Anoop Kumar Sood
@niamt.ac.in
Professor, Department of Mechanical & Manufacturing Engineering
National Institute of Advanced Manufacturing Technology
RESEARCH, TEACHING, or OTHER INTERESTS
Mechanical Engineering, Statistics, Probability and Uncertainty, Industrial and Manufacturing Engineering, Computational Theory and Mathematics
FUTURE PROJECTS
Mathematical modelling of Addititve Manufacturing
Applications Invited
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Ashwani Sharma, Kheelraj Pandey, and Anoop Kumar Sood
Springer Science and Business Media LLC
Anoop Kumar Sood, Azhar Equbal, Zahid A. Khan, Irfan Anjum Badruddin, and Mohamed Hussien
MDPI AG
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.
Sunita Nayak, Anoop Kumar Sood, and Abhishek Pandey
Springer Singapore
Azhar Equbal, Anoop Kumar Sood, Md. Israr Equbal, Irfan Anjum Badruddin, and Zahid A. Khan
Elsevier BV
Azhar Equbal, Shahid Akhter, Anoop Kumar Sood, and Iftekhar Equbal
Elsevier BV
Anoop Kumar Sood
IGI Global
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.
Azhar Equbal, Mohammad Shamim, Irfan Anjum Badruddin, Md. Israr Equbal, Anoop Kumar Sood, Nik Nazri Nik Ghazali, and Zahid A. Khan
MDPI AG
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.
Azhar Equbal, Md. Israr Equbal, and Anoop Kumar Sood
Springer Science and Business Media LLC
Azhar Equbal, Md. Israr Equbal, and Anoop Kumar Sood
Elsevier BV
Anoop Kumar Sood and Azhar Equbal
Elsevier BV
A Equbal, Md. A. Equbal, A K Sood, R Pranav, and Md. I. Equbal
IOP Publishing
Fused deposition modelling (FDM) is an extrusion based additive manufacturing process which fabricates the part by extruding semi-molten thermoplastic material through a small nozzle in a machine plateform. The material is deposited layer over layer and the part is fabricated following the bottom up approach. The process can built any complex part geometry in very less time without any tooling problem. Despite of having numerous advantages, fused deposition modelled part’s performance is poorer when measured in terms of part qualities like dimensional accuracy, surface roughness and mechanical strength. Considering the domestic and industrial usage of FDM technology various researchers have contributed their effort in improvement of these part qualities prior to its application. The present study is headed towards reviewing their efforts and reflecting the techniques used for optimization of FDM part qualities.
M. Karmuhilan and Anoop kumar sood
Elsevier BV
Azhar Equbal, Md. Israr Equbal, Anoop Kumar Sood, and Md. Asif Equbal
International Journal of Technology
Electroplating on fused deposition modeling parts through two different routes is presented in the study. One route follows the conventional method of electroplating using chromic acid for surface preparation or etching and the other route uses the novel method of electroplating using aluminium charcoal (Al-C) paste for surface preparation. Same plating conditions are used for both the routes employed. The result proposes that instead of shell cracking in few electroplated samples, Al-C route is also capable of producing good copper deposition on FDM samples. Cracks may develop in few samples electroplated through Al-C route, because of dissolution of paste at high operating condition during electroplating. Proper drying of electrolessly plated samples and adaptation of suitable operating condition reduces the risk of electroplated shell cracking.
Saroj Kumar Padhi, Ranjeet Kumar Sahu, S. S. Mahapatra, Harish Chandra Das, Anoop Kumar Sood, Brundaban Patro, and A. K. Mondal
Springer Science and Business Media LLC
Md Israr Equbal, Rajkumar Ohdar, Azhar Equbal, and Anoop Kumar Sood
Inderscience Publishers
In this paper, three dimensional finite element analysis has been carried out using FEM-based DEFORMTM 3D software on hot forging of connecting rod. The influence of design parameters and process parameters are investigated for the responses like effective strain rate and forging load during forging operation. In order to optimise both the responses simultaneously, grey relational analysis (GRA) embedded with Taguchi method is employed. Grey relational grade is used as a performance index to determine optimal setting of process parameters for both the responses simultaneously. Analysis of variance (ANOVA) is employed to determine significant parameters. Process parameters such as flash thickness, flash width, and corner radii are found to be the most significant parameters affecting grey relational grade. Optimal process setting leading to a higher effective strain rate with the least forging load has been verified through a confirmation experiment for validation of the results. [Received 15 October 2015; Revised 25 February 2016; Accepted 13 March 2016]
Azhar Equbal and Anoop Kumar Sood
Elsevier BV
Azhar Equbal and Anoop Sood
MDPI AG
Metallization of ABS (acrylonitrile-butadiene-styrene) parts has been studied on flat part surfaces. These parts are fabricated on an FDM (fused deposition modeling machine) using the layer-wise deposition principle using ABS as a part material. Electroless copper deposition on ABS parts was performed using two different surface preparation processes, namely ABS parts prepared using chromic acid for etching and ABS parts prepared using a solution mixture of sulphuric acid and hydrogen peroxide (H2SO4/H2O2) for etching. After surface preparations using these routes, copper (Cu) is deposited electrolessly using four different acidic baths. The acidic baths used are 5 wt% CuSO4 (copper sulfate) with 15 wt% of individual acids, namely HF (hydrofluoric acid), H2SO4 (sulphuric acid), H3PO4 (phosphoric acid) and CH3COOH (acetic acid). Cu deposition under different acidic baths used for both the routes is presented and compared based on their electrical performance, scanning electron microscopy (SEM) and energy dispersive X-ray spectrometry (EDS). The result shows that chromic acid etched samples show better electrical performance and Cu deposition in comparison to samples etched via H2SO4/H2O2.
Ratnakar Das, Anindita Sarmah, D.V.N. Lakshmi, and A. Sood
Elsevier BV
S. S. Mahapatra and Anoop Kumar Sood
Springer Science and Business Media LLC
Anoop Kumar Sood, Rajkumar Ohdar, and S.S. Mahapatra
Trans Tech Publications, Ltd.
Fused deposition modelling (FDM) is one of the rapid prototyping (RP) processes that build part of any geometry by sequential deposition of material on a layer by layer basis. Unlike other RP systems which involve an array of lasers, powders, resins, this process uses heated thermoplastic filaments which are extruded from the tip of nozzle in a prescribed manner. Present work focuses on extensive study to understand the effect of five important parameters such as layer thickness, part build orientation, raster angle, raster width and air gap on the sliding wear of test specimen built through FDM. The study provides insight into complex dependency of wear on process parameters and proposes a statistically validated predictive equation. Microphotographs are used to explain the mechanism of wear. Finally, the predictive equation is used to find optimal parameter setting through bacteria foraging optimization algorithm (BFOA).
Anoop Kumar Sood, Asif Equbal, Vijay Toppo, R.K. Ohdar, and S.S. Mahapatra
Elsevier BV
Anoop K. Sood, Raj K. Ohdar, and Siba S. Mahapatra
Elsevier BV
ANOOP KUMAR SOOD, VEDANSH CHATURVEDI, SAURAV DATTA, and SIBA SANKAR MAHAPATRA
World Scientific Pub Co Pte Lt
Fused deposition modeling (FDM) is a process by which functional parts can be produced rapidly through deposition of fused layers of material according to a numerically defined cross-sectional geometry. Literature suggests that process parameters largely influence on quality characteristics of rapid prototyping (RP) parts. A functional part is subjected to different loading conditions in actual practice. Therefore, process parameters need to be determined in such a way that they collectively optimize more than one response simultaneously. To address this issue, effect of important process parameters viz., layer thickness, orientation, raster angle, raster width, and air gap have been studied. The responses considered in this study are mechanical property of FDM produced parts such as tensile, bending and impact strength. The multiple responses are converted into a single response using principal component analysis (PCA) so that influence of correlation among the responses can be eliminated. Resulting single response is nothing but the weighted sum of three principal components that explain almost hundred percent of variation. The experiments have been conducted in accordance with Taguchi's orthogonal array to reduce the experimental runs. The results indicate that all the factors such as layer thickness, orientation, raster angle, raster width and air gap and interaction between layer thickness and orientation significantly influence the response. Optimum parameter settings have been identified to simultaneously optimize three responses. The mechanism of failure is explained with the help of SEM micrographs.