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Hemantha Kumar, A.
- Parametric Analysis of Optimum Cutting Parameters for AISI1042 Using PVD Tool in Turning Operation Using Grey Relation Analysis
Authors
1 SCSVMV University, Kanchipuram, IN
2 Geethanjali Institute of Science and Technology, Nellore, IN
3 Mechanical Engg Dept., SCSVMV University, Kanchipuram, IN
4 Mechanical Engg Dept., AITS, Tirupati, IN
Source
Manufacturing Technology Today, Vol 15, No 3 (2016), Pagination: 3-11Abstract
The paper study is carried out on orthogonal cutting of AISI 1042(EN 41B) carbon steel under dry turning conditions with PVD coated cemented carbide inserts. This paper presents the cutting parameters which influences the Surface roughness (Ra) and Material Removal Rate (MRR) on AISI 1042. Experiments are carried out by conducting experiments based on Taguchi technique considering L27 orthogonal array on a lathe (PSG A141). The process parameters considered for the study are cutting speed, feed rate, and depth of cut and the output parameters are MRR and Ra. A Model has been developed using regression technique and the optimal cutting parameters for minimum surface roughness, and maximum MRR were obtained using Taguchi technique. For predicting the surface roughness, an Artificial Neural Network (ANN) model was designed through back propagation network using MATLAB software for the data obtained. Comparison of the experimental data and ANN results shows that there is no significant difference and ANN was used confidently. Optimal machining parameters were determined by the grey relation grade obtained from the grey relation analysis for multi-performance characteristics (the surface roughness and Material removal rate). The results of confirmation experiments reveal that grey relation analysis coupled with factorial design can effectively be used to obtain the optimal combination of turning parameters. Experimental results have shown that the surface roughness and material removal rate in the turning process can be improved effectively through the new approach.Keywords
AISI No1042 Alloy Steel, PVD Coated Tool, Taguchi Technique, ANN and Grey Relational Analysis.
- Comparison of Optimum Cutting Parameters in Machining Die Steel (EN 31) by using Gray Relational Analysis and TOPSIS
Authors
1 Rayalaseema University, IN
2 Department of Mechanical Engineering, AITS, Tirupati, IN
Source
Manufacturing Technology Today, Vol 16, No 4 (2017), Pagination: 3-11Abstract
Manufacturing industries are undergoing various changes due to the unending need of the customers for qualitative, reliable and sophisticated parts and products in the modern era and technological world. Accompanying the development of mechanical industry, the demands for alloy materials having high hardness and impact resistance are increasing. To meet such requirements manufacturers are make use of EDM machines. EDM are used to cut conductive metals of high hardness or the materials that are difficult to cut or impossible to cut with the traditional methods. The machines are also specialized in cutting complex contours or fragile geometries that would be difficult to be produced using conventional cutting methods. However, environmental impact due to release of toxic emissions aerosols during the process, poor operational safety due to fire hazard, electromagnetic radiation and non-bio degradable waste are the major problems concerned with conventional dielectric fluids (i.e. kerosene, hydro carbon, etc.,). To reduce the problems with conventional die electric fluids waste palm oil blended with kerosene is used. The present work was to examine the effects of process parameters on the machining quality and to obtain optimal process parameters in order to maximize Material Removal Rate and Minimize the Surface Roughness and Dimensional deviation error. The process parameters that are consider for the present work is current (I), voltage (V), pulse on (Pon), and pulse off (Poff) and responses are metal removal rate (MRR), surface roughness (Ra) and dimensional deviation (DD). Comparison of optimum values by using multi objective optimization techniques like Gray Relational analysis (GRA) and TOPSIS.
Keywords
Electric Discharge Machining (EDM), Material Removal Rate (M.R.R), Surface Roughness (Ra), Dimensional Deviation (DD), Gray Relational Analysis (GRA), Technique for Order of Preference by Similarity to Ideal Solution TOPSIS.References
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