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One of the most significant performance indicators for measuring the machinability of materials is tool wear and surface roughness. Choosing the best combination of cutting parameters can help reduce production costs, which is what the manufacturing industry is interested in. At the same time, industries are always looking for an alternative to conventional flood cooling since its use creates an environmental burden and health concerns for the operators. Therefore, vegetable oil-based minimum quantity cooling lubrication (MQCL) is considered a cutting environment. Sunflower oil is utilized as base fluid in MQCL and applied to the cutting zone through a nozzle. The turning experiments are conducted on C45 material which is widely used in various industrial applications, including numerous automotive components. Since flood cooling is widely utilized in machining C45, it is the present-day need to assess alternative cooling and lubricating approaches to avoid the adverse effects of flood cooling. The Taguchi method was used in the present work to minimize surface roughness and tool wear. L9 orthogonal array was constructed, and experiments were performed on C45 steel using coated carbide cutting tools. The statistical approach is utilized to evaluate the effect of cutting parameters on output responses. The optimal cutting settings for cutting speed, feed, and depth of cut to minimize surface roughness are 100 m/min, 0.18 mm/rev, 0.150 mm, and 80 m/min, 0.18 mm/rev, and 0.150 mm for tool wear. According to the findings, cutting speed, feed rate, and depth of cut varied surface roughness by 1.9%, 78.3%, and 14.04%, and tool wear by around 43.8%, 37.9%, and 6.3%, respectively. The outcomes can be useful to metal-cutting industries to identify the combination of machining parameters with vegetable oil-based MQCL.


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Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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