How to cite this paper
Chakravorty, R., Gauri, S & Chakraborty, S. (2013). Optimization of Multiple Responses of Ultrasonic Machining (USM) Process: A Comparative Study.International Journal of Industrial Engineering Computations , 4(2), 285-296.
Refrences
Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables.Journal of Quality Technology, 12, 214-219.
Dvivedi, A., & Kumar, P. (2007). Surface quality evaluation in ultrasonic drilling through the Taguchi technique.International Journal of Advanced Manufacturing Technology, 34, 131-140.
Gauri, S.K., Chakravorty, R., & Chakraborty, S. (2011). Optimization of correlated multiple responses of ultrasonic machining (USM) process.International Journal of Advanced Manufacturing Technology, 53, 1115-1127.
Hsi, H.M., Tsai, S.P., Wu, M.C., & Tzuang, C.K. (1999). A genetic algorithm for the optimal design of microwave filters.Intentional Journal of Industrial Engineering, 6, 282-288.
Hsieh, K.L., & Tong, L.I. (2001). Optimization of multiple quality responses involving qualitative and quantitative characteristics in IC manufacturing using neural networks.Computers in Industry, 46, 1-12.
Jeyapaul, R., Shahabudeen, P., & Krishnaiah, K. (2005). Simultaneous optimization of multi-response problems in the Taguchi method using genetic algorithm.International Journal of Advanced Manufacturing Technology,30, 870-878.
Jadoun, R.S., Kumar, P. & Mishra, B.K. (2009). Taguchi’s optimization of process parameters for production accuracy in ultrasonic drilling of engineering ceramics.Production Engineering Research and Development, 3, 243-253.
Khuri, A.I. and Conlon, M. (1981) ‘Simultaneous optimization of multiple responses represented by polynomial regression functions’, Technometrics, Vol. 23, pp. 363-375.
Kumar, P., Barua, P.B., & Gaindhar, J.L. (2000). Quality optimization (multi-characteristics) through Taguchi technique and utility concept.Quality and Reliability Engineering International, 16, 475-485.
Kim, K., & Lin, D. (2000). Simultaneous optimization of multiple responses by maximizing exponential desirability functions.Journal of Royal Statistical Society: Series C (Applied Statistics), 43, 311-325.
Kumar, J., & Khamba, J.S. (2008). An experimental study on ultrasonic machining of pure Titanium using designed experiments.Journal of Brazilian Society of Mechanical Science and Engineering, XXX, 231-238.
Kumar, J., Khamba, J.S., & Mohapatra, S.K. (2008). An investigation into the machining characteristics of titanium using ultrasonic machining.International Journal of Machining and Machinability of Materials, 3, 143-161.
Kumar, J., Khamba, J.S., & Mohapatra, S.K. (2009). Investigating and modelling tool-wear rate in the ultrasonic machining of titanium.International Journal of Advanced Manufacturing Technology, 41, 1107-1117.
Kumar, J., & Khamba, J.S. (2010). Modeling the material removal rate in ultrasonic machining of titanium using dimensional analysis.International Journal of Advanced Manufacturing Technology, 48, 103-119.
Montgomery, D.C. (1984).Design and Analysis of Experiments. New York: Wiley.
Phadke, M.S. (1989).Quality Engineering using Robust Design. New Jersey: Prentice Hall, Englewood Cliffs.
Pignatiello, J.R., & Joseph, J. (1993). Strategies for robust multi-response quality engineering.Industrial Engineering Research Division - IIE Transactions, 25, 5-15.
Ramakrishnan, R., & Karunamoorthy, L. (2006). Multi response optimization of wire EDM operations using robust design of experiments.International Journal of Advanced Manufacturing Technology, 29, 105-112.
Rao, R.V., Pawar, P.J., & Davim, J.P. (2010). Parameter optimization of ultrasonic machining process using non-traditional optimization algorithms.Materials and Manufacturing Processes, 25, 1120-1130.
Singh, P.N., Raghukandan, K., & Pai, B.C. (2004). Optimization by grey relational analysis of EDM parameters on machining Al-10%SiCP composites.Journal of Materials Processing Technology, 155-156, 1658-1661.
Singh, R., & Khamba, J.S. (2006). Ultrasonic machining of titanium and its alloys: A review.Journal of Materials Processing Technology, 173, 125-135.
Singh, R., & Khamba, J.S. (2007). Taguchi technique for modelling material removal rate in ultrasonic machining of titanium.Material Science and Engineering, 460-461, 365-369.
Singh, R., & Khamba, J.S. (2009). Mathematical modeling of tool wear in ultrasonic machining of titanium.International Journal of Advanced Manufacturing Technology, 43, 573-580.
Tai, C.Y., Chen, T.S., & Wu, M.C. (1992). An enhanced Taguchi method for optimising SMT processes.Journal of Electronics Manufacturing, 2, 91-100.
Thoe, T.B., Aspinwall, D.K., & Wise, M.L.H. (1998).Review on ultrasonic machining.International Journal of Machine Tools and Manufacture, 38, 239-255.
Tong, L.I., & Hsieh, K.L. (2000). A novel means of applying artificial neural networks to optimize multi-response problem.Quality Engineering, 13, 11–18.
Tsui, K. (1999). Robust design optimization for multiple characteristic problems.International Journal of Production Research,37, 433-445.
Walia, R.S., Shan, H.S., & Kumar, P. (2006). Multi-response optimization of CAFAAFM process through Taguchi method and utility concept.Materials and Manufacturing Processes, 21, 907-914.
Dvivedi, A., & Kumar, P. (2007). Surface quality evaluation in ultrasonic drilling through the Taguchi technique.International Journal of Advanced Manufacturing Technology, 34, 131-140.
Gauri, S.K., Chakravorty, R., & Chakraborty, S. (2011). Optimization of correlated multiple responses of ultrasonic machining (USM) process.International Journal of Advanced Manufacturing Technology, 53, 1115-1127.
Hsi, H.M., Tsai, S.P., Wu, M.C., & Tzuang, C.K. (1999). A genetic algorithm for the optimal design of microwave filters.Intentional Journal of Industrial Engineering, 6, 282-288.
Hsieh, K.L., & Tong, L.I. (2001). Optimization of multiple quality responses involving qualitative and quantitative characteristics in IC manufacturing using neural networks.Computers in Industry, 46, 1-12.
Jeyapaul, R., Shahabudeen, P., & Krishnaiah, K. (2005). Simultaneous optimization of multi-response problems in the Taguchi method using genetic algorithm.International Journal of Advanced Manufacturing Technology,30, 870-878.
Jadoun, R.S., Kumar, P. & Mishra, B.K. (2009). Taguchi’s optimization of process parameters for production accuracy in ultrasonic drilling of engineering ceramics.Production Engineering Research and Development, 3, 243-253.
Khuri, A.I. and Conlon, M. (1981) ‘Simultaneous optimization of multiple responses represented by polynomial regression functions’, Technometrics, Vol. 23, pp. 363-375.
Kumar, P., Barua, P.B., & Gaindhar, J.L. (2000). Quality optimization (multi-characteristics) through Taguchi technique and utility concept.Quality and Reliability Engineering International, 16, 475-485.
Kim, K., & Lin, D. (2000). Simultaneous optimization of multiple responses by maximizing exponential desirability functions.Journal of Royal Statistical Society: Series C (Applied Statistics), 43, 311-325.
Kumar, J., & Khamba, J.S. (2008). An experimental study on ultrasonic machining of pure Titanium using designed experiments.Journal of Brazilian Society of Mechanical Science and Engineering, XXX, 231-238.
Kumar, J., Khamba, J.S., & Mohapatra, S.K. (2008). An investigation into the machining characteristics of titanium using ultrasonic machining.International Journal of Machining and Machinability of Materials, 3, 143-161.
Kumar, J., Khamba, J.S., & Mohapatra, S.K. (2009). Investigating and modelling tool-wear rate in the ultrasonic machining of titanium.International Journal of Advanced Manufacturing Technology, 41, 1107-1117.
Kumar, J., & Khamba, J.S. (2010). Modeling the material removal rate in ultrasonic machining of titanium using dimensional analysis.International Journal of Advanced Manufacturing Technology, 48, 103-119.
Montgomery, D.C. (1984).Design and Analysis of Experiments. New York: Wiley.
Phadke, M.S. (1989).Quality Engineering using Robust Design. New Jersey: Prentice Hall, Englewood Cliffs.
Pignatiello, J.R., & Joseph, J. (1993). Strategies for robust multi-response quality engineering.Industrial Engineering Research Division - IIE Transactions, 25, 5-15.
Ramakrishnan, R., & Karunamoorthy, L. (2006). Multi response optimization of wire EDM operations using robust design of experiments.International Journal of Advanced Manufacturing Technology, 29, 105-112.
Rao, R.V., Pawar, P.J., & Davim, J.P. (2010). Parameter optimization of ultrasonic machining process using non-traditional optimization algorithms.Materials and Manufacturing Processes, 25, 1120-1130.
Singh, P.N., Raghukandan, K., & Pai, B.C. (2004). Optimization by grey relational analysis of EDM parameters on machining Al-10%SiCP composites.Journal of Materials Processing Technology, 155-156, 1658-1661.
Singh, R., & Khamba, J.S. (2006). Ultrasonic machining of titanium and its alloys: A review.Journal of Materials Processing Technology, 173, 125-135.
Singh, R., & Khamba, J.S. (2007). Taguchi technique for modelling material removal rate in ultrasonic machining of titanium.Material Science and Engineering, 460-461, 365-369.
Singh, R., & Khamba, J.S. (2009). Mathematical modeling of tool wear in ultrasonic machining of titanium.International Journal of Advanced Manufacturing Technology, 43, 573-580.
Tai, C.Y., Chen, T.S., & Wu, M.C. (1992). An enhanced Taguchi method for optimising SMT processes.Journal of Electronics Manufacturing, 2, 91-100.
Thoe, T.B., Aspinwall, D.K., & Wise, M.L.H. (1998).Review on ultrasonic machining.International Journal of Machine Tools and Manufacture, 38, 239-255.
Tong, L.I., & Hsieh, K.L. (2000). A novel means of applying artificial neural networks to optimize multi-response problem.Quality Engineering, 13, 11–18.
Tsui, K. (1999). Robust design optimization for multiple characteristic problems.International Journal of Production Research,37, 433-445.
Walia, R.S., Shan, H.S., & Kumar, P. (2006). Multi-response optimization of CAFAAFM process through Taguchi method and utility concept.Materials and Manufacturing Processes, 21, 907-914.