Optimize input parameter for CNC Turning process for MRR and surface finish using Machine Learning
Keywords:
CNC Turning, Material Removal Rate (MRR), Machine LearningAbstract
Optimizing machining parameters in CNC turning is crucial for enhancing productivity, improving surface quality, and reducing manufacturing costs. This study aims to optimize key input parameters cutting speed, feed rate, and depth of cut maximize Material Removal Rate (MRR) and achieve a superior surface finish using Machine Learning techniques.
References
Zhujani, F., Abdullahu, F., Todorov, G., & Kamberov, K. (2024, February 2).Optimization of Multiple Performance Characteristics for CNC Turning of Inconel 718. 2. Ntukidem, A., Achebo, O., Ozigaguna, U., Uwoghiren, F.O., & Obahiagbon, K.O. (2024, May 9). Optimization of Material Removal Rate in Computer Numerical Control Lathe Machine in Turning AISI 1040 Steel.
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Published
2024-10-12
How to Cite
Roy Ranson D Cruz , Manish Thakur , Sunil Patidar , Ram Janm Singh Durvesh Deth , Swaraj Disawal. (2024). Optimize input parameter for CNC Turning process for MRR and surface finish using Machine Learning. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2124–2133. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/1991
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