Mechanics & Industry
Volume 21, Number 6, 2020
|Number of page(s)||17|
|Published online||16 October 2020|
Investigation on hard turning temperature under a novel pulsating MQL environment: An experimental and modelling approach
School of Mechanical Engineering, KIIT University, Bhubaneswar-24, Odisha, India
* e-mail: email@example.com
Accepted: 27 September 2020
Generation of total heat in hard turning largely influenced the cutting tool wear, tool life and finishing quality of work-surface. Thus, the measurement of this heat in terms of temperature becomes a necessity for achieving favourable machining performances. Therefore, this work presents a novel study on temperature measurement in three different zones during hard turning operation of 4340 grade steel under pulsating MQL environment. Temperatures are measured at three different locations namely chip-tool interface, flank face, and machined work surface (near to tool-work contact) and the location wise temperature is termed as chip tool interface temperature (T), flank face temperature (Tf) and machined work surface temperature (Tw) correspondingly. The temperature T and Tf are measured with help of K-type thermocouple while Tw is measured by Fluke make infra-red thermal camera. Pulsating MQL significantly reduced the temperature as the maximum temperature is noticed 110 °C which corresponds to chip-tool interface temperature (T) at highest speed (200 m/min) condition. In each test, the order of temperature follow the trend as: T > Tf > Tw. Considering average of all 16 temperatures, T is 14.42% greater than Tf and 39.36% larger than Tw while Tf is 21.79% greater than Tw. Experimental results concludes that the cutting speed is the most influencing factor followed by depth of cut for both T and Tf, whereas depth of cut is the most influencing factor for Tw. Further, these temperatures are predicted using linear regression, and absolute mean error (MAE) for responses T, Tf, and Tw is noticed as 1.848%, 0.542%, and 3.766% individually. Additionally, the optimum setting of input terms are estimated using WPCA (weighted principal component analysis) and found to be dc1 (0.1 mm) − fr2 (0.08 mm/rev) − vc2 (100 m/min) − Pt2 (2 s).
Key words: Hard turning / pulsating MQL / temperature / linear regression / WPCA
© AFM, EDP Sciences 2020
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