FEM-Based Simulative Study for Multi-Response Optimization of Powder Bed Fusion Process Anoop Kumar Sood, Azhar Equbal, Zahid A. Khan, Irfan Anjum Badruddin, Mohamed Hussien Mathematics, 2022 Laser powder bed fusion (LPBF) is an additive manufacturing technology which uses a heat source (laser) to sinter or fuse atomized powder particles together. A new layer of powder is spread over the previous layer using a roller, and then the laser power fuses them. This mechanism is repeated until the part model is completed. To reduce the time, effort, and cost, the present study incorporated the design of an experimental approach conjoined with finite element analysis (FEA) to simulate the LPBF process. A three-dimensional (3D) bi-material model was subjected to FEA with variations in temporal and spatial material characteristics. A Gaussian moving heat source model for the multi-scanning of a single layer was developed to understand the effect of process parameters, namely laser power, scan speed, and scan pattern on melt pool dimensions. Although, similar simulation models have been reported in the literature, the majority of these did not consider parametric variations. A few studies adopted multiple parameters which varied simultaneously, but the major limitation of these studies was that most of them did not consider multiple characteristics under a constrained environment. In the present research, the multi-parameter multi-level simulation study was performed to understand the process mechanism with fewer simulations. Results showed that the studied dimensions were sensitive to parameter setting, and that temperature variation within the melt pool was dependant on the material phase in the vicinity of the melt pool. This research proposed that melt pool dimensions must be accurately controlled for optimum process performance to achieve proper overlap between the adjacent scan lines and sufficient depth to complete bonding with the bottom layer. Since the involved criteria were of a conflicting nature, the problem of determining a single factor setting to obtain the desired results was solved using grey relational analysis (GRA). It was found that, among all the considered process parameters, scan velocity was the most significant one. This research recommended a maximum scan velocity i.e., v = 1.5 m/s, with a minimum laser power i.e., P = 80 W. In addition, it was also suggested that low energy density be used to melt the powder layer properly.
The usefulness of additive manufacturing (AM) in COVID-19 Azhar Equbal, Shahid Akhter, Anoop Kumar Sood, Iftekhar Equbal Annals of 3D Printed Medicine, 2021 COVID-19 caused by novel coronavirus is a serious pandemic that has affected the various countries all across the globe. The effect of this pandemic is so devastating that many rising nations are brought to their knees and struggling to save the damage posed to their economy. Medical professionals and the healthcare community are paying their best effort to minimize and overcome the spread of this pandemic. To continue to fight against the COVID-19, healthcare delivery systems require the support of novel technologies which can meet their rapid demand for medical equipment and devices. The study explores the damage caused by COVID-19 to the industrial sector and the way AM is contributing to the economy post-COVID-19. State of the art concerning the application of AM in the present scenario especially to support the interrupted global supply chain is collected and analysed to identify its relevance in the battle against COVID-19.
Finite element-based optimization of additive manufacturing process using statistical modelling and league of champion algorithm Anoop Kumar Sood Machine Learning Applications in Non Conventional Machining Processes, 2021 The study develops a 2D (two-dimensional) finite element model with a Gaussian heat source to simulate powder bed-based laser additive manufacturing process of Ti6Al4V alloy. The modelling approach provides insight into the process by correlating laser power and scan speed with melt pool temperature distribution and size. To tackle the FEA result in optimization environment, statistical approach of data normalization and regression modelling is adopted. Statistical treatment is not only able to deduce the interdependence of various objectives consider but also make the representation of objectives and constraint computationally simple. Adoption of a new stochastic algorithm namely league of a champion algorithm (LCA) together with penalty function approach for non-linear constraint handling reduces the effort required and computational complexity involved in determining the optimum parameter setting.
Application of the combined ANN and GA for multi-response optimization of cutting parameters for the turning of glass fiber-reinforced polymer composites Azhar Equbal, Mohammad Shamim, Irfan Anjum Badruddin, Md. Israr Equbal, Anoop Kumar Sood, Nik Nazri Nik Ghazali, Zahid A. Khan Mathematics, 2020 Glass fiber-reinforced polymer (GFRP) composites find wide applications in automobile, aerospace, aircraft and marine industries due to their attractive properties such as lightness of weight, high strength-to-weight ratio, high stiffness, good dimensional stability and corrosion resistance. Although these materials are required in a wide range of applications, their non-homogeneous and anisotropic properties make their machining troublesome and consequently restrict their use. It is thus important to study not only the machinability of these materials but also to determine optimum cutting parameters to achieve optimum machining performance. The present work focuses on turning of the GFRP composites with an aim to determine the optimal cutting parameters that yield the optimum output responses. The effect of three cutting parameters, i.e., spindle rotational speed (N), feed rate (f) and depth of cut (d) in conjunction with their interactions on three output responses, viz., Material Removal Rate (MRR), Tool Wear Rate (TWR), and Surface roughness (Ra), is studied using full factorial design of experiments (FFDE). The statistical significance of the cutting parameters and their interactions is determined using analysis of variance (ANOVA). To relate the output response and cutting parameters, empirical models are also developed. Artificial Neural Network (ANN) combined with Genetic Algorithm (GA) is employed for multi-response optimization to simultaneously optimize the MRR, TWR and Ra.
Optimization of process parameters of FDM part for minimiizing its dimensional inaccuracy International Journal of Mechanical and Production Engineering Research and Development, 2017
Engineering, Technology and Management KC Rath, A Rocha, SS Mahapatra, AK Sood, A Kumar Springer Nature , 2025 2025
Surface finish enhancement of Si (100) with single pole magnetic abrasive finishing using chemical oxidizers and alumina slurry A Sharma, K Pandey, AK Sood Silicon 16 (10), 4557-4576 , 2024 2024 Citations: 4
Fuzzy logic based model to predict surface roughness of Si (100) wafer using preliminary experimental data obtained from single pole magnetic abrasive finishing process A Sharma, K Pandey, AK Sood Silicon 16 (10), 4199-4212 , 2024 2024 Citations: 4
Mechanical Properties Evaluation of Natural Fiber Mats-Based Composites A Prasad, R Das, AK Sood Journal of Technology 12 (10), 1037-1051 , 2024 2024
Design for additive manufacturing for prediction of deformations and residual stresses on topologically optimised structure K Kachhap, U Khandey, AK Sood Materials Today: Proceedings 103, 168-175 , 2024 2024 Citations: 4
Preliminary Experimental Investigation into Work Brush Temperature on Silicon Wafer Using Single Pole Magnetic Abrasive Finishing (SPMAF) A Sharma, K Pandey, AK Sood International Conference on Scientific and Technological Advances in … , 2023 2023
FEM-Based Simulative Study for Multi-Response Optimization of Powder Bed Fusion Process AK Sood, A Equbal, ZA Khan, IA Badruddin, M Hussien Mathematics 10 (14), 2505 , 2022 2022
RSM based investigation of compressive properties of FDM fabricated part A Equbal, AK Sood, MI Equbal, IA Badruddin, ZA Khan CIRP Journal of Manufacturing Science and Technology 35, 701-714 , 2021 2021 Citations: 34
The usefulness of additive manufacturing (AM) in COVID-19 A Equbal, S Akhter, AK Sood, I Equbal Annals of 3D Printed Medicine 2, 100013 , 2021 2021 Citations: 38
Application of Machine Learning in Fused Deposition Modeling: A Review A Equbal, S Akhter, MA Equbal, AK Sood Fused Deposition Modeling Based 3D Printing, 445-463 , 2021 2021 Citations: 14
Finite Element-Based optimization of additive manufacturing process using statistical modelling and league of champion algorithm AK Sood Machine Learning Applications in Non-Conventional Machining Processes, 215-234 , 2021 2021 Citations: 2
Integrated approach for flexible job shop scheduling using multi-objective genetic algorithm S Nayak, AK Sood, A Pandey International Conference on Energy, Materials Sciences & Mechanical … , 2020 2020 Citations: 5
Application of the combined ANN and GA for multi-response optimization of cutting parameters for the turning of glass fiber-reinforced polymer composites A Equbal, M Shamim, IA Badruddin, MI Equbal, AK Sood, NN Nik Ghazali, ... Mathematics 8 (6), 947 , 2020 2020 Citations: 35
Feasibility of FDM-electroplating process for EDM electrode fabrication AK Sood, A Equbal Materials Today: Proceedings 28, 1154-1157 , 2020 2020 Citations: 14
PCA-based desirability method for dimensional improvement of part extruded by fused deposition modelling technology A Equbal, MI Equbal, AK Sood Progress in Additive Manufacturing 4 (3), 269-280 , 2019 2019 Citations: 37
An investigation on the feasibility of fused deposition modelling process in EDM electrode manufacturing A Equbal, MI Equbal, AK Sood CIRP Journal of Manufacturing science and technology 26, 10-25 , 2019 2019 Citations: 83
Multi-criterion decision method for roughness optimization of fused deposition modelled parts A Equbal, MA Equbal, MI Equbal, AK Sood Additive Manufacturing Technologies from an Optimization Perspective, 235-262 , 2019 2019 Citations: 4
An insight on current and imminent research issues in EDM A Equbal, MI Equbal, MA Equbal, AK Sood Non-Conventional Machining in Modern Manufacturing Systems, 33-54 , 2019 2019 Citations: 3
A review and reflection on part quality improvement of fused deposition modelled parts A Equbal, MA Equbal, AK Sood, R Pranav, MI Equbal IOP Conference Series: Materials Science and Engineering 455 (1), 012072 , 2018 2018 Citations: 19
Intelligent process model for bead geometry prediction in WAAM M Karmuhilan, AK Sood Materials Today: Proceedings 5 (11(3)), 24005-24013 , 2018 2018 Citations: 99
MOST CITED SCHOLAR PUBLICATIONS
Parametric appraisal of mechanical property of fused deposition modelling processed parts AK Sood, RK Ohdar, SS Mahapatra Materials & Design 31 (1), 287-295 , 2010 2010 Citations: 1860
Improving dimensional accuracy of fused deposition modelling processed part using grey Taguchi method AK Sood, RK Ohdar, SS Mahapatra Materials & design 30 (10), 4243-4252 , 2009 2009 Citations: 908
Experimental investigation and empirical modelling of FDM process for compressive strength improvement AK Sood, RK Ohdar, SS Mahapatra Journal of Advanced Research 3 (1), 81-90 , 2012 2012 Citations: 797
Optimization of Fused Deposition Modelling (FDM) Process Parameters Using Bacterial Foraging Technique. SK Panda, S Padhee, AK Sood, SS Mahapatra Intell. Inf. Manag. 1 (2), 89-97 , 2009 2009 Citations: 267
Parametric appraisal of fused deposition modelling process using the grey Taguchi method AK Sood, RK Ohdar, SS Mahapatra Proceedings of the Institution of Mechanical Engineers, Part B: Journal of … , 2010 2010 Citations: 215
An investigation on sliding wear of FDM built parts AK Sood, A Equbal, V Toppo, RK Ohdar, SS Mahapatra CIRP Journal of Manufacturing Science and Technology 5 (1), 48-54 , 2012 2012 Citations: 202
A study on dimensional accuracy of fused deposition modeling (FDM) processed parts using fuzzy logic RK Sahu, SS Mahapatra, AK Sood Journal for Manufacturing Science and Production 13 (3), 183 , 2013 2013 Citations: 183
Optimization of process parameters in fused deposition modeling using weighted principal component analysis AK Sood, V Chaturvedi, S Datta, SS Mahapatra Journal of Advanced Manufacturing Systems 10 (02), 241-259 , 2011 2011 Citations: 116
Optimization of fused deposition modeling process parameters using a fuzzy inference system coupled with Taguchi philosophy SK Padhi, RK Sahu, SS Mahapatra, HC Das, AK Sood, B Patro, ... Advances in Manufacturing 5 (3), 231-242 , 2017 2017 Citations: 110
Intelligent process model for bead geometry prediction in WAAM M Karmuhilan, AK Sood Materials Today: Proceedings 5 (11(3)), 24005-24013 , 2018 2018 Citations: 99
Bayesian regularization-based Levenberg–Marquardt neural model combined with BFOA for improving surface finish of FDM processed part SS Mahapatra, AK Sood The International Journal of Advanced Manufacturing Technology 60 (9), 1223-1235 , 2012 2012 Citations: 98
An investigation on the feasibility of fused deposition modelling process in EDM electrode manufacturing A Equbal, MI Equbal, AK Sood CIRP Journal of Manufacturing science and technology 26, 10-25 , 2019 2019 Citations: 83
Prediction of dimensional accuracy in fused deposition modelling: a fuzzy logic approach A Equbal, AK Sood, SS Mahapatra International Journal of Productivity and Quality Management 7 (1), 22-43 , 2011 2011 Citations: 74
Rapid tooling: A major shift in tooling practice A Equbal, AK Sood, M Shamim Manufacturing and Industrial Engineering 14 (3-4) , 2015 2015 Citations: 72
Investigations on metallization in FDM build ABS part using electroless deposition method A Equbal, AK Sood Journal of Manufacturing Processes 19, 22-31 , 2015 2015 Citations: 67
Optimization of process parameters of FDM part for minimiizing its dimensional inaccuracy A Equbal, AK Sood, AR Ansari, MA Equbal International Journal of Mechanical and Production Engineering Research and … , 2017 2017 Citations: 60
Metallization on FDM parts using the chemical deposition technique A Equbal, AK Sood Coatings 4 (3), 574-586 , 2014 2014 Citations: 57
Prediction and analysis of sliding wear performance of fused deposition modelling-processed ABS plastic parts A Equbal, AK Sood, V Toppo, RK Ohdar, SS Mahapatra Proceedings of the Institution of Mechanical Engineers, Part J: Journal of … , 2010 2010 Citations: 47
Electrical discharge machining: an overview on various areas of research A Equbal Manufacturing and Industrial Engineering , 2014 2014 Citations: 41
Study on parametric optimization of fused deposition modelling (FDM) process AK Sood 2011 Citations: 41