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Venkataramaiah, P.
- Prediction of Surface Roughness in Drilling of Al 7075/10% - SiCp Composite under MQL Condition using Fuzzy Logic
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Authors
Affiliations
1 Department of Mechanical Engineering, Sri Venkateswara University, Tirupati- 517502, IN
1 Department of Mechanical Engineering, Sri Venkateswara University, Tirupati- 517502, IN
Source
Indian Journal of Science and Technology, Vol 8, No 12 (2015), Pagination:Abstract
The main aim of this study is to examine the influence of drilling parameters on Aluminium Metal Matrix Composite (Al7075/10% - SiCp). The Drilling experiments were conducted according to Taguchi L27 orthogonal array on Al7075/10% - SiCp composite with uncoated and coated HSS tools under MQL environment. The input parameters were used is speed, feed, tool material, point angle and cutting environment for 3 levels. This composite is fabricated using 53 μm sized SiC particles reinforced into aluminium matrix material via stir casting process. The surface roughness is considered as experimental result and it is predicted using fuzzy logic. The results specify that the predicted surface roughness values and experimental surface roughness values are close to each other and surface roughness can be predicated efficiently by fuzzy logic modeling technique.Keywords
Al7075/10% - SiCp Metal Matrix Composite, Drilling, Surface Roughness (Ra), Fuzzy Logic Modeling, Stirr CastingFull Text
- 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
Abstract Views :189 |
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Authors
Affiliations
1 Department of Mechanical Engineering, Sri Venkateswara University College of Engineering, Tirupati-517502, A.P., IN
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
Abstract Views :195 |
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Authors
Affiliations
1 Dept. of Mechanical Engineering, Sri Venkateswara University College of Engineering, Tirupati, Andhra Pradesh, IN
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.
Keywords
Aluminium Metal Matrix Composite (AMMC), Slab Milling, Talysurf Meter, Laser Thermometer, Fuzzy-Taguchi Method.- Analysis of Surface Roughness, Material Removal Rate and Temperature in Milling of En 31 for Die Making under Minimum Quantity Lubirication Condition
Abstract Views :266 |
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Authors
Affiliations
1 S V University, Tirupati, IN
1 S V University, Tirupati, IN
Source
Manufacturing Technology Today, Vol 16, No 2 (2017), Pagination: 11-17Abstract
Conventional milling process remains its importance as it is flexible in cutting dovetails, keyways and slots etc., although Non-traditional machining process are playing major role in machining industry. In other hand Minimum Quantity Lubrication (MQL) refers a little (50-5600ml/hr) lubricant dispensing system which is the substitute for the flood type lubricating system which dispenses 20 L/h of lubricant. In this work, milling experiments are conducted on En-31 material for making die using solid carbide tool and HSS tools under MQL condition. The effect of process parameters such as speed (S), depth of cut (DOC), coolant type (CT), tool material (TM), and amount of coolant dispensed (ACD) on cutting temperature, material removal rate and surface roughness is investigated. A special setup is prepared for regulating the minimum quantity of lubricant. The responses such as Temperature, Material Removal Rate and Surface Roughness are measured and regression models are developed for these responses. Regression models are solved using Particle Swarm Optimization (PSO) technique.Keywords
Milling Operation, Particle Swarm Optimization, En 31, MQL Setup.References
- Anand Babu, K; Vijaya Kumar, G; Venkataramaiah, P: Prediction of Surface Roughness in Drilling of Al 7075/10% - SiCp Composite under MQL Condition using Fuzzy Logic, ‘Indian Journal of Science and Technology’, vol. 8, no. 12, 2015, 54074.
- Tunc, Lutfi Taner; Gu, Yuchen; Burke, Mary Grace: Effects Of Minimal Quantity Lubrication (MQL) On Surface Integrity In Robotic Milling Of Austenitic Stainless Steel, ‘Peer-review under responsibility of the scientific committee of the 3rd CIRP Conference on Surface Integrity (CIRP CSI)’, doi: 10.1016/j.procir.2016.
- Kedare, SB; Borse, DR; Shahane, PT: Effect of Minimum Quantity Lubrication (MQL) on Surface Roughness of Mild Steel of 15HRC on Universal Milling Machine, ‘3rd International Conference on Materials Processing and Characterization', ICMPC, 2014.
- Goyal, Anurag; Jasvir, S; Tiwana, Amrit Pal: A Review study on Minimum Quantity Lubrication in Machining, ‘International Journal of Recent Development in Engineering and Technology’, ISSN: 2347 - 6435, vol. 2, no. 5, May 2014.
- Hossain, Md. Shahriar Jahan; Ahmad, Nafis: A neuro-fuzzy approach to select cutting parameters for commercial die manufacturing,’ 10th International Conference on Mechanical Engineering, ICME 2013, 'Procedia Engineering', vol. 90, 2014, 753 - 759.
- Loginsa, Andris; Torimsa, Toms: The Influence of High-Speed Milling Strategies on 3D Surface Roughness Parameters, 25th DAAAM International Symposium on Intelligent Manufacturing and Automation, 2014, 'Procedia Engineering', vol. 100, 2015, 1253 - 1261.
- Jurkovic, J; Korosec, M; Kopac, J: New approach in tool wear measuring technique using CCD vision system,’ International Journal of Machine Tools and Manufacture’, vol. 45, no. 9, 2005, 1023-1030.
- Rajesh Choudhary; Kumar, H; Garg, RK: Analysis and Evaluation of Heat Affected Zones in Electric Discharge Machining of EN 31 Die Steel,’ Indian Journal of Engineering & Material Sciences’, vol. 17, 2010, 91-98.
- Dave, HK; Patel, LS; Raval, HK: Effect of machining conditions on MRR and surface roughness during CNC Turning of different Materials Using TiN Coated Cutting Tools – A Taguchi approach, ‘International Journal of Industrial Engineering Computations', vol. 3, no. 5, April 2012, 925-930.
- Arunkumar, N; Rawoof, Shareef Abdur H; Vivek, R: Investigation on the Effect of Process Parameters For Machining of EN31 (Air Hardened Steel) By EDM, ‘International Journal of Engineering Research and Applications (IJERA)’, ISSN: 2248-9622, www.ijera.com, vol. 2, no. 4, July-August 2012, 1111-1121.
- Tsai, CY; Yeh, SW: A Multiple objective particle swarm optimization approach for Inventory Classification,’ 'International Journal of Production Economics', vol. 114, no. 2, Feb 2008, 656-666.
- Sreenivasa Rao, M; Venkaiah, N: Parametric Optimization In Machining of Nimonic-263 Alloy Using RSM And Particle Swarm Optimization,’ 2nd International Conference on Nanomaterials and Technologies (CNT 2014)’, Procedia Materials Science 10, 2015, 70-79.
- Cus, F; Zuperl, U; Gecevska, V: High speed end-milling optimization using Particle Swarm Intelligence, ‘Journal of Achievements in Materials and Manufacturing Engineering’, www.journalamme.org, vol. 22, no. 2, June, 2007.
- Rajyalakshmi, G; Koushik, Thatipally; Kalyan, Tammu: Parametric Optimization In Wedm Using Particle Swarm Optimization Technique, ‘Proceedings of 56th IRF International Conference’, 29th May, 2016, Pune, India, ISBN: 978-93-86083-26-5.
- James, Kennedy; Russell, Eberhart: Particle Swarm Optimisation, ' Proceedings of IEEE International Conference on Neural Networks', vol. 4, 1942–1948. doi:10.1109/ICNN.1995.488968
- Development of Fuzzy Logic Technique for Modeling Surface Roughness in Drilling of EN24 Steel with Coated Tools
Abstract Views :149 |
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Authors
Affiliations
1 Department of Mechanical Engineering, S. V. University, Tirupati, A. P., IN
1 Department of Mechanical Engineering, S. V. University, Tirupati, A. P., IN
Source
International Journal of Scientific Engineering and Technology, Vol 3, No 11 (2014), Pagination: 1391-1396Abstract
The present paper focused on the application of fuzzy logic for predicting the surface Roughness (Ra) in drilling of EN24 Steel using uncoated and coated tools. For conducting drilling experiments Taguchi L16 orthogonal array was used. The Taguchi method and Analysis of Variance (ANOVA) is employed to find out the influences of machining parameters on surface roughness for their optimization. The machining parameters used in the experiment were drilling speed, feed, tool type and coolant. The obtained experimental results were analyzed and the results revealed that coolant was the prevailing factor on the surface roughness followed by tool type, feed and speed. In addition, the fuzzy predicted values and experimental values of surface roughness are fairly close to each other. Therefore, the developed fuzzy logic model can be effectively used to predict the surface roughness in drilling of EN24 Steel.Keywords
Drilling, Surface Roughness, Taguchi, ANOVA, Fuzzy Logic Modeling Technique, EN24 Steel.Full Text
- Evaluation of Aluminium Hybrid Metal Matrix Composites by Analytical Hierarchy Process (AHP) Method
Abstract Views :192 |
PDF Views:1
Authors
Affiliations
1 Department of Mechanical Engineering, Sri Venkateswara University College of Engineering, Tirupati, IN
1 Department of Mechanical Engineering, Sri Venkateswara University College of Engineering, Tirupati, IN
Source
Manufacturing Technology Today, Vol 17, No 2 (2018), Pagination: 3-14Abstract
Selection of most appropriate matrix materials plays a pivotal role in the fabrication of aluminium based hybrid metal matrix composites. In order to satisfy the demands offered by engineering fraternity, aluminium based hybrid metal matrix composites (AHMMCs) has become a most promising material with superior mechanical properties, low density, good corrosion resistance and tribological properties. This paper mainly focused on an evaluation of a most suitable matrix material for fabrication of AHMMCs using an Analytical Hierarchy Process (AHP). In this research, selection of a suitable matrix material from AA 6XXX series has been investigated by considering the five criteria such as Density, Tensile strength, Hardness, Melting Point and Cost of available matrix materials in the market. Finally, the result shows that AA 6082 aluminium alloy is the optimum matrix materials for the production of AHMMCs.Keywords
Material Selection, Analytic Hierarchy Process, Alternatives, Criteria, Multi-Criteria Decision-Making.- Multi Objective Optimization of Process Parameters in Drilling of AL 6061-T6 and Brass C360 Alloys by WASPAS Method
Abstract Views :226 |
PDF Views:2
Authors
Affiliations
1 Department of Mechanical Engineering, S.V. University, Tirupati, IN
1 Department of Mechanical Engineering, S.V. University, Tirupati, IN
Source
Manufacturing Technology Today, Vol 17, No 12 (2018), Pagination: 3-11Abstract
In the present work, the drilling experiments are performed on Aluminum 6061-T6 and Brass C360 alloy block of 8mm thickness using HSS Twist drills by means of universal drilling machine. Cutting parameters drill diameter, speed and feed rate are varied at 3 different levels. A number of drilling experiments are conducted using the L9 orthogonal array according to Taguchi design of experiment (DOE) on both materials separately. The output performances viz. MRR, surface roughness, torque and cutting forces are recorded for each run. Multi objective optimization technique WASPAS (weighted aggregated sum product assessment) method is used for determining the optimal drilling parameters resulting in minimum Surface roughness, Torque, cutting force and Maximum MRR. The measured responses were analyzed and the Influence of drill parameters on output responses such as metal removal rate and surface roughness, cutting force, torque is studied. After nine experimental trials, responses are compared for Al 6061-T6 and Brass C360 alloys.Keywords
Drilling, Taguchi Design of Experiment (DOE), AL 6061-T6 and Brass C360 Alloys, WASPAS Method.References
- A. Prabukarth, V. Krishnaraj, M. Senthilkumar - multi-objective optimization on drilling of titanium alloy, Materials Science Forum vol. 763, 2013, 29-49.
- M.A. Amran, S. Salmaha, R. Izamshahb, M. Hadzleyb, Sivaraosb -“Effects of machine parameters on surface roughness using response surface method in drilling process”, The Malaysian International Tribology Conference 2013, Procedia Engineering 68, 2013, 24 – 29.
- Nisha Tamta, R S Jadoun - Parametric Optimization of Drilling Machining Process for Surface Roughness on Aluminium Alloy 6082 Using Taguchi Method, SSRG International Journal of Mechanical Engineering (SSRGIJME), vol. 2, no. 7, July 2015.
- B.Shivapragash ,K.Chandrasekaran , C . Parthasarathy and M.Samuel-“Multiple Response Optimizations in Drilling Using Taguchi and Grey Relational Analysis”. International Journal of Modern Engineering Research (IJMER), vol. 3, no. 2, March-April. 2013, 765-768.
- Madic, M.Gecevska, V.Radovanovic, M. Petkovic - Multi criteria economic analysis of machining processes using the waspas method, 'Journal Of Production Engineering', vol. 17, No. 2.
- Hari Singh, Abhishek Kamboj, Sudhir Kumar: Multi Response Optimization in Drilling Al6063/SiC/15% Metal Matrix Composite,'International Journal of Mechanical and Mechatronics Engineering', vol. 8, no. 4, 2014
- A Comparative Study in Heat-Assisted Machining of Inconel 718 and Hastelloy-276 using Machine Learning Techniques
Abstract Views :321 |
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Authors
Affiliations
1 SVU College of Engineering, Tirupati, Andhra Pradesh, IN
1 SVU College of Engineering, Tirupati, Andhra Pradesh, IN