Faculty Publications

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Author: search.filters.author.Dayananda Pai, D.Subject: search.filters.subject.Metal matrix composites

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    Application of response surface methodology and enhanced non- Dominated sorting genetic algorithm for optimisation of grinding process
    (Elsevier Ltd, 2013) Dayananda Pai, D.; Rao, S.; D'Souza, R.
    Optimisation of grinding process during grinding of A16061-SiC composites is investigated in this study. Stir cast A16061-SiC composites with varying volume percentage of SiC reinforcement were ground on a conventional grinding machine with diamond grit grinding wheel. Three grinding variables were studied for simultaneous optimization of material removal rate and surface roughness. Initially, the response surface models for grinding process parameters were developed using response surface methodology. Further, the developed models were optimized using enhanced elitist non-dominated sorting genetic algorithm (enhanced NSGA-II), a time saving algorithm in comparison to conventional NSGA-II. The suitable grinding conditions for multi-objective optimization of the grinding process were obtained from enhanced NSGA-II. Finally the confirmation tests were performed to validate the results obtained from response surface methodology and enhanced NSGA-II. It is observed that, experimental results and the results obtained from enhanced NSGA-II are in close conformance. Hence it is concluded that the developed algorithm can effectively be used for optimization of grinding process. © 2013 The Authors. Published by Elsevier Ltd.
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    Application of response surface methodology on surface roughness in grinding of aerospace materials (6061Al-15Vol%SiC25P)
    (2010) Dayananda Pai, D.; Rao, S.S.; Shetty, R.; Nayak, R.
    In this paper, the effects and the optimization of machining parameters on surface roughness in the grinding of 6061Al-SiC25P (MMCs) specimen are investigated. In the grinding process, a machining parameter, such as hardness of the specimen, flow rate of the coolant and depth of cut while machining were chosen for evaluation by the response surface methodology. By response surface methodology, a complete realization of the process parameters and their effects were achieved. The variation of surface roughness with machining parameters was mathematically modeled using response surface methodology. Finally, experimentation was carried out to identify the effectiveness of the proposed method. © 2006-2010 Asian Research Publishing Network (ARPN). All rights reserved.