Faculty Publications
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Item Grinding parameters prediction under different cooling environments using machine learning techniques(Taylor and Francis Ltd., 2023) Prashanth, G.S.; Sekar, P.; Bontha, S.; Balan, A.S.S.Selection of optimum process parameters is vital for performing a sound grinding operation on Inconel 751 alloy. This paper co-relates the relationship between the most influential input parameters like cutting velocity, depth of cut, feed rate, and environmental conditions to the output parameters, namely, tangential grinding forces, normal grinding forces, temperature, and surface roughness. Three types of machine-learning (ML) algorithms such as support vector machine (SVM), Gaussian process regression (GPR), and boosted tree ensemble techniques are employed to develop a ML model for predicting the output variables during grinding operation of Inconel 751. In order to develop a better ML model, K-fold technique is employed on a total of 81 datasets which are extracted from experimental studies. ML models developed from different algorithms are compared based on performance metrics like R2 score and root-mean-square error (RMSE). GPR algorithm exhibits best results with relatively better R2 score and RMSE value in predicting grinding forces and temperature at wheel work interface. From analyzing the ML models, it is found that cooling environments determined the output grinding parameters to a greater extent when compared with the input grinding parameters. © 2022 Taylor & Francis.Item Improving Surface Finish of Laser Additively Manufactured Curvilinear Surfaces Via Electropolishing and Electroless Coating(American Society of Mechanical Engineers (ASME), 2025) Praharaj, A.K.; Kambikath, N.V.; Suvin, P.S.; Bontha, S.Laser-directed energy deposition (LDED) is a very useful additive manufacturing technique for repairing and manufacturing complex-shaped parts compared to traditional manufacturing techniques. However, the inadequate surface quality of the LDED fabricated components limits their direct utilization in different sectors. In addition, improving the surface finish of the curvilinear surfaces (useful for cooling channels and fuel nozzles) is also challenging. Hence, the current study focuses on surface modification of LDED fabricated SS 316L hollow cylindrical samples by combining electropolishing and electroless coating. We have performed electropolishing (two different currents, 8 A and 15 A) on the as-deposited (AD) sample with and without the application of the grinding process. The electropolishing reduced the roughness of the AD sample from 3.2 ?m to 0.85 ?m and 0.74 ?m for 8 A and 15 A, respectively. The reduction in roughness was more at a higher current value due to the rapid anodic dissolution of the surface peaks. A further reduction in roughness was observed when grinding was performed before electropolishing. However, grinding resulted in higher material removal from the deposited surfaces and reduction in roughness was also minimal. Hence, only the electropolishing sample was selected for the next step, in which Ni-P electroless coating was performed on the surface to form a protective layer. After electroless coating, the coefficient of friction and wear-rate were reduced by 9.5% and 25.6% compared to the AD sample. Delamination and severe plastic deformation were the major wear mechanisms for the AD sample, whereas abrasion was dominant for the coated sample. The current work proposes a combined surface modification approach of electropolishing and electroless coating for the LDED processed components with curvilinear surfaces. © © 2024 by ASME.