Paper Contents
Abstract
This review paper presents a comprehensive analysis of the application of the Taguchi method for optimizing CNC turning parameters, with a focus on improving surface roughness. CNC turning is a fundamental manufacturing process that requires careful selection of machining parameters to ensure product quality and operational efficiency. The Taguchi method, widely applied for design of experiments (DOE), offers a systematic approach to identify optimal parameters using minimal experimental trials This paper reviews various research studies employing the Taguchi method to optimize cutting speed, feed rate, and depth of cut in CNC turning. Additionally, it highlights the integration of computational tools like MATLAB for simulation-based validation. Comparative analysis is conducted to evaluate the effectiveness of different optimization approaches. Research gaps, including limited multi-objective optimization and the lack of real-time validation, are also identified. Recommendations for future research, including hybrid models combining Taguchi with artificial intelligence (AI) and machine learning (ML), are proposed
Copyright
Copyright © 2025 Sakshi Karaiya. This is an open access article distributed under the Creative Commons Attribution License.
