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Evaluation of Water Consumption and Neuro-Fuzzy Model of the Detergent Leavings Kinetics’ Removal in a Clean in Place System

  • Rodrigo Sislian
  • Valdir M. Júnior
  • Leo Kunigk
  • Sérgio R. Augusto
  • Ricardo A. Malagoni
  • Ubirajara C. Filho
  • Rubens Gedraite
Conference paper

Abstract

This work has focused on describing the water consumption and the Neuro-Fuzzy model of the detergent leavings kinetics’ removal of a CIP System, based on the pH measured. The plant dynamics has been identified for different operational conditions. A flowrate value of 10.5 L.min−1 has been proved to be effective in order to provide the minimum required rinse water volume to execute the stage of the CIP system, which means that it is possible to optimize the process reducing energy, water and steam consumption as well as the time of unused machinery bringing productivity gains. The obtained models, allowed the prediction of the system dynamics behavior. The results were validated when compared with the experimental data. Three triangular membership functions for the input data modeled accordingly the pH dynamics with an error of 0.011 when comparing the validation data and the obtained model.

Keywords

CIP system Kinetics’ removal Modeling Neuro-fuzzy Optimization Productivity gains 

Notes

Acknowledgment

The authors acknowledge the financial support provided by Fapemig (Fundação de Amparo a Pesquisa do Estado de Minas Gerais) research fund and by Mauá Institute of Technology.

References

  1. 1.
    M.R. Bird, M. Barlett, CIP optimization for the food industry: Relationships between detergent concentration, temperature and cleaning time. Inst. Chem. Eng. 73c, 63–70 (1995) Google Scholar
  2. 2.
    L. Gormezano, Desenvolvimento e implementação de sistema para avaliar a cinética de remoção de resíduos presentes nos tubos de trocador de calor feixe tubular. M.S. Dissertation, Department of Chemical Engineering, CEUN-IMT, 2007Google Scholar
  3. 3.
    R. Sislian et. al., Neuro-Fuzzy Model of the Detergent Leavings Kinetics’ Removal in a Clean in Place System, in Lecture Notes in Engineering and Computer Science: Proceedings of the World Congress on Engineering and Computer Science, Vol II, WCECS 2013, pp. 617–620, San Francisco, 23–25 Oct 2013Google Scholar
  4. 4.
    S. Jun, V.M. Puri, A 2D dynamic model for fouling performance of plate heat exchangers. J. Food Eng. 75, 364–374 (2006)CrossRefGoogle Scholar
  5. 5.
    T.J.M. Jeurnink, D.W. Brinkman, The cleaning of heat exchangers and evaporators after processing milk or whey. Intern. Dairy J. 4, 347–368 (1994)CrossRefGoogle Scholar
  6. 6.
    P. Jong, Impact and control of fouling in milk processing. Trends Food Sci. Tech. 8, 401–405 (1997)CrossRefGoogle Scholar
  7. 7.
    R. Sislian, Estudo de Sistema de Limpeza CIP Usando Identificação de Sistemas, M.S. Dissertation, Department of Chemical Engineering, Unicamp, Mestrado 2012Google Scholar
  8. 8.
    J.S. Jang, ANFIS: Adaptive-Network-based Fuzzy Inference Systems. IEEE Trans. Syst. Man Cybern. 23(3), 665–685 (1993)CrossRefGoogle Scholar
  9. 9.
    L.C. Benini, M.M. Junior, Modelagem Neuro-Fuzzy com apoio do Matlab. Support Material, Presidente Prudente 2008Google Scholar
  10. 10.
    V. Melero Jr., Instrumentação e Identificação de um Processo de Sanitização Cinética CIP, M.S. Dissertation, Department of Chemical Engineering, CEUN-IMT 2011Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Rodrigo Sislian
    • 1
  • Valdir M. Júnior
    • 2
  • Leo Kunigk
    • 2
  • Sérgio R. Augusto
    • 2
  • Ricardo A. Malagoni
    • 3
  • Ubirajara C. Filho
    • 3
  • Rubens Gedraite
    • 3
  1. 1.São PauloBrazil
  2. 2.São Caetano do SulBrazil
  3. 3.UberlândiaBrazil

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