Faculty Publications
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Item Influence of milling parameters on Al-Li alloy surface characteristics(Elsevier Ltd, 2023) Marakini, V.; Srinivasa Pai, P.; Udaya Bhat, K.; Thakur, D.S.; Achar, B.P.Lightweight alloys attract the aerospace industries due to their high specific strength. Al-Li alloy has been investigated in the present study to identify their functional performance in terms of surface characteristics namely surface roughness and hardness. Dry face milling was performed using uncoated carbide inserts for the experimental conditions obtained from Taguchi L27 design of experiments. The effect of milling parameters, such as feed rate, cutting speed and depth of cut on surface roughness and hardness have been investigated and presented. Further, the optimal milling conditions are identified using statistical techniques – Grey Relational Analysis (GRA) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The study showed that feed rate is the most influential parameter on both surface characteristics. Both GRA and TOPSIS showed similarity in identifying the same condition as optimal for milling Al-Li alloy under dry condition. © © 2023 Elsevier Ltd. All rights reserved.Item High Speed Machining for Enhancing the AZ91 Magnesium Alloy Surface Characteristics: Influence and Optimisation of Machining Parameters(Defense Scientific Information and Documentation Centre, 2022) Marakini, V.; Srinivasa Pai, P.; Udaya Bhat, K.; Thakur, D.S.; Achar, B.P.In this study, optimum machining parameters are evaluated for enhancing the surface roughness and hardness of AZ91 alloy using Taguchi design of experiments with Grey Relational Analysis. Dry face milling is performed using cutting conditions determined using Taguchi L9 design and Grey Relational Analysis has been used for the optimisation of multiple objectives. Taguchi’s signal-to-noise ratio analysis is also performed individually for both characteristics and grey relational grade to identify the most influential machining parameter affecting them. Further, Analysis of Variance is carried to see the contribution of factors on both surface roughness and hardness. Finally, the predicted trends obtained from the signal-to-noise ratio are validated using confirmation experiments. The study showed the effectiveness of Taguchi design combined with Grey Relational Analysis for the multi-objective problems such as surface characteristics studies. © 2022, DESIDOCItem Enhancing the surface integrity characteristics of Al-Li alloy using face milling(Elsevier B.V., 2022) Marakini, V.; Srinivasa Pai, P.; Udaya Bhat, K.; Thakur, D.S.; Achar, B.P.This work presents the milling induced surface integrity investigation of Al-Li alloy. The effect of milling on the surface roughness, microhardness, microstructure, and residual stress is studied. Uncoated carbide inserts are used for milling due their superior hardness and greater life, when machining softer materials such as aluminium and its alloys. Results show that the minimum surface roughness (Ra = 0.043 µm) and maximum microhardness (216 HV) are achievable from the milling process, when compared with the roughness (Ra = 0.528 µm) and microhardness (180 HV) of the as-received material. Results indicate limited harm to alloy microstructure from the milling process and the presence of compressive residual stress induced from milling. The work finds scope for aerospace applications. © 2022 Elsevier B.V.Item High-speed face milling of AZ91 Mg alloy: Surface integrity investigations(KeAi Publishing Communications Ltd., 2022) Marakini, V.; Pai, S.P.; Bhat K, U.K.; Thakur, D.S.; Achar, B.P.Magnesium (Mg) alloys are popular in the aerospace and automotive sector owing to their light-weight aspects. Amongst various Mg alloys, AZ91 alloy behaviour under machining has been trending and needs to be completely explored. The selection of optimal machining parameters is an important decision making process to achieve highest quality along with reduced cost and time. In this regard, this article describes experimental investigations to evaluate the performance of face milling operations on the surface characteristics of AZ91 magnesium alloy. The experiments were carried out with uncoated and PVD (Physical Vapour Deposition) coated carbide inserts at three levels of cutting speed (500, 700 and 900 m/min), feed rate (0.1, 0.2 and 0.3 mm/teeth) and depth of cut (0.5, 1.0 and 1.5 mm) under dry machining conditions. Major surface integrity indicators, such as roughness, hardness, residual stresses and microstructure are analysed. Chip morphology is also analysed and the correlation between chips and machined surface roughness is established. Face milling operation significantly improved surface roughness and microhardness of this alloy. Roughness improvement up to 85% (0.067 μm) and hardness improvement up to 33% (91.8 HV) is observed from the use of uncoated carbide inserts. Whereas, from PVD coated inserts, roughness improvement up to 81% (0.083 μm) and hardness improvement up to 60% (111.2 HV) is achieved. A similarity in behaviour between the two types of insert conditions are observed with increase in roughness from feed increase and decrease in hardness from cutting speed increase. Microstructural analysis showed PVD coated insert conditions producing surface with no defects, when compared to the crack observed in the surface from the use of uncoated carbide inserts. Marginally higher compressive residual stresses are detected at the surfaces from use of the uncoated inserts. Overall, due to no surface defect and the significant improvement in hardness and roughness from the PVD coated inserts, they are recommended for use in face milling operation for the cutting conditions investigated in this study. © 2022 The AuthorsItem Effect of High-Speed Dry Face Milling on Surface Integrity Characteristics of AZ91 Mg Alloy(Springer, 2023) Marakini, V.; Pai, S.P.; Bhat K, U.K.; Thakur, D.S.; Achar, B.P.In the present study, high-speed dry face milling is performed on AZ91 magnesium alloy using uncoated carbide inserts. The most influential surface integrity characteristics, such as surface roughness, hardness, microstructure and residual stresses, are investigated for a set of milling parameters chosen from the Taguchi design of experiments. The impact of machining conditions, such as feed rate, cutting speed and depth of cut on the surface integrity characteristics, are identified in order to improve the overall functionality of the alloy. Grey Relational Analysis optimization method is implemented to identify the optimal milling conditions. The results showed that high-speed dry face milling is very influential in improving the overall surface integrity characteristics of this alloy. © 2022, ASM International.Item Meta-heuristic algorithm based optimization studies in cryogenic and conventional milling of magnesium alloy AZ91(Elsevier B.V., 2025) Marakini, V.; P, S.P.; D'Mello, G.; Bhat K, U.; Thakur, D.; Achar, B.P.The surface finish of a machined product is essential for assessing its quality and other attributes. Modeling the surface roughness and hardness of a machined component is challenging for several reasons. The present study examines the effectiveness of four meta-heuristic algorithms in optimizing surface characteristics like roughness (Ra) and hardness (HV) in the machining of magnesium alloy AZ91. Experiments with uncoated carbide inserts have been conducted under dry and cryogenic conditions. The study's input parameters are the depth of cut, feed rate, and cutting speed. Modeling and prediction studies have been conducted using Multi Layered Perceptron (MLP) Neural Network, and the output of this model has been considered as the objective function for the optimization algorithms. Algorithms, namely Particle Swarm Optimization (PSO), Bat Algorithm (BA), and recently developed algorithms, namely Jaya Algorithm (JAYA) and Fruit Fly Optimization Algorithm (FOA), have been tested. The optimization accuracy of FOA has been found to be superior to that of the other algorithms. As per the knowledge of the authors, this work probably presents a first attempt in applying the JAYA and FOA metaheuristic algorithms in the machining studies of an AZ series magnesium alloy. © 2025 The Authors