Open Access
Javvadi Eswara Manikanta
B. Naga Raju
Chitrada Prasad
Naveen Kumar Gurajala
N Malleswararao Battina
- Research Scholar Trans-Disciplinary Research Hub Andhra Pradesh India
- Professor Department of Mechanical Engineering Andhra Pradesh India
- Assistant Professor Department of Physics, Aditya College of Engineering Andhra Pradesh India
- Assistant Professor Department of Mechanical Engineering, CMR College of Engineering and Technology Hyderabad India
- Assistant Professor Department of Mechanical Engineering, Shri Vishnu Engineering College for Women Andhra Pradesh India
Abstract
The machining industry’s evolving environmental consciousness has prompted a growing demand for cutting fluids devoid of chlorine and sulphur, thus fostering sustainable machining practices. This surge in demand is driven by mounting apprehensions over environmental contamination and worker safety. As the industry transitions to modern cutting fluids, it becomes imperative to comprehend their effectiveness and the optimal machine parameters required for their deployment in the turning process. In our current study, we employ the Taguchi technique in conjunction with Grey Relational Analysis (GRA) to assess the efficacy of parameter optimization and its impact on the turning of SS 304 steel, utilizing non-toxic, biodegradable vegetable-based cutting fluids. Our investigation delves into the influence of various process variables, including cooling conditions (CC), cutting speed (Vc), feed rate (f), and depth of cut (a), on critical response parameters like Cutting Force (CF) and Surface Roughness (SR). This is accomplished through rigorous Analysis of Variance (ANOVA) to identify the parameters of significant influence. The study reveals that employing the Minimum Quantity Lubrication (MQL) method at a cutting speed of 1000 revolutions per minute, a feed rate of 90 mm/minute, and a 0.3 depth of cut leads to substantial enhancements in machining performance. The microstructure of the optimized sample is investigated through the use of a Scanning Electron Microscope. Optimally, MQL machining at Vc 1000 rpm, f 90 mm/min, and a 0.3 mm minimized CF. Additionally, the type of cutting coolant (CC), a, Vc, and f contributed 77.77%, 6.54%, 4.606%, and 2.328%, respectively, to CF reduction.
Keywords: Eco friendly cutting fluids, Turning, Minimum Quantity Lubrication (MQL), Surface roughness, cutting force, Optimization.
[This article belongs to Special Issue under section in Journal of Polymer and Composites(jopc)]
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References
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Journal of Polymer and Composites
Volume | 11 |
Special Issue | 12 |
Received | October 30, 2023 |
Accepted | January 5, 2024 |
Published | April 1, 2024 |