http://technology.eurekajournals.com/index.php/IJETMPE <p style="text-align: justify;">International Journal on Emerging Trends in Mechanical &amp; Production Engineering (IJETMPE) is an attempt of Eureka Group of Journals to bridge the gap between "Campuses and Corporate" by including both academic research activities as well as the innovation done on industries and corporate professionals in the domain of Mechanical &amp; Production Engineering.&nbsp;IJETMPE provides a platform for the researchers, academicians, professional, practitioners and students to impart and share knowledge in the form of high quality empirical and theoretical research papers, case studies, literature reviews and book reviews. The journal focuses on a fast peer review process of submitted papers to ensure accuracy, relevance of articles and originality of papers.. This journal is not limited to the manufacturing side improvement but it also includes management inside the manufacturing units, solutions of problems arising due to capacity addition by adoption of new technology in industries for their existing units as well as for new proposed units.</p> en-US admin@eurekajournals.com (Eureka Journals) Sat, 05 Apr 2025 09:19:51 +0000 OJS 3.0.0.0 http://blogs.law.harvard.edu/tech/rss 60 http://technology.eurekajournals.com/index.php/IJETMPE/article/view/832 <p>The machining industry continuously strives to achieve high-quality components characterized by superior surface finish, dimensional accuracy, and durability, all while ensuring cost efficiency and environmental sustainability. This study focuses on the optimization of machining parameters in the turning of EN24 and EN31 alloy steels to minimize surface roughness, a key indicator of product quality. The specific objectives were to evaluate the effects of cutting speed, depth of cut, and feed rate on surface roughness, determine optimal parameter settings, and develop a predictive mathematical model for surface quality.</p> <p>The methodology involved conducting turning experiments on a CNC lathe using coated carbide inserts (ISO TNMG 160408). Surface roughness was measured using a precision roughness tester, and experiments were designed using the Taguchi Method with an L9 orthogonal array. The analysis was performed using Minitab software, which facilitated the generation of main effect and interaction plots to understand the influence of individual and combined machining parameters. Results indicated that cutting speed and feed rate were the most significant factors affecting surface roughness, whereas the depth of cut showed minimal impact. A mathematical model was developed to predict surface roughness based on the experimental data, offering a practical tool for process planning.</p> <p>The study concludes that optimizing machining parameters can significantly improve surface finish, thereby enhancing component performance and longevity. This research contributes to the field of precision manufacturing by providing a systematic approach to parameter optimization, which can be adopted across various industrial applications. The findings not only enable manufacturers to produce high-quality components more efficiently but also reduce resource wastage and operational costs, aligning with sustainable manufacturing goals. This work highlights the practical value of integrating robust experimental designs and statistical tools in machining process optimization.</p> Amarjeet Singh Sandhu http://technology.eurekajournals.com/index.php/IJETMPE/article/view/832