ML BASED MODELING AND OPTIMIZATION OF CNC TURNING PROCESS PARAMETERS

Abstract

Abstract: In recent times, mechanical and production industries are facing increasing challenges related to the shift towards sustainable manufacturing. In the era of smart manufacturing, production efficiency can be achieved without hampering the quality of the product by optimizing the process parameters. In the present work, the data collected from the machining operations is used for the development of machine learning (ML) based models to test, evaluate and optimize the process parameters of CNC Turning process. Polynomial Regression, Support Vector and Random Forest are applied and the best fit technique is used to develop the model. ML models are used to optimize the process parameters using Teaching and Learning Based Optimization (TLBO)algorithm. The outcome of this work provides tailor-made solutions to enhance the productivity and quality and useful in industries.