Optimization of CNC Turning Parameters in Machining EN19 using Face Centered Central Composite Design Based RSM
M. V. Satish Kumar1, M. Pradeep Kumar2, S. Vamshi Krishna3, K. Vikram Kumar4
1Dr. M. V. Satish Kumar, Professor and head, Department of Mechanical, Kamala Institute of Technology and Science, Karimnagar, Telangana.
2Mr. M. Pradeep Kumar, Assistant Professor, Department of Mechanical, Kamala Institute of Technology and Science, Karimnagar, Telangana.
3Mr. S. Vamshi Krishna, Assistant Professor, Department of Mechanical, Kamala Institute of Technology and Science, Karimnagar, Telangana.
4Mr. K. Vikram Kumar, Assistant Professor, Department of Mechanical, Kamala Institute of Technology and Science, Karimnagar, Telangana.
Manuscript received on July 11, 2020. | Revised Manuscript received on July 21, 2020. | Manuscript published on July 30, 2020. | PP: 889-896 | Volume-9 Issue-2, July 2020. | Retrieval Number: B3923079220/2020©BEIESP | DOI: 10.35940/ijrte.B3923.079220
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© 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: Manufacturing a defect free (quality) product is playing a vital role in today’s globally competitive, customer oriented era. Meeting the demand of the market by producing sufficient quantity is another challenge. Achieving greater production rates without compromising on quality, increases the complexity of the task. Adopting modern manufacturing methods like CNC turning are essential to meet the above requirements. EN19 is an important member in the family of alloy steels, which has a wide variety of applications in automobile and machine tool industries. Optimization of machining parameters is crucial in obtaining the required outputs such as quality and productivity. In this work, optimization of CNC turning parameters for machining EN19 alloy steel is performed. The number of experiments was designed using face centred central composite based response surface methodology with varied independent process parameters namely cutting speed, feed and depth of cut. After designing the experiments, the performance measures such as surface roughness of the test samples and Material Removal Rate (MRR) is calculated using the existing formulae. The influence of parameters on MRR and surface roughness are determined by analysis of variance (ANOVA) and for significance interactions of the process parameters are also considered. Using MINITAB 17 software analysis is performed. Further, regression analysis has been done and second order mathematical model is obtained. Using desirability approach, optimization is carried out.
Keywords: Optimization, Response surface methodology, Machining.