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Dadakhalandar, S.
- Prediction and Optimization of Flank Wear and Surface Roughness in Down Milling of Al- 7075+ (Al2O3)P MMC Using Ti-N Coated Helical Milling Cutter
Authors
1 Department of Mechanical Engineering, Sri Venkateswara University College of Engineering, Tirupati-517502, A.P., IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 8, No 3 (2016), Pagination: 116-119Abstract
During milling operations of Aluminum Metal Matrix Composites (AMMC) by using plain HSS cutters, some problems arise because of the fabrication of reinforced particles. To achieve this problem, coated helical milling cutters are used to minimize the wear rate and better surface finish. In this study, flank wear is observed on Titanium Nitride (Ti-N) coated milling cutters in down milling of Al-7075+ 4% Al2O3-p, afterwards the wear rate of the cutter and surface roughness of composite were investigated. Image processing tool in MATLAB is adopted to measure the wear rate on both the axes of cutter and surface roughness (Ra) of the MMC's measured by using Talysurf meter. In this work, the input parameters speed, feed rate and depth of cut were taken in a range of low, medium and high; coolant conditions are dry, soluble oil and diesel. The optimum milling parameters were found by using Fuzzy- Taguchi optimization method and the practical results were compared by Fuzzy prediction values. It is observed that tool wear and surface roughness were lower at higher cutting speed, lower feed rates and lower depth of cuts when soluble oil is used as coolant and the variation between experimental data and predicted data is comparatively less.Keywords
Aluminum Metal Matrix Composite, Flank Wear, Surface Roughness, Down Milling, Fuzzy-Taguchi, MRPI, Fuzzy Prediction.
- An Experimental Study on Influence of Coolants in Down Milling of AMMC using Ti-N coated HSS Cutter
Authors
1 Dept. of Mechanical Engineering, Sri Venkateswara University College of Engineering, Tirupati, Andhra Pradesh, IN
Source
Manufacturing Technology Today, Vol 15, No 3 (2016), Pagination: 24-30Abstract
In recent years, many researchers and authors have been investigating various aspects of Aluminium Metal Matrix composites (AMMC) because of their combined mechanical and thermal properties. It becomes a significant task to study the behaviour of AMMC during machining. By observing previous approaches on AMMC, machining of composites is very difficult under normal conditions. During milling process of AMMC using Ti-N coated HSS cutter, some problems arise because of the reinforced particles fabricated in it. High temperatures and poor surface quality were observed at shear zone during machining.
In this context, Aluminium metal matrix composite material is selected as Al- 6061+ 2% Al2O3 and Titanium Nitride (Ti-N) coated HSS helical milling cutter having a size more than composite work piece is selected. The input parameters were taken as speed, feed rate, depth of cut in a range of low, medium and high and coolants are Dry, soluble oil and veg. oil to perform the experiment. Because of various applications and reliable properties of AMMC in advance manufacturing systems, nanotechnology, mechatronics, cryogenics etc., the output parameters were selected as temperature (T) and surface roughness (Ra). Afterwards, Taguchi design of experiments L18 is adopted for the experiment. The values of temperature and surface roughness are noted and the optimal input machining conditions are found by using Fuzzy- Taguchi optimization technique with reference to normalized values followed by their corresponding S/N ratios of output parameters.
The effective optimum results were found by using Fuzzy- Taguchi technique and the variation between experimental and Fuzzy predicted data has been compared and concluded.