Mechanical Engineering, Industrial and Manufacturing Engineering, Automotive Engineering, Aerospace Engineering
51
Scopus Publications
613
Scholar Citations
8
Scholar h-index
8
Scholar i10-index
Scopus Publications
Validation of powder flow characteristics in laser deposition using image correlation Pratheesh Kumar S, Rhahela Begam T, Irudaya Paulin G, Rithanya J Materials and Manufacturing Processes, 2026 Additive Manufacturing (AM), particularly Laser Direct Metal Deposition (LDMD), enables precise layer-wise metal deposition; however, powder stream stability critically influences part quality and dimensional accuracy. This study introduces a non-contact, image-based methodology integrating Digital Image Correlation (DIC) and Structural Similarity Index Measure (SSIM) to quantitatively assess powder distribution in LDMD. High-speed imaging combined with Python-based OpenCV processing is employed to measure convergence diameter and uniformity index for different materials (aluminum, iron, and lead) under varying process conditions. Pixel-to-length calibration and structural similarity analysis allow accurate capture of transient powder flow characteristics. Results show that convergence diameter increases with particle size and gas pressure, reaching 4.1 mm for 300 µm lead particles, while uniformity indices between 0.9585 and 0.985 indicate stable flow behavior. The proposed approach provides a validated framework for optimizing LDMD process control, reducing material wastage, and improving component performance in high-precision manufacturing sectors.
Data-driven approaches in incremental forming: Unravelling the path to enhanced manufacturing efficiency using data acquisition S. Pratheesh Kumar, V. Joseph Stanley, S. Nimesha International Journal of Lightweight Materials and Manufacture, 2025 Incremental forming is a versatile and cost-effective sheet metal forming technique widely adopted in low-volume manufacturing and prototyping across various industries. Recent advancements in data-driven approaches, including machine vision, neural networks, and 3D reconstruction methods, have significantly enhanced the precision and efficiency of incremental forming processes. This study explores the integration of advanced data acquisition and processing techniques to improve the accuracy, automation, and defect detection capabilities in incremental forming. Key advancements such as robot-assisted forming, computer-controlled toolpath generation from CAD models , and real-time quality monitoring using machine vision are discussed. The potential of single- and multi-view 3D reconstruction methods for optimizing toolpath strategies and enhancing formability is also examined. The findings highlight opportunities for full automation in incremental forming, demonstrating its potential to revolutionize modern manufacturing by reducing costs, increasing customization , and improving product quality. These advancements could benefit industries such as aerospace, automotive, and medical device manufacturing, where precision and flexibility are critical.
Automation Inspection in Metal Fabrication: Enhancing Sheet Metal Forming Processes with Automation, Machine Vision and Image Correlation for Quality Assurance S. Pratheesh Kumar, N. Balasubramanian Journal of Advanced Manufacturing Systems, 2024 This review emphasizes the evolving need for automated inspection in metal fabrication processes due to the increasing complexity of design advancements over the years. The study explores various defect detection algorithms and evaluates their effectiveness in enhancing the accuracy and reliability of the inspection process. Machine vision plays a crucial role in this context, contributing significantly to the precision of the inspection process in metal fabrication. Its ability to handle complex tasks ensures a thorough assessment of manufactured components. The paper also explores the use of digital image correlation (DIC) as a key tool in quality assurance for metal fabricated products. This technique provides detailed insights, enabling a thorough understanding of structural integrity and defect identification. By integrating insights on automated inspection through defect detection algorithms, machine vision and DIC, this review aims to advance quality assurance methodologies in the ever-evolving field of metal fabrication.
MULTI-OBJECTIVE PROCESS PARAMETER OPTIMIZATION IN SINGLE POINT INCREMENTAL FORMING OF SS-304 USING BOXBEHNKEN DESIGN OF EXPERIMENT AND TOPSIS OPTIMIZATION Optimization of Advanced Manufacturing Processes, 2024
OPTIMIZATION AND PROCESS PARAMETERS STUDY IN SINGLEPOINT INCREMENTAL FORMING OF TI GRADE 3 USING TAGUCHI DESIGN OF EXPERIMENTS AND GENETIC ALGORITHM OPTIMIZATION Optimization of Advanced Manufacturing Processes, 2024
MULTI-OBJECTIVE PROCESS PARAMETERS OPTIMIZATION IN SINGLE-POINT INCREMENTAL FORMING OF C110 BY CENTRAL COMPOSITE DESIGN AND MOORA OPTIMIZATION TECHNIQUE Optimization of Advanced Manufacturing Processes, 2024
Experimental and finite element analysis of titanium based medial tibial condyle using incremental sheet metal forming Indian Journal of Engineering and Materials Sciences, 2021
Effect of process parameters on tensile strength and surface quality of PLA-ABS part produced by fused deposition modeling Indian Journal of Engineering and Materials Sciences, 2021
Validation of powder flow characteristics in laser deposition using image correlation Pratheesh Kumar S, Rhahela Begam T, Irudaya Paulin G, Rithanya J Materials and Manufacturing Processes 41 (4), 1-20 , 2026 2026
Experimental and Theoretical Investigation on Tensile Properties of Fused Deposition Modeling Prototypes of ABS-M30 using RSM and GA K Anand, S Pratheesh Kumar, VJ Subiramanian Lecture Notes in Civil Engineering 1 (01), 441 - 453 , 2025 2025
Powder catchment efficiency optimisation of Stelcar 65 fabricated by laser direct metal deposition S. Pratheesh Kumar, Rithika Jayabharathi Yuvarajan Progress in Additive Manufacturing 1 (01), 1-14 , 2025 2025
Just-In-Time (JIT) Implementation in Foundry Division using Mix Model Manufacturing and Inventory Handling System Pratheesh Kumar S, Naveen Anthuvan R, Dharshini PU, Jayasadha S, Shanmugam S Journal of Mechanical Engineering and Technology (JMET) 9 (01), 14 - 43 , 2025 2025
Exploring the Efficacy of Python-Driven Automated Machine Vision Algorithms for Inspection in Sheet Metal Forming Pratheesh kumar S, Nharguna Nangai Experimental Techniques 1 (01), 1-24 , 2025 2025 Citations: 4
Exploring the synergy of python programming in single point incremental forming S. Pratheesh Kumar, N. Mugilan International Journal on Interactive Design and Manufacturing, 1-25 , 2025 2025 Citations: 3
Investigations on mass flow rate of rotary vane feeder for direct metal laser deposition SP Kumar, JR Ramakrishna, S Karthikeyan Progress in Additive Manufacturing 10 (1), 33-52 , 2025 2025 Citations: 3
Data-Driven Approaches in Incremental Forming: Unravelling the Path to Enhanced Manufacturing Efficiency using Data Acquisition Pratheesh Kumar S, Joseph Stanley V and Nimesha S International Journal of Lightweight Materials and Manufacture, 1-29 , 2024 2024 Citations: 4
Automation inspection in metal fabrication: enhancing sheet metal forming processes with automation, machine vision, and image correlation for quality assurance S Pratheesh Kumar, Balasubramanian, N Journal of Advanced Manufacturing Systems , 2024 2024 Citations: 1
Multi-Objective Process Parameter Optimization in Single Point Incremental Forming of SS-304 Using Box-Behnken Design of Experiment and TOPSIS Optimization Pratheesh Kumar S, S Nandhagopal Optimization of Advanced Manufacturing Processes 1, 77-97 , 2024 2024
Multi-Objective Process Parameters Optimization in Single Point Incremental Forming of C110 By Central Composite Design and MOORA Optimization Technique Pratheesh Kumar S, U Akash, S Akash Optimization of Advanced Manufacturing Processes 1, 117-135 , 2024 2024
Optimization and Process Parameters Study in Single Point Incremental Forming of Ti Grade 3 Using Taguchi Design of Experiments and Genetic Algorithm Optimization Pratheesh Kumar S, P Mohit Akash Optimization of Advanced Manufacturing Processes 1, 99-115 , 2024 2024
Implementation of Six Sigma to improve service quality and customer satisfaction in e-commerce industry Pratheesh Kumar S, R Rajamani, P B Maharasi, R Mohanraj, K Morsshini, Prabhu ... Recent Advances in Material, Manufacturing, and Machine Learning 2, 467-475 , 2024 2024
A case study to improve the productivity of ladle gearbox manufacturing Pratheesh Kumar S, R Rajesh, R Raashika, R Mohanraj, T C Varunkumar, Mark V ... Recent Advances in Material, Manufacturing, and Machine Learning 2, 544-554 , 2024 2024
Study on Six Sigma methodology to improve the brand value of beverage industry Pratheesh Kumar S, R. Naveen Anthuvan, K. Anand, R. Mohanraj, R. Arunkoushik ... Recent Advances in Material, Manufacturing, and Machine Learning 2 (1), 459-466 , 2024 2024
Internet of things based remote monitoring and energy consumption analysis in CNC machine R Mohanraj, SH Chealvan, SP Kumar, SH Knikhil, CS Ramshankar, ... AIP Conference Proceedings 2946 (1) , 2023 2023 Citations: 1
Integration of product life cycle management on iot enabled product in an manufacturing industry R Mohanraj, R Rajamani, SP Kumar, MN Prabu, M Vikram, ... AIP Conference Proceedings 2946 (1) , 2023 2023 Citations: 2
Remote monitoring and financial assessment of gravity die casting machine using industrial internet of things R Mohanraj, N Krishnakumar, M Senthilkumar, SP Kumar, R Arunkoushik, ... AIP Conference Proceedings 2946 (1) , 2023 2023 Citations: 1
Improving the Efficiency of the Vehicle Service Sector Using CPM and PERT S Pratheesh Kumar, E Selvavignesh, Jonathan Cecil Fernando, S Sree Kannan, R ... Advances in Manufacturing, Automation, Design and Energy Technologies … , 2023 2023
Incorporating Six Sigma in e-Learning Platform During COVID-19 Pandemic S Pratheesh Kumar, V Nithin, S Akash, N Sheik Musthaq Ahamed Advances in Manufacturing, Automation, Design and Energy Technologies … , 2023 2023
MOST CITED SCHOLAR PUBLICATIONS
A review on properties of Inconel 625 and Inconel 718 fabricated using direct energy deposition SP Kumar, S Elangovan, R Mohanraj, JR Ramakrishna Materials Today: Proceedings 46, 7892-7906 , 2021 2021 Citations: 201
Review on the evolution and technology of State-of-the-Art metal additive manufacturing processes SP Kumar, S Elangovan, R Mohanraj, JR Ramakrishna Materials Today: Proceedings 46, 7907-7920 , 2021 2021 Citations: 131
Real-time applications and novel manufacturing strategies of incremental forming: An industrial perspective SP Kumar, S Elangovan, R Mohanraj, S Boopathi Materials Today: Proceedings 46, 8153-8164 , 2021 2021 Citations: 53
Critical review of off-axial nozzle and coaxial nozzle for powder metal deposition SP Kumar, S Elangovan, R Mohanraj, B Srihari Materials Today: Proceedings 46, 8066-8079 , 2021 2021 Citations: 42
Significance of continuous wave and pulsed wave laser in direct metal deposition SP Kumar, S Elangovan, R Mohanraj, VS Narayanan Materials Today: Proceedings 46, 8086-8096 , 2021 2021 Citations: 41
Experimental investigations of warm incremental sheet forming process on magnesium AZ31 and aluminium 6061 alloy R Mohanraj, S Elangovan, S Pratheesh Kumar Proceedings of the Institution of Mechanical Engineers, Part L: Journal of … , 2023 2023 Citations: 18
Multi-objective optimization in incremental sheet forming of Ti-6Al-4V alloy using grey relational analysis method CV Ajay, S Elangovan, S Pratheesh Kumar, K Manisekar Proceedings of the Institution of Mechanical Engineers, Part E: Journal of … , 2022 2022 Citations: 15
Optimization in single point incremental forming of Inconel 718 through response surface methodology S Pratheesh Kumar, S Elangovan Transactions of the Canadian Society for Mechanical Engineering 44 (1), 148-160 , 2019 2019 Citations: 14
A comprehensive review in incremental forming on approaches of deformation analysis and surface morphologies SP Kumar, S Elangovan, R Mohanraj, S Boopathi Materials Today: Proceedings 43, 3129-3139 , 2021 2021 Citations: 8
Machinability study in milling of Ti-6Al-4V using cryogenic treated and coated tool RN Anthuvan, SP Kumar, RA Prakash, B Arunkarthik, A Akhilesh Materials Today: Proceedings 46, 8417-8428 , 2021 2021 Citations: 8
IoT-enabled Condition Monitoring and Intelligent Maintenance System for Machine R Mohanraj, R Rajamani, S Elangovan, S Pratheesh kumar, ... Futuristic Manufacturing, 163-177 , 2023 2023 Citations: 7
Review on surface characteristics of components produced by direct metal deposition process S. Pratheesh Kumar, K. Anand, S. Hari Chealvan and S. Karthikeya Muthu Journal of Mechanical Engineering and Sciences 16 (4), 9197 – 9229 , 2022 2022 Citations: 7
Effect of process parameters on tensile strength and surface quality of PLA-ABS part produced by fused deposition modeling. M Ramasamy, ES Moorthy, A Balasubramanian, PKS Kumaran, ... Indian Journal of Engineering & Materials Sciences 28 (3) , 2021 2021 Citations: 7
Experimental study on single point incremental forming of Inconel 718 S Pratheesh Kumar, S Elangovan, R Mohanraj Transactions of the Canadian Society for Mechanical Engineering 44 (2), 179-188 , 2019 2019 Citations: 6
Optimization and prediction of incremental sheet forming parameters of Titanium grade 5 sheet using a response surface methodology and artificial neural network Veera Ajay C, Elangovan S, Kamaraja AS, Karthik Kumar K and Pratheesh Kumar S Proceedings of the Institution of Mechanical Engineers, Part C: Journal of … , 2022 2022 Citations: 5
Exploring the Efficacy of Python-Driven Automated Machine Vision Algorithms for Inspection in Sheet Metal Forming Pratheesh kumar S, Nharguna Nangai Experimental Techniques 1 (01), 1-24 , 2025 2025 Citations: 4
Data-Driven Approaches in Incremental Forming: Unravelling the Path to Enhanced Manufacturing Efficiency using Data Acquisition Pratheesh Kumar S, Joseph Stanley V and Nimesha S International Journal of Lightweight Materials and Manufacture, 1-29 , 2024 2024 Citations: 4
Technology overview of metal additive manufacturing processes S. Pratheesh Kumar, R. Naveen Anthuvan, K. Anand, S. Sanjith Raj, P. M ... AIP Conference Proceedings 2460 (1), 1-15 , 2022 2022 Citations: 4
Experimental and finite element analysis of titanium based medial tibial condyle using incremental sheet metal forming M Ramasamy, ES Moorthy, PK Selva Kumaran, AP Rangasamy Indian Journal of Engineering and Materials Sciences (IJEMS) 28 (5), 502-508 , 2021 2021 Citations: 4
Exploring the synergy of python programming in single point incremental forming S. Pratheesh Kumar, N. Mugilan International Journal on Interactive Design and Manufacturing, 1-25 , 2025 2025 Citations: 3
