Modeling and Optimization of Abrasive Waterjet Parameters using Regression Analysis
Authors: Farhad Kolahan, A. Hamid Khajavi
Abstract:
Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.
Keywords: AWJ cutting, Mathematical modeling, Simulated Annealing, Optimization
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1080936
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2159References:
[1] U. Çaydaş, A. Hasçalik, "A study on surface roughness in abrasive waterjet machining process using artificial neural networks and regression analysis method", J. Mater. Process. Techno., vol. 2 0 2, pp. 574 -582, 2008.
[2] M.A. Azmir, A.K. Ahsan, "Investigation on glass/epoxy composite surfaces machined by abrasive water jet machining", J. Mater. Process. Techno., vol.198, pp.122-128, 2008.
[3] C. Ma, R.T. Deam, "A correlation for predicting the kerf profile from abrasive water jet cutting", Experimental Thermal and Fluid Science, vol.30, pp.337-343, 2006.
[4] J. John Rozario Jegaraj, N. Ramesh Babu, "A soft computing approach for controlling the quality of cut with abrasive waterjet cutting system experiencing orifice and focusing tube wear", J. Mater. Process. Techno., vol.185, no.1-3, pp.217-227, 2007.
[5] M. Hashish, "Optimization factors in abrasive waterjet machining", ASME J. Eng. Ind., vol.113, pp.29-37, 1991.
[6] R. Kovacevic, M. Fang, "Modeling of the influence of the abrasive waterjet cutting parameters on the depth of cut based on fuzzy rules", Int. J. Mach. Tools Manuf., vol. 34, no.1, pp.55-72, 1994.
[7] M. Hashish, "A modeling study of metal cutting with abrasive water jets", Transactions of ASME J. Eng. Mater. Technol., vol.106, no.1, pp.88-100, 1984.
[8] M. Ramulu, D. Arola, "The influence of abrasive waterjet cutting conditions on the surface quality of graphite/epoxy laminates", Int. J. Mach. Tools Manuf., vol.34, no.3, pp.295-313, 1994.
[9] P.S. Chakravarthy, N. Ramesh Babu, "A hybrid approach for selection of optimal process parameters in abrasive water jet cutting", in, Proceedings of the Institution of Mechanical Engineers, Part B: J. Eng. Manuf., vol.214, pp.781-791, 2000.
[10] D.S. Srinivasu, N. Ramesh Babu, "A neuro-genetic approach for selection of process parameters in abrasive water jet cutting considering variation in diameter of focusing nozzle", Appl. Soft Comp., Vol.8, pp.809-819, 2008.
[11] D.C. Montgomery, E.A. Peck, G.G. Vining, Introduction to Linear Regression Analysis. third ed., Wiley, New York, 2003.
[12] Kirkpatrick, S., Gelatt, C. & Vecchi, M. "Optimization by simulated annealing". Science, vol.220, pp.671-680, 1983.