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Advances in Computational Intelligence in Materials Science

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1st International Conference on Emerging Trends in Mechanical Sciences for Sustainable Technologies

Green Machinability Study of Al 6061 in CNC End Milling using Box Behnken Design and Grey Relational Analysis

Suresh Kumar R, Alagu Vignesh K, Gokulprasanth S and Thillai Ambalanatham A, Centre for Advanced Materials and Testing, Department of Mechanical Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India.

Online First : 07 June 2023
Publisher Name : AnaPub Publications, Kenya.
ISSN (Online) : 2960-2408
ISSN (Print) (Online) : 2960-2394
ISBN (Online) : 978-9914-9946-6-7
ISBN (Print) : 978-9914-9946-7-4
Pages : 076-088

DOI
https://doi.org/10.53759/acims/978-9914-9946-6-7_10
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Abstract

Green Machining (GM), a step towards addressing the means and ways to minimize environmental impact has found inevitable stand among researchers involved in machinability studies. Several means and techniques are being followed and tested with an aim of reducing the adverse effect on environment caused by different manufacturing operations without compromising on quality aspects. The major area focused here is the study of the coolant impact on the process and the environment. Specifically, when the used coolant is disposed without proper treatment causes adverse effect to the health and environment. By considering the environment's effects into account, green machining strategies like dry machining (DM), minimum quantity lubrication (MQL), ice-jet machining, cryogenics etc. are employed for minimizing the usage of coolant along with high quality deliverables. This study focuses on the dry machinability study during the operation and function of end milling on Al6061. The entire experimental analysis were executed as per box-Behnken design (BBD) and grey relational analysis (GRA). The study involved spindle speed (Ss), depth of cut (Dc), and feed rate (Fr) as controlling parameters and responses as average roughness (Ra), material removal rate (Mrr), and power consumption (Pc). A total of 27 experimental runs based on BBD were performed and the responses were analyzed for prediction of optimal solutions.

Keywords

Roughness (Ra), Material Removal Rate (Mrr), Power Consumption (Pc), Box-Behnken Design (BBD), Grey Relational Analysis (GRA).

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Cite this article

Suresh Kumar R, Alagu Vignesh K, Gokulprasanth S and Thillai Ambalanatham A, “Green Machinability Study of Al 6061 in CNC End Milling using Box Behnken Design and Grey Relational Analysis”, Advances in Computational Intelligence in Materials Science, pp. 076-088,June. 2023. doi:10.53759/acims/978-9914-9946-6-7_10

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© 2023 Suresh Kumar R, Alagu Vignesh K, Gokulprasanth S and Thillai Ambalanatham A. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                           

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