{"title":"Cryogenic Freezing Process Optimization Based On Desirability Function on the Path of Steepest Ascent","authors":"R. Uporn, P. Luangpaiboon","volume":72,"journal":"International Journal of Industrial and Manufacturing Engineering","pagesStart":2808,"pagesEnd":2814,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/1150","abstract":"
This paper presents a comparative study of statistical methods for the multi-response surface optimization of a cryogenic freezing process. Taguchi design and analysis and steepest ascent methods based on the desirability function were conducted to ascertain the influential factors of a cryogenic freezing process and their optimal levels. The more preferable levels of the set point, exhaust fan speed, retention time and flow direction are set at -90oC, 20 Hz, 18 minutes and Counter Current, respectively. The overall desirability level is 0.7044.<\/p>\r\n","references":"[1] Guillermo Garcia-Guerata, Cryogenic Manual, Air Products and\r\nChemical Inc., Rev.0, 2000\r\n[2] I.J. Jeong and K.J. Kim, \"Stochastics and Statistics: An interactive\r\ndesirability function method to multi response optimization,\" European\r\nJournal of operation Research, Vol. 195, 2009, pp. 412-426.\r\n[3] P.B.S. Reddy, K. Nishina and A.S. Babu (1998) Taguchi's methodology\r\nfor multi-response optimisation-a case study in the Indian plastics\r\nindustry. International Journal of Quality & Reliability Management,\r\nVol. 15(6), pp. 646-668. doi:10.1108\/02656719810218194\r\n[4] H.C. Lin, C.T. Su, C.C. Wanga, B.H. Chang and R.C. Juang, \"Parameter\r\noptimisation of continuous sputtering process based on Taguchi\r\nmethods, neural networks, desirability function, and genetic algorithms,\"\r\nExpert Systems with Applications, Vol. 39, 2012, pp. 12918-12925.\r\nhttp:\/\/dx.doi.org\/10.1016\/j.eswa.2012.05.032\r\n[5] P. Luangpaiboon, \"Process Optimisation via Conventional Factorial\r\nDesigns and Simulated Annealing on the Path of Steepest Ascent for a\r\nCSTR\", Proceedings of International Conference in Operations\r\nResearch 2002, Klagenfurt University, AUSTRIA, pp. 329-334.\r\n[6] P. Luangpaiboon, Y. Suwanknam and S. Homrossukon, \"Constrained\r\nResponse Surface Optimisation for Precisely Atomising Spraying\r\nProcess\", IAENG Transactions on Engineering Technologies, Vol. 5,\r\n2010, pp. 286-300. DOI: 10.1063\/1.3510555","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 72, 2012"}