Fuzzy Logic Approach for Assessing Sustainability: Methodology Development for Hollow Fiber Membrane Module

Abstract:

Sustainability has become new evolution of quality and efficiency indicator for product life cycle. It is generally acknowledge that sustainability is a result from balancing the environmental, economical and social aspect. However, each aspects may expand to different type of parameters involved that cross the system boundary; qualitative and quantitative parameters. Fuzzy logic approach will be applied to deal with the data uncertainty for obtaining the sustainability assessment of hollow fiber membrane module. Fuzzy logic operation will formulate the mapping from inputs to an output. Thus, it will able for intermediate assessment between sustainable and non-sustainable hollow fiber membrane module. Hence, this paper introduces the comprehensive method for assessing sustainability as guide for hollow fiber membrane designer and manufacturer for future sustainability improvement.

• Periodical: Advanced Materials Research (Volume 845)
• Pages: 579-583
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.845.579
• Online since: December 2013
• Authors: Salwa Mahmood, Abdul Rahman Hemdi, Muhamad Zameri Mat Saman*, Mohd Yusof Noordin
• Keywords: Fuzzy Logic Approach, Hollow Fiber Membrane Module, Sustainability Assessment

References

[1] Y. A Phillis, L.A. Andriantiatsaholiniaina, Sustainability: an ill-defined concept and its assessment using fuzzy logic, Ecological Economics, 37(2001) 435-456.

DOI: 10.1016/s0921-8009(00)00290-1

[2] S.B. Jalil, Development of nanofiltration polyethersulfone hollow fiber membrane for cyclo Dextrin Glycosyltransferase (GGTase) separation, MEng Thesis. Universiti Teknologi Malaysia. (2004).

[3] T. Melin, B. Jefferson, D. Bixio, C. Thoeye, W. De Wilde, J. De Koning, J., Membrane bioreactor technology for wastewater treatment and reuse, Desalination, 187(2006) 271-282.

DOI: 10.1016/j.desal.2005.04.086

[4] S. Mahmood, M.Z.M. Saman, N.M. Yusof, Life cycle assessment of membrane system for wastewater treatment: a review and further research, Applied Mechanics and Material, 315(2013) 186-191.

DOI: 10.4028/www.scientific.net/amm.315.186

[5] H.A.O. Ying, G. Chen, Necessary conditions for some typical fuzzy systems as universal approximators, Automatica, 33(1997) 1333-1338.

DOI: 10.1016/s0005-1098(97)00026-5

[6] A.R. Hemdi, M.Z.M. Saman, S. Sharif, Sustainability evaluation using fuzzy inference methods, International Journal of Sustainable Energy, 2011, 1-17.

DOI: 10.1080/14786451.2011.605947

[7] L.A. Zadeh, A theory of approximate reasoning. In: J. Hayes, D. Michie, L. Mikulich (Eds), Machine Intelligence, Halstead, New York, 9(1979) 149-194.

[8] H.J. Zimmerman, Fuzzy set theory and its application. Kluwer, Boston p.339. (1991).

[9] A.M.G. Cornelissen, J. van den Berg, W.J. Koops, M. Grossman, H.H.J. Udo, Assessment of the contribution of sustainability indicators to sustainable development: a novel approach using fuzzy set theory, Agriculture, Ecosystems & amp; Environment, 86(2001).

DOI: 10.1016/s0167-8809(00)00272-3

[10] T. Rajaram, A. Das, Modeling of interactions among sustainability components of an agro-ecosystem using local knowledge through cognitive mapping and fuzzy inference system. Expert Systems with Application, 37 (2010) 1734-1744.

DOI: 10.1016/j.eswa.2009.07.035

[11] A. Kaufmann, M.M. Gupta, Introduction to fuzzy arithmetic: Theory and application, New York, Van Nostrand Reinhold Company Inc. (1985).