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Sustainable green cutting fluid for interpreting optimization of process variables while machining on various CNC manufacturing systems—an experimental approach for exploring

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Abstract

Sustainable metal machining always results in reduction in overall global environmental impacts such as material waste, power utility, and pollution, in machining industries. Even though there are several literature studies on eco-friendly cutting fluids, but they confine the applications to a single metal machining system only. Hence, this present work firstly prioritizes understanding of the role of various sustainable cutting fluids (viz. water-soluble oil, rice bran oil, coconut oil and neem oil) by analyzing the multi-response optimization (viz. application of VIKOR method) on lathe machine facing operation and thus exploring the optimal process variables. In addition, comparative study of the sustainable cutting fluids under consideration with their viscosities and wettability is added to enhance an in-depth comprehensive understanding of their role. Secondly, the estimated optimal eco-friendly cutting fluid (in this work, the neem oil) is adopted in two different machining systems such as computer numerical control (CNC) lathe system (3-axis facing) operations and a CNC turn-mill system (4-axis co-axial) operations for analyzing the machining responses with regard to their individual optimization and moreover, to correlate assessing of the machining parameters (viz. spindle speeds, tool feeds, and depth of cuts) on the generated responses using analysis of variance.

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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were prepared by all the authors. The first draft of the manuscript was written by [Kothapalli Arun Vikram] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Kothapalli Arun Vikram.

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Ramena, D.V.P., Vikram, K.A., Chebolu, R. et al. Sustainable green cutting fluid for interpreting optimization of process variables while machining on various CNC manufacturing systems—an experimental approach for exploring. Int J Adv Manuf Technol (2024). https://doi.org/10.1007/s00170-024-14028-2

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