How to cite this paper
N., S., Tirumala, D., Gajjela, R & Das, R. (2018). ANN and RSM approach for modelling and multi objective optimization of abrasive water jet machining process.Decision Science Letters , 7(4), 535-548.
Refrences
Assarzadeh, S., Ghoreishi, M., & Shariyyat, M. (2010). Response surface methodology approach to process modeling and optimization of powder mixed electrical discharge machining (PMEDM). In Proceedings of the 16th International Symposium on Electromachining (ISEM-XVI) April (pp. 19-23).
Azmir, M. A., & Ahsan, A. K. (2009). A study of abrasive water jet machining process on glass/epoxy composite laminate. Journal of Materials Processing Technology, 209(20), 6168-6173.
Borkowski, P. (2004). Theoretical and experimental basis of hydro-jet surface treatment. Publ. Koszalin University of Technology.
Box, G. E., & Draper, N. R. (2007). Response surfaces, mixtures, and ridge analyses (Vol. 649). John Wiley & Sons.
Fenggang, L., Geskin, E. S., & Tismenetskiy, L. (1996). Feasibility study of abrasive waterjet polishing. 13th Int. In Conf. on Jetting Technology. Sardinia(pp. 709-723).
Folkes, J. (2009). Waterjet—An innovative tool for manufacturing. Journal of Materials Processing Technology, 209(20), 6181-6189.
Hashish, M. (1987). Turning With Abrasive-Waterjets--a First Investigation. J. Eng. Ind.(Trans. ASME), 109(4), 281-290.
Hashish, M. (1989). An investigation of milling with abrasive-waterjets. ASME J. Eng. Ind, 111(2), 158-166.
Ibraheem, H. M. A., Iqbal, A., & Hashemipour, M. (2015). Numerical optimization of hole making in GFRP composite using abrasive water jet machining process. Journal of the Chinese Institute of Engineers, 38(1), 66-76.
Jegaraj, J. J. R., & Babu, N. R. (2007). A soft computing approach for controlling the quality of cut with abrasive waterjet cutting system experiencing orifice and focusing tube wear. Journal of Materials Processing Technology, 185(1), 217-227.
Khan, A. A., & Haque, M. M. (2007). Performance of different abrasive materials during abrasive water jet machining of glass. Journal of materials processing technology, 191(1), 404-407.
Lemma, E., Chen, L., Siores, E., & Wang, J. (2002). Optimising the AWJ cutting process of ductile materials using nozzle oscillation technique. International Journal of Machine Tools and Manufacture, 42(7), 781-789.
Liu, D., Huang, C., Wang, J., Zhu, H., Yao, P., & Liu, Z. (2014). Modeling and optimization of operating parameters for abrasive waterjet turning alumina ceramics using response surface methodology combined with Box–Behnken design. Ceramics International, 40(6), 7899-7908.
Lu, Y., Li, X., Jiao, B., & Liao, Y. (2005). Application of artificial neural networks in abrasive waterjet cutting process. Advances in Neural Networks–ISNN 2005, 982-982.
Mishra, P. K. (2002). Non-conventional machining processes. Published by NK Mehra (Naroja publishing house), 3.
Momber, A. W., & Kovacevic, R. (1997). Test parameter analysis in abrasive water jet cutting of rocklike materials. International Journal of Rock Mechanics and Mining Sciences, 34(1), 17-25.
Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response surface methodology: process and product optimization using designed experiments. John Wiley & Sons.
Nagdeve, L., Chaturvedi, V., & Vimal, J. (2012). Implementation of Taguchi approach for optimization of abrasive water jet machining process parameters. International Journal of Instrumentation, Control and Automation, 1(3), 4.
Patel, S. R., & Shaikh, A. A. (2013). Control and measurement of abrasive flow rate in an Abrasive Waterjet Machine. International journal of innovative Research in Science, Engineering and Technology, ISSN, 2319-8753.
Ramprasad, U. G., & Kamal, H. (2015). Optimization MRR of Stainless steel 403 in abrasive water jet machining using ANOVA and Taguchi method. International Journal of Engineering Research and Applications, 5(5), 86-91.
Shanmugam, D. K., & Masood, S. H. (2009). An investigation on kerf characteristics in abrasive waterjet cutting of layered composites. Journal of materials processing technology, 209(8), 3887-3893.
Shanmugam, D. K., Wang, J., & Liu, H. (2008). Minimisation of kerf tapers in abrasive waterjet machining of alumina ceramics using a compensation technique. International Journal of Machine Tools and Manufacture, 48(14), 1527-1534.
Srinivasu, D. S., & Babu, N. R. (2008). A neuro-genetic approach for selection of process parameters in abrasive waterjet cutting considering variation in diameter of focusing nozzle. Applied Soft Computing, 8(1), 809-819.
Srinivasu, D. S., Babu, N. R., Srinivasa, Y. G., Louis, H., Peter, D., & Versemann, R. (2005, August). Genetically evolved artificial neural networks built with sparse data for predicting depth of cut in abrasive water jet cutting. In Proceedings American Water Jet Conference. Houston, Texas (pp. 1-16).
Vundavilli, P. R., Parappagoudar, M. B., Kodali, S. P., & Benguluri, S. (2012). Fuzzy logic-based expert system for prediction of depth of cut in abrasive water jet machining process. Knowledge-Based Systems, 27, 456-464.
Yong, Z., & Kovacevic, R. (1997). Modeling of jetflow drilling with consideration of the chaotic erosion histories of particles. Wear, 209(1-2), 284-291.
Zhao, C. Y., Gong, H., Fang, F. Z., & Li, Z. J. (2013). Experimental study on the cutting force difference between rotary ultrasonic machining and conventional diamond grinding of K9 glass. Machining Science and Technology, 17(1), 129-144.
Azmir, M. A., & Ahsan, A. K. (2009). A study of abrasive water jet machining process on glass/epoxy composite laminate. Journal of Materials Processing Technology, 209(20), 6168-6173.
Borkowski, P. (2004). Theoretical and experimental basis of hydro-jet surface treatment. Publ. Koszalin University of Technology.
Box, G. E., & Draper, N. R. (2007). Response surfaces, mixtures, and ridge analyses (Vol. 649). John Wiley & Sons.
Fenggang, L., Geskin, E. S., & Tismenetskiy, L. (1996). Feasibility study of abrasive waterjet polishing. 13th Int. In Conf. on Jetting Technology. Sardinia(pp. 709-723).
Folkes, J. (2009). Waterjet—An innovative tool for manufacturing. Journal of Materials Processing Technology, 209(20), 6181-6189.
Hashish, M. (1987). Turning With Abrasive-Waterjets--a First Investigation. J. Eng. Ind.(Trans. ASME), 109(4), 281-290.
Hashish, M. (1989). An investigation of milling with abrasive-waterjets. ASME J. Eng. Ind, 111(2), 158-166.
Ibraheem, H. M. A., Iqbal, A., & Hashemipour, M. (2015). Numerical optimization of hole making in GFRP composite using abrasive water jet machining process. Journal of the Chinese Institute of Engineers, 38(1), 66-76.
Jegaraj, J. J. R., & Babu, N. R. (2007). A soft computing approach for controlling the quality of cut with abrasive waterjet cutting system experiencing orifice and focusing tube wear. Journal of Materials Processing Technology, 185(1), 217-227.
Khan, A. A., & Haque, M. M. (2007). Performance of different abrasive materials during abrasive water jet machining of glass. Journal of materials processing technology, 191(1), 404-407.
Lemma, E., Chen, L., Siores, E., & Wang, J. (2002). Optimising the AWJ cutting process of ductile materials using nozzle oscillation technique. International Journal of Machine Tools and Manufacture, 42(7), 781-789.
Liu, D., Huang, C., Wang, J., Zhu, H., Yao, P., & Liu, Z. (2014). Modeling and optimization of operating parameters for abrasive waterjet turning alumina ceramics using response surface methodology combined with Box–Behnken design. Ceramics International, 40(6), 7899-7908.
Lu, Y., Li, X., Jiao, B., & Liao, Y. (2005). Application of artificial neural networks in abrasive waterjet cutting process. Advances in Neural Networks–ISNN 2005, 982-982.
Mishra, P. K. (2002). Non-conventional machining processes. Published by NK Mehra (Naroja publishing house), 3.
Momber, A. W., & Kovacevic, R. (1997). Test parameter analysis in abrasive water jet cutting of rocklike materials. International Journal of Rock Mechanics and Mining Sciences, 34(1), 17-25.
Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response surface methodology: process and product optimization using designed experiments. John Wiley & Sons.
Nagdeve, L., Chaturvedi, V., & Vimal, J. (2012). Implementation of Taguchi approach for optimization of abrasive water jet machining process parameters. International Journal of Instrumentation, Control and Automation, 1(3), 4.
Patel, S. R., & Shaikh, A. A. (2013). Control and measurement of abrasive flow rate in an Abrasive Waterjet Machine. International journal of innovative Research in Science, Engineering and Technology, ISSN, 2319-8753.
Ramprasad, U. G., & Kamal, H. (2015). Optimization MRR of Stainless steel 403 in abrasive water jet machining using ANOVA and Taguchi method. International Journal of Engineering Research and Applications, 5(5), 86-91.
Shanmugam, D. K., & Masood, S. H. (2009). An investigation on kerf characteristics in abrasive waterjet cutting of layered composites. Journal of materials processing technology, 209(8), 3887-3893.
Shanmugam, D. K., Wang, J., & Liu, H. (2008). Minimisation of kerf tapers in abrasive waterjet machining of alumina ceramics using a compensation technique. International Journal of Machine Tools and Manufacture, 48(14), 1527-1534.
Srinivasu, D. S., & Babu, N. R. (2008). A neuro-genetic approach for selection of process parameters in abrasive waterjet cutting considering variation in diameter of focusing nozzle. Applied Soft Computing, 8(1), 809-819.
Srinivasu, D. S., Babu, N. R., Srinivasa, Y. G., Louis, H., Peter, D., & Versemann, R. (2005, August). Genetically evolved artificial neural networks built with sparse data for predicting depth of cut in abrasive water jet cutting. In Proceedings American Water Jet Conference. Houston, Texas (pp. 1-16).
Vundavilli, P. R., Parappagoudar, M. B., Kodali, S. P., & Benguluri, S. (2012). Fuzzy logic-based expert system for prediction of depth of cut in abrasive water jet machining process. Knowledge-Based Systems, 27, 456-464.
Yong, Z., & Kovacevic, R. (1997). Modeling of jetflow drilling with consideration of the chaotic erosion histories of particles. Wear, 209(1-2), 284-291.
Zhao, C. Y., Gong, H., Fang, F. Z., & Li, Z. J. (2013). Experimental study on the cutting force difference between rotary ultrasonic machining and conventional diamond grinding of K9 glass. Machining Science and Technology, 17(1), 129-144.