Dr. M. K. Pradhan
@nitrr.ac.in
Associate Professor, Department of Mechanical Engineering
National Institute of Technology, Raipur, (An Institute of National Importance, under MHRD, Govt. of India) India. Pin- 462 003
Dr. M. K. Pradhan, Associate Professor, Department of Mechanical Engineering, National Institute of Technology, Raipur (An Institute of National Importance). Prior to this, he was working as Assistant Professor, Grade-1, in the Department of Mechanical, Maulana Azad National Institute of Technology, Bhopal (An Institute of National Importance). He has completed his PhD., from National Institute of Technology, Rourkela his research topic was “Experimental Investigation and Modelling of Surface Integrity, Accuracy and Productivity Aspect in EDM of AISID2 Steel” in 2010. Prior to this, after completing M.E from NIT Rourkela in the year 1999. He is currently head of Metrology and Measurement Lab and CAM Lab., and was Head of Workshop and Production Engineering Lab. of the Maulana Azad National Institute of Technology, Bhopal, India. He teaches metrology, tool engineering, metal forming, theory of plasticity, design, and manufacturing subjects. He has over 25 years of teaching and research
EDUCATION
PhD (Mechanical Engineering)
RESEARCH, TEACHING, or OTHER INTERESTS
Mechanical Engineering, Multidisciplinary, Industrial and Manufacturing Engineering, Museology
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Rajesh Sharma, M K Pradhan, and Pankaj Jain
IOP Publishing
Abstract The aim of this study is to determine the use of B 4 C along with AVA as economical reinforcements to improve the mechanical properties of aluminium alloy 8011. The purpose of this investigation is the development of cost-effective hybrid metal matrix composites. The present investigation assessed the mechanical characteristics of Al-8011 alloy, Al-8011/3AVA, Al-8011/4B 4 C, Al-8011/2.5B 4 C/2.5AVA, and Al-8011/3B 4 C/3AVA composites, which were manufactured through stir-casting techniques. Scanning electron microscope (SEM) imaging with an energy-dispersive spectroscope (EDS) was performed on the fabricated composites to confirm the presence of reinforcements, and the images revealed a uniform distribution of reinforcements in the matrix. The density of the composite decreased with an increase in weight % of AVA-B 4 C in comparison with that of matrix aluminum alloy 8011. Results obtained for tensile strength and hardness exhibit the optimal results from adding 3 wt.% B 4 C with 3 wt.% AVA. The present paper also investigates the application of three multiple criteria decision-making (MCDM) methodological approaches to select the best option.
Rakesh Kumar Patel and Mohan Kumar Pradhan
IOP Publishing
Abstract Inconel 718 is a nickel-based superalloy with exceptional mechanical qualities, including high tensile and impact strength, as well as good oxidation and corrosion resistance. EDM is widely used to cut hard materials of this type by common parameters affecting spark, current, duty cycle etc, whereas MRR, SR can be greatly improved by using sufficient fluid properties of the dielectric. Incorporation of alumina nanoparticles with deionized water may improve machining performance, with no prior research on machining characteristics of Inconel 718 using alumina nanofluid in EDM. The machinability of Inconel 718 via the electrical discharge machining process, as well as the performance of alumina nanofluid as a dielectric medium, have been evaluated using deionized water with a concentration of 0.5%. In this study, based on the effect of various input parameters such as I p , P o n and G v on the MRR, TWR and SR, and the RSM has been used to conduct the experiments. A maximum MRR of 0.048 g min−1, a TWR of 0.00632 g min−1 and an SR of 3.271 μm are achieved. Overall, the use of alumina nanofluid can improve machining performance in EDM, due to the reduction of abnormalities such as crack formation and molten metal debris in the machined surface of Inconel 718.
Ambuj Pateriya and Mohan Kumar Pradhan
IOP Publishing
Abstract Researchers were compelled to create composites as alternatives to the already used engineering materials due to the industrial desire for fresh, promising materials with superior mechanical and tribological properties. Due to their superior characteristics, aluminium matrix composites (AMCs) with the appropriate class of particulate/particle reinforcements have been shown to have a wide range of tribological applications. A thorough evaluation of the sliding wear response of aluminium matrix composites (AMCs) in a dry environment using a pin-on-disc wear tester has been attempted in this review study. A discussion regarding wear performance of Al monolithic alloy and its composites has been made with respect to varying process parameters (e.g. normal load, sliding distance, and speed) and the concentration of different particle reinforcements incorporated in the production of aluminium matrix composites. The existing paper provides a synergic presentation of the effects of various intrinsic and extrinsic variables on wear characteristics, leading to the novelty and uniqueness of this review article.
Amit Kumar and Mohan Kumar Pradhan
Springer Science and Business Media LLC
Mohan Kumar Pradhan
SAGE Publications
The high strength-to-weight ratio and ease of manufacturing of composite materials make them widely used across a variety of industries. A commonly used method of improving composite structure load-bearing capacity is to employ carbon fiber-reinforced polymer (CFRP) cores. The mechanical properties of CFRP, however, vary in different directions due to its anisotropic behavior. Due to higher tensile strength along the fibers, anisotropy can lead to failure based on directions other than the fiber orientation. A thorough analysis of CFRP core failure modes has been conducted. Experimental analysis, finite element analysis, and micromechanical modeling techniques have been used in these studies. In this research, specific emphasis has been placed on understanding failure behavior under transverse loading conditions. Failure modes have been thoroughly examined in relation to geometric parameters such as interference, wedge angle, and friction coefficient. Modeling CFRP core failure and displacement behavior was carried out using FEA simulations to validate the research findings. A comparison of the obtained results with existing literature ensured that they were accurate and reliable. Additionally, response surface methodology was employed for optimization, aiming to minimize two critical factors: radial compressive stress and core displacement. By minimizing these factors, the performance and reliability of CFRP cores in applications related to grid capacity can be enhanced. The analysis of the research data revealed that the friction coefficient and interference play significant roles as interacting factors, albeit with opposite impacts on the stresses within the CFRP cores. The optimal values for interference and friction coefficient were found to be 0.0224 mm and 0.4, respectively, to minimize radial stress. Furthermore, the wedge angle exhibited a substantial influence on core displacement, with an optimal value of 3.5°.
Diksha Jaurker and Mohan Kumar Pradhan
Inderscience Publishers
M. K. Pradhan and Deepansh Gill
Springer Nature Singapore
Saurabh Jain, M. K. Pradhan, and Amit Kumar
Springer Nature Singapore
Amit Kumar, Mohan Kumar Pradhan, and Saurabh Jain
Springer Nature Singapore
Diksha Jaurker, M. K. Pradhan, Siddharth Jaurker, and Raj Malviya
Springer Nature Singapore
Amit Kumar, Mohan Kumar Pradhan, and Raja Das
SAGE Publications
In addition to dimensions, surface roughness measurement is crucial in every manufacturing. In this study, a trustworthy method for characterising the surface roughness of electrical discharge machined surfaces was developed using a convolutional neural network. Since feature extraction is incorporated into the convolution process of the network, this technique eliminates it. Images of EDMed surfaces were taken using a mobile camera. MATLAB software was used to process a signal vector that was created from the intensity of the picture pixels. A database of specimens with recorded surface roughness values was created. When samples with known surface roughness are given, the proposed technique is a strong contender for real-time surface roughness measurement. The generated predicted values are compared with the measured values acquired from a profilometer using a stylus. The applicability and accuracy of five loss functions are considered before they are chosen and examined for the prediction models. The accuracy and performance of this digital model suggest that it has the capability to assess the surface roughness very well.
M.K. Pradhan
Inderscience Publishers
Mohan Kumar Pradhan and Shubham Gupta
De Gruyter
Rakesh Kumar Patel and Mohan Kumar Pradhan
IOP Publishing
Abstract The substrate deposited on the workpiece is used by surface coating for the achievement of various properties in terms of hardness, smoothness, tear or wear etc But various methods such as electro-plating, conversion coating or several, are less effective because of costly machine involvement, complexity during operation, complexity during work-surface installation, specific (high/low) temperatures and thick coating. To achieve better coating among all, a layer of the modified composite coated surface using Copper (Cu), Molybdenum disulfide (MoS2) and Hexagonal Boron Nitride (HBN) with the help of an Electrical Discharge Machine (EDM) with reverse polarity is formed. In this process, the effect of two variable parameters current and composition (powder mixing ratio) of Cu, MoS2 and HBN with a 50% duty factor on the thickness of the deposited layer is observed. During the deposition process, each green compact electrode is formed by mixing the powdered material in a mortar for approximately 2.5 h and after processing in a hot press moulding machine. The deposited layer of the coating has also been analyzed using FESEM, XRD and tribological properties, where the highest deposition or thickness of the coating has been achieved at a powder mixing ratio of 20/40/40 to Cu/HBN/MoS2 with a current of 10 A at the same duty factor. Overall, better coating with controllable thickness can be achieved by using EDC, which can be helpful in automobiles or other industries where metal-to-metal friction causes performance loss.
Ramesh Kumar Nayak, Mohan Kumar Pradhan, and Ashok Kumar Sahoo
CRC Press
Mohan Kumar Pradhan
Inderscience Publishers
Rajesh Sharma, M.K. Pradhan, and Pankaj Jain
Elsevier BV
Ambuj Pateriya, N. D. Mittal, and M. K. Pradhan
Springer Nature Singapore
Amit Kumar and Mohan K. Pradhan
Springer Nature Singapore
Rakesh Kumar Patel and M. K. Pradhan
Springer Nature Singapore
Deepansh Gill and M. K. Pradhan
Springer Nature Singapore
Diksha Jaurker and M. K. Pradhan
Springer Nature Singapore
Rajesh Sharma, Mohan K. Pradhan, and Pankaj Jain
Springer Singapore
Neeraj Agarwal, Nitin Shrivastava, and M. K. Pradhan
IEEE
Optimization is the act of making the best or most effective use of a situation or resource. It involves maximizing or minimizing a mathematical function. A new and simple metaheuristic optimization algorithm is developed and proposed in this paper as Ananya Algorithm. Simplicity is the beauty of the proposed algorithm. Ananya algorithm is one of the simplest optimization algorithms to implement, among all optimization techniques. This algorithm has only two candidates hence it avoids large calculations. This algorithm moves towards a better solution with the difference between the mean of variables and the best variable. This algorithm works on simple calculations and does not involve any complicated calculations. This algorithm is tested for thirty unconstrained benchmark functions like sphere function, Beale function, Goldstein-Price function, Booth Function, Matyas Function, and convergence graph shown for the same. Every time this algorithm got successful to achieve an optimum solution. It takes a little CPU time to optimize. Ananya algorithm is compared to particle swarm optimization (PSO) and genetic algorithm (GA). It required lesser mean functional evaluation to achieve an optimal solution, hence the Ananya algorithm has better performance than the two algorithms.
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Publications
Nayak, R.K; Pradhan, M. K.; Sahoo, A.K.; Machining of Nanocomposites 2022 CRC Press, Taylor & Francis Group