh, Vijaykumar Jatti, Satish Chinchanikar, Akshansh Mishra, Eyob Messele Sefene, , , , , , and
Obrabotka Metallov, 2024
A Comparative Analysis of Machining Performance During Turning SS304 Stainless Steel Under Dry and Compressed Air Cooling Conditions
Nityam Gangji, Imran Maniyar, Rohit Jaiswal, Prem Gangurde, Utkarsh Dhavad, Satish Chinchanikar
Lecture Notes in Mechanical Engineering, 2024
ANN modelling of surface roughness of FDM parts considering the effect of hidden layers, neurons, and process parameters
Satish Chinchanikar, Sourabh Shinde, Vaibahv Gaikwad, Avez Shaikh, Mayur Rondhe, Mohit Naik
Advances in Materials and Processing Technologies, 2024
Investigation of Chip Thickness and Shear Angle During Turning AISI 304 Stainless Steel
Rohan Nirwal, Satish Chinchanikar, Mahendra Gadge, Soummya Tembhurne, Rohit Thakare, Harshal Bhatkar
Lecture Notes in Mechanical Engineering, 2024
Green Manufacturing: A Global Perspective
Shantanu Patil, Pavankumar Jadhav, Dhiraj Shinde, Shubham Pawar, Rupesh Pawar, Satish Chinchanikar
Lecture Notes in Mechanical Engineering, 2024
Investigation of conventional and ultrasonic vibration-assisted turning of hardened steel using a coated carbide tool
Govind S. Ghule, Sudarshan Sanap, Satish Chinchanikar, Robert Cep, Ajay Kumar, Suresh Y. Bhave, Rakesh Kumar, Faisal Altarazi
Frontiers in Mechanical Engineering, 2024
Performance modeling and multi-objective optimization during turning AISI 304 stainless steel using coated and coated-microblasted tools
Satish Chinchanikar, , Mahendra Gadge, and
Obrabotka Metallov, 2023
Ultrasonic vibration-assisted hard turning of AISI 52100 steel: comparative evaluation and modeling using dimensional analysis
Govind Ghule, , Sudarshan Sanap, Satish Chinchanikar, , and
Obrabotka Metallov, 2023
Generative design for additive manufacturing (G-DFAM): An explorative study of aerospace brackets
Shubham Dhurjad, Avez Shaikh, Satish Chinchanikar
Aip Conference Proceedings, 2023
Experimental Investigations and Simulation of Solar-Powered Reverse Osmosis Water Desalination System using CFD
Shivaji S. Gadadhe, Nilesh Diwakar, Satish Chinchanikar
International Journal of Engineering Trends and Technology, 2023
A Review on Machining of Nickel-Based Superalloys Using Nanofluids Under Minimum Quantity Lubrication (NFMQL)
Paresh Kulkarni, Satish Chinchanikar
Journal of the Institution of Engineers India Series C, 2023
Mechanical properties, microstructure, and fracture behavior of friction stir welded AA7075 joints with conical pin and conical threaded pin type tools
V. S. Gaikwad, Satish Chinchanikar
Scientia Iranica, 2023
Investigation and multi-objective optimization of friction stir welding of AA7075-T651 plates
Vaibhav Gaikwad, Satish Chinchanikar, Omkar Manav
Welding International, 2023
Machine Learning Techniques for Smart Manufacturing: A Comprehensive Review
Avez Shaikh, Sourabh Shinde, Mayur Rondhe, Satish Chinchanikar
Lecture Notes in Mechanical Engineering, 2023
Characterization and Machinability Studies of Aluminium-based Hybrid Metal Matrix Composites – A Critical Review
Suhas Prakashrao Patil, Sandeep Sadashiv Kore, Satish Suresh Chinchanikar, Shital Yashwant Waware
Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 2023
A Review on Machine Learning, Big Data Analytics, and Design for Additive Manufacturing for Aerospace Applications
Satish Chinchanikar, Avez A. Shaikh
Journal of Materials Engineering and Performance, 2022
Modeling of sliding wear characteristics of Polytetrafluoroethylene (PTFE) composite reinforced with carbon fiber against SS304
Satish Chinchanikar and
Obrabotka Metallov, 2022
Adaptive Neuro Fuzzy Inference System to Predict the Mechanical Properties of Friction Stir Welded AA7075-T651 Joints
Jordan Journal of Mechanical and Industrial Engineering, 2022
Experimental Investigation on Laser-Processed Micro-Dimple and Micro-Channel Textured Tools during Turning of Inconel 718 Alloy
Avadhoot Rajurkar, Satish Chinchanikar
Journal of Materials Engineering and Performance, 2022
Multi-objective Optimization of Turning of Titanium Alloy Under Minimum Quantity Lubrication
Journal of Optimization in Industrial Engineering, 2022
Mechanical behaviour of friction stir welded AA7075-T651 joints considering the effect of tool geometry and process parameters
Vaibhav S. Gaikwad, Satish Chinchanikar
Advances in Materials and Processing Technologies, 2022
Investigation of tool forces, weld bead micro-hardness and surface roughness during friction stir welding of Aluminium 6063 alloy
Satish Chinchanikar, Swaroop Gharde, Mahendra Gadge
Advances in Materials and Processing Technologies, 2022
A review on micro-blasting as surface treatment technique for improved cutting tool performance
Mahendra Gadge, Gaurav Lohar, Satish Chinchanikar
Materials Today Proceedings, 2022
Effect of Voxel-Based Surface Mesh Size on Process Simulation for Metal Additive Manufacturing of Ti6Al4V Impeller of Centrifugal Compressor
Avez Shaikh, Ajinkya Shinde, Satish Chinchanikar, Tanmay Deshpande
Lecture Notes in Mechanical Engineering, 2022
A review on acoustic performance analysis of reactive muffler
Shubham Chivate, Pravin Hujare, Rajesh Askhedkar, Deepak Hujare, Satish Chinchanikar
Materials Today Proceedings, 2022
Analysis of cutting temperature during turning of SS 304 using uncoated and PVD coated carbide inserts
Atul Kulkarni, Nitin Ambhore, Abhijeet Deshpande, Prashant Anerao, Satish Chinchanikar
Materials Today Proceedings, 2022
Experimental investigations of conical perforations on the thermal performance of cylindrical pin fin heat sink
Sandeep S. Kore, Rupesh Yadav, Satish Chinchanikar, Pralhad Tipole, Vishal Dhole
International Journal of Ambient Energy, 2022
Experimental investigations on the ultrasonic vibration-assisted hard turning of AISI 52100 steel using coated carbide tool
Govind S. Ghule, Sudarshan Sanap, Sanjay Adsul, Satish Chinchanikar, Mahendra Gadge
Materials Today Proceedings, 2022
Mechanical design of multi-PMTs for IWCD
N Deshmukh, S Chinchanikar, C Garde, A Kulkarni, S Garode, T Lindner, A Konaka, M Hartz
Journal of Physics Conference Series, 2022
Mechanical design of water cherenkov test experiment (WCTE) at CERN
S V Garode, S S Chinchanikar, C S Garde, A R Mache, S G Joshi, N Deshmukh, P Patil, A Konaka, M Hartz
Journal of Physics Conference Series, 2022
Dimensional analysis and ANN simulation of chip-tool interface temperature during turning SS304
Atul Kulkarni, , Satish Chinchanikar, Vikas Sargade, , and
Obrabotka Metallov, 2021
A review on nanofluids in minimum quantity lubrication machining
Satish Chinchanikar, S.S. Kore, Pravin Hujare
Journal of Manufacturing Processes, 2021
State of the art in friction stir welding and ultrasonic vibration-assisted friction stir welding of similar/dissimilar aluminum alloys
S. Chinchanikar, Vaibhav S. Gaikwad
Journal of Computational and Applied Research in Mechanical Engineering, 2021
Investigation on surface roughness, ultimate tensile strength, and microhardness of friction stir welded AA7075-T651 joint
Vaibhav S. Gaikwad, Satish Chinchanikar
Materials Today Proceedings, 2021
Characterization of pre-and/or post-treated PVD-AlTiN coating: Nanohardness, modulus of indentation and percent elastic portion of the nanoindentation
Mahendra Gadge, Satish Chinchanikar
Materials Today Proceedings, 2021
Performance study of dimple and channel textured tools during turning of Inconel-718
Avadhoot Rajurkar, Satish Chinchanikar
Materials Today Proceedings, 2021
Sliding wear characteristics of carbon filled polytetrafluoroethylene (Ptfe) composite against aisi 304 stainless steel counterface
Satish Chinchanikar, Amol Barade, Abhijeet Deshpande
Materials Science Forum, 2021
Investigation of electric discharge machining processes parameters on material removal rate, tool wear rate and surface roughness during machining of EN19
Vaibhav S. Gaikwad, Vijaykumar S. Jatti, Satish S. Chinchanikar, Keshav N. Nandurkar
Materials Today Proceedings, 2021
Dry sliding wear characteristics of carbon filled polytetrafluoroethylene (PTFE) composite against Aluminium 6061 alloy
Anamol Sonawane, Abhijeet Deshpande, Satish Chinchanikar, Yashwant Munde
Materials Today Proceedings, 2021
Thermal modeling of laser surface micro-texturing: Investigation on effects of laser parameters on dimple-texture dimensions and aspect ratio
Niranjan Deshmukh, Avadhoot Rajurkar, Omkar Kolekar, Radhika Mule, Satish Chinchanikar
Materials Today Proceedings, 2021
Evaluation of Cutting Tool Vibration and Surface Roughness in Hard Turning of AISI 52100 Steel: An Experimental and ANN Approach
Nitin Ambhore, Dinesh Kamble, Satish Chinchanikar
Journal of Vibration Engineering and Technologies, 2020
Experimental analysis of different shaped ribs on heat transfer and fluid flow characteristics
Sandeep S Kore, Sunil V. Dingare, Satish Chinchanikar, Pravin Hujare, Ashok Mache
E3s Web of Conferences, 2020
Comparative evaluation of machining performance of inconel 625 under dry and cryogenic cutting conditions
G B Narkhede, Satish Chinchanikar, S S Vadgeri, B S Rathod
Iop Conference Series Materials Science and Engineering, 2020
Investigations on the Machining Performance using Solid Lubricant Mixed with Varying Proportions in Vegetable Oil during Hard Turning
Satish Chinchanikar, H.M. Bawangaonwala, Shubham Bokade, Shubham Garode
Iop Conference Series Materials Science and Engineering, 2020
Mathematical Modelling of Material Removal Rate during Electric Discharge Machining Using Buckingham's Pi-Theorem
Vaibhav S Gaikwad, Vijaykumar S Jatti, Satish S Chinchanikar, Nikhil S Kakuste, Keshav N Nandurkar
Iop Conference Series Materials Science and Engineering, 2020
Analysis of tool vibration and surface roughness with tool wear progression in hard turning: An experimental and statistical approach
Nitin Ambhore, Dinesh Kamble, Satish Chinchanikar
Journal of Mechanical Engineering and Sciences, 2020
An Experimental Investigation of Cutting Tool Reliability and its Prediction Using Weibull and Gamma Models: A Comparative Assessment
Mohamad Gaddafee, Satish Chinchanikar
Materials Today Proceedings, 2020
Estimating primary fragment characteristics during hypervelocity impact of spherical fragment on thin plate using artificial neural network
Proceedings 31st International Symposium on Ballistics Ballistics 2019, 2019
Reliability of PVD-coated single-layer TiAlN carbide tool during turning of hardened AISI 4340 alloy steel
Satish Chinchanikar, Mohamad Gaddafee
Materials Today Proceedings, 2019
Assessment of Cutting Tool Reliability During Turning Considering Effects of Cutting Parameters and Machining Time
Gaddafee Mohamad, Satish Chinchanikar
Lecture Notes on Multidisciplinary Industrial Engineering, 2019
Reliability of Coated Carbide Tool during Turning Hardened Steel
Mohamad Gaddafee, Satish Chinchanikar
Iop Conference Series Materials Science and Engineering, 2018
Behaviour of cutting tool vibrations with the progress of tool wear in turning hardened AISI 52100 steel: An approach to tool condition monitoring system
Nitin Ambhore, Dinesh Kamble, Satish Chinchanikar
Iop Conference Series Materials Science and Engineering, 2018
Prediction of cutting tool vibration and surface roughness in hard turning of AISI52100 steel
Nitin Ambhore, Dinesh Kamble, Satish Chinchanikar
Matec Web of Conferences, 2018
Multi-Objective Optimization of Hard Turning: A Genetic Algorithm Approach
Omkar Manav, Satish Chinchanikar
Materials Today Proceedings, 2018
Prediction of Effect of Cutting Parameter on Fatigue Life of AISI 52100 Steel
Vijay Vanjari, Aniket Salve, Satish chinchanikar
Materials Today Proceedings, 2018
Multi-performance optimization in hard turning of AISI 4340 Steel using Particle Swarm Optimization technique
Omkar Manav, Satish Chinchanikar, Mahinder Gadge
Materials Today Proceedings, 2018
Design and Analysis of Compliant Mechanical Amplifier
V.S. Patil, P.R. Anerao, S.S. Chinchanikar
Materials Today Proceedings, 2018
Finish Machining of Hardened Steel
S.K. Choudhury, S. Chinchanikar
Comprehensive Materials Finishing, 2017
Evaluation of Tensile Strength of a Butt-Welded Joint Considering the Effect of Welding Parameters Using Response Surface Methodology
Amit P. Shinde, Abhijeet R. Deshpande, Satish S. Chinchanikar, Atul P. Kulkarni
Materials Today Proceedings, 2017
Residual Stresses during Hard Turning of AISI 52100 Steel: Numerical Modelling with Experimental Validation
Sujit Pawar, Aniket Salve, Satish Chinchanikar, Atul Kulkarni, Ganesh Lamdhade
Materials Today Proceedings, 2017
Cutting force modeling considering tool wear effect during turning of hardened AISI 4340 alloy steel using multi-layer TiCN/Al2O3/TiN-coated carbide tools
Satish Chinchanikar, S. K. Choudhury
International Journal of Advanced Manufacturing Technology, 2016
Comparative evaluations of nose wear progression and failure modes during hard turning under dry and near-dry cutting conditions
Satish Chinchanikar, S.K. Choudhury
International Journal of Machining and Machinability of Materials, 2016
Predictive modeling for flank wear progression of coated carbide tool in turning hardened steel under practical machining conditions
Satish Chinchanikar, S. K. Choudhury
International Journal of Advanced Manufacturing Technology, 2015
Machining of hardened steel - Experimental investigations, performance modeling and cooling techniques: A review
Satish Chinchanikar, S.K. Choudhury
International Journal of Machine Tools and Manufacture, 2015
Tool condition monitoring system: A review
Nitin Ambhore, Dinesh Kamble, Satish Chinchanikar, Vishal Wayal
Materials Today Proceedings, 2015
Experimental Investigationson Chip Formation and Plowing Cutting Forces During Hard Turning
Virendra bhokse, Satish Chinchanikar, Prashant Anerao, Atul Kulkarni
Materials Today Proceedings, 2015
A Numerical Model to Obtain Temperature Distribution During Hard Turning of AISI 52100 Steel
P.S. Bapat, P.D. Dhikale, S.M. Shinde, A.P. Kulkarni, S.S. Chinchanikar
Materials Today Proceedings, 2015
Hard turning using HiPIMS-coated carbide tools: Wear behavior under dry and minimum quantity lubrication (MQL)
Satish Chinchanikar, S.K. Choudhury
Measurement Journal of the International Measurement Confederation, 2014
Experimental investigations to optimise and compare the machining performance of different coated carbide inserts during turning hardened steel
Satish Chinchanikar, Sounak K Choudhury
Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture, 2014
Investigation of chip-tool interface temperature during turning of hardened AISI 4340 alloy steel using multi-layer coated carbide inserts
Satish Chinchanikar, S. K. Choudhury, A. P. Kulkarni
Advanced Materials Research, 2013
Wear behaviors of single-layer and multi-layer coated carbide inserts in high speed machining of hardened AISI 4340 steel
Satish Chinchanikar, S. K. Choudhury
Journal of Mechanical Science and Technology, 2013
Investigations on machinability aspects of hardened AISI 4340 steel at different levels of hardness using coated carbide tools
Satish Chinchanikar, S.K. Choudhury
International Journal of Refractory Metals and Hard Materials, 2013
Effect of work material hardness and cutting parameters on performance of coated carbide tool when turning hardened steel: An optimization approach
Satish Chinchanikar, S.K. Choudhury
Measurement Journal of the International Measurement Confederation, 2013
Modelling and evaluation of flank wear progression of coated carbide tools in turning hardened steels
Satish Chinchanikar, S.K. Choudhury
International Journal of Manufacturing Technology and Management, 2013

Satish Suresh Chinchanikar

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