Abstract
This study focuses on the prediction of cutting force, tool flank wear and surface roughness with extreme pressure (EP) additive included vegetable-based cutting fluids (VBCFs) using fuzzy logic and regression. Cutting force, tool flank wear and surface roughness are measured during turning of AISI 1040 steel according to L9 orthogonal array. A model depends on fuzzy logic is established, and the results obtained from fuzzy logic are compared with the results from regression and experimentation. Fuzzy logic model gives closer values to experimental results than the regression model. It has been concluded that fuzzy rule-based modelling helps in predicting cutting force, surface roughness and tool flank wear. Confirmation experiment results revealed that fuzzy logic model is better than regression model for predicting cutting force, tool wear and surface roughness in turning.
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Satheesh Kumar, B., Parimala, N., Vamsi Krishna, P. (2020). Fuzzy Logic and Regression Modelling of Machining Parameters in Turning AISI 1040 Steel Using Vegetable-Based Cutting Fluids with Extreme Pressure Additive. In: Voruganti, H., Kumar, K., Krishna, P., Jin, X. (eds) Advances in Applied Mechanical Engineering. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-1201-8_121
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DOI: https://doi.org/10.1007/978-981-15-1201-8_121
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