COMPLIANCE MODELING AND INTELLIGENT OPTIMIZATION OF KERF DURING WEDM OF AL7075/SiCP METAL MATRIX COMPOSITE
Keywords:
Al7075/SiCP MMCs, kerf, WEDM , OptimizationAbstract
This investigation presents the formulation of the kerf (width of the slit) and the optimal control parameter settings of wire electrochemical discharge machining (WEDM) for machining Al7075/SiCP MMCs. WEDM has proven its economical efficiency and effectiveness in cutting the hard ceramic reinforced MMCs. Kerf is an important performance characteristic which determines the dimensional accuracy of the machined component while producing high precision components. Lack of availability of machinability information for advanced MMCs necessitates more experimental trials in manufacturing industry. Therefore, extensive experimental investigations are essential to predict kerf. This work is aimed to investigate the significance of particulate size, volume fraction of SiCP, pulse-on time, pulse-off time and wire tension on the kerf. A response surface model was developed to predict and analyze the relative significance of the control variables on kerf and was confirmed for its adequacy by several statistical tests. A powerful artificial intelligence called genetic algorithms (GA) was then used to determine the best combination of the control variable settings. In the next step the derived optimal settings were confirmed by experimental validation. The results obtained in this work state that, the derived optimized parameters are capable of machining the Al7075/SiCP MMCs more efficiently and with better dimensional accuracy.
Downloads
References
M. Rosso, Ceramic and metal matrix composites: Routes and properties, Journal of Materials Processing Technology 175 (2006) 364–375
A. Manna Æ B. Bhattacharyya, Investigation for optimal parametric combination for achieving better surface finish during turning of Al /SiC-MMC, Int J Adv Manuf Technol (2004) 23: 658–665.
Harlal Singh Mali, Alakesh Manna, Simulation of surface generated during abrasive flow finishing of Al/SiC p -MMC using neural networks, Int J Adv Manuf Technol (2012) 61:1263 – 1268.
Ho KH, Newman ST, Rahimifard S, Allen RD (2004) State of the art in wire electrical discharge machining (WEDM). Int J Mach Tools Manuf 44:1247 – 1259.
C. Satishkumar, M. Kanthababu, V. Vajjiravelu, R. Anburaj, N. Thirumalai Sundarrajan, H. Arul, Investigation of wire electrical discharge machining characteristics of Al6063/SiC p composites, Int J Adv Manuf Technol (2011) 56:975 – 986.
Guo ZN, Wang X, Huang ZG, Yue TM (2002) Experimental investigation into shaping particles-reinforce material by WEDM HS. J Mater Process Technol 129:56 – 59.
Yan BH, Tsai HC (2005) Examination of wire electrical discharge machining of Al2O3/6061Al composites. Int J Mach Tools Manuf 45(3):251 – 259.
Aniza Alias, Bulan Abdullah, Norliana Mohd Abbas, Influence of machine feed rate in wedm of titanium Ti-6Al-4V with constant current (6a) using brass wire, Procedia Engineering, 41, ( 2012 ), 1806 – 1811.
Kodalagara Puttanarasaiah Somashekhar & Nottath Ramachandran & Jose Mathew, Material removal characteristics of microslot (kerf) geometry in μ-WEDM on aluminium Int J Adv Manuf Technololgy, 2010, 51:611–626.
Sangju Lee, Michael A. Scarpulla, Eberhard Bamberg, Effect of metal coating on machinability of high purity germanium using wire electrical discharge machining, Journal of Materials Processing Technology 213 (2013) 811–817
Nihat Tosun, Can Cogun and Gul Tosun, 2004, A study on kerf and material removal rate in wire electrical discharge machining based on Taguchi method, Journal of Materials Processing Technology – Journal of material processing and technology, vol. 152, no. 3, pp. 316-322, 2004.
K. Palanikumar, R. Karthikeyan, Optimal machining conditions for turning of particulate metal matrix composites using Taguchi and response surface methodologies, Machining Science and Technology: An International Journal, 10:417–433.
Montgomery, D. C., “Design and analysis of experiments”, 5th edition, John Wiley & Sons, INC, New York, 2003.
Chen CJ, Tseng CS (1996) The path and location planning of workpiece by genetic algorithms. J Intell Manuf 7:69
Dereli T, Filiz IH, Baykasoglu A (2001) Optimizing cutting parameters in process planning of prismatic parts using genetic algorithms. Int J Prod Res 39:3303
P. Palanisamy, I. Rajendran, S. Shanmugasundaram, Optimization of machining parameters using genetic algorithm and experimental validation for end-milling operations, International Journal of Advanced Manufacturing Technology, 32: (2007) 644 – 655.
Kalyanmoy Deb, Optimization for engineering design : Algorithms and Examples, PHI Learning Limited, New Delhi, 2010.
Deb, K., “Multi objective optimization using evolutionary algorithms”, John Wiley & Sons (ASIA) Pte. Ltd., Singapore, 2001.
