Optimisation of Machining Factors for Surface Roughness and Mean Cutting Force of AISI 52100 Steel During Turning Under Microlubrication Condition
Rajarajan.S1, Sivaprakasam.R2
1Rajarajan S, Research Scholar, Department of Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore (Tamil Nadu), India.
2Sivaprakasam R, Professor, Department of Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore (Tamil Nadu), India.
Manuscript received on 05 February 2019 | Revised Manuscript received on 13 February 2019 | Manuscript published on 28 February 2019 | PP: 219-225 | Volume-8 Issue-4, February 2019 | Retrieval Number: D2711028419/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This research work is conducted in order to find the best practicable turning factors to achieve enhanced surface quality cylindrical AISI52100 steel components under microlubrication condition. The turning operation is performed in a turning centre (All Geared Lathe) with CBN insert of 0.8mm nose radius. The turning factors namely feed rate, cutting velocity and depth of cut are preferred to accomplish the experimentation based on Taguchi’s L25(5 3 ) orthogonal array, simultaneously the cutting forces such as feed force, tangential force and thrust force are observed using a calibrated lathe tool dynamometer adapted in the tool holder. The surface roughness of the turned steel alloy components is deliberated by means of a precise surface roughness apparatus. A prediction model in lieu of average surface roughness and mean cutting force is created by means of nonlinear regression examination with the aid of MINITAB software. The most favorable machining settings for surface roughness and mean cutting force are recognized by Taguchi’s method and verified with a confirmation trial.
Keyword: AISI52100, Microlubrication Condition, Surface Roughness, Cutting Force, Lathe, Regression Analysis, Taguchi Method.
Scope of the Article: Machine Design