Contribution of Factors such as Machining Parameters, MQL Nozzle Orientation (Angle & Distance) and MQL Nano-Fluid Type on Surface Finish of Turned Steel Work-Pieces Using DOE Approach
| Autor: | Bhushan T. Patil, Vasim A. Shaikh, D. S. S. Sudhakar, Miriyala Veerabhadrarao |
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| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Work (thermodynamics) Materials science Mechanical Engineering Nozzle Mechanical engineering 02 engineering and technology Surface finish Condensed Matter Physics 020303 mechanical engineering & transports 020901 industrial engineering & automation Nanofluid 0203 mechanical engineering Machining Mechanics of Materials Orientation (geometry) Surface roughness General Materials Science |
| Zdroj: | Materials Science Forum. 1019:181-193 |
| ISSN: | 1662-9752 |
| DOI: | 10.4028/www.scientific.net/msf.1019.181 |
| Popis: | Study of input factors play a vital role in controlling of process responses such as surface finish, cutting temperature, energy consumption etc. in machining process. Design of Experiment (DOE) is one such tool used by researchers to identify the key factors and levels and optimize the process.An attempt was made to identify and experiment turning of AISI 4340 steel using 6 factors viz. cutting speed, feed rate, depth of cut, MQL nozzle orientations (distance from the cutting tool-chip interface, nozzle angle) and different cutting fluid (Coolant). The response variable selected for study was surface roughness of the work-piece which needed to fit criteria smaller-the-better. L25 Orthogonal Array-OA design was selected for 6 factors and 5 levels. Comparison of results of average responses of different levels of factors, analysis of variance (ANOVA) of the process is detailed. Experimental results showed that the key contributors in the turning process are due to cutting speed, feed and depth of cut covering from 12% to 40%. The major contributor to the process was the cutting speed. Selection of MQL fluids and nozzle orientation contributed to 10% showing least significance.This experiment helps us to understand the importance of machine cutting conditions as key success factors which can be assisted with MQL fluids and other input factors. |
| Databáze: | OpenAIRE |
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