Generally
fuzzy control system (FCS) is worked in washing machine. For the fuzzy set
theory, membership functions are the building blocks. In a fuzzy set, fuzziness is determined
by its membership functions. The shapes of membership functions are important, because it has an effect
on fuzzy inference system. The shapes of membership functions can be
triangular, trapezoidal and gaussian. The most widely used triangular membership
function is used in this paper, because
it can capture the short time period. In washing machine, open loop control system
is found. This paper applies a fuzzy synthetic evaluation method (FSEM) for
washing cloth in washing machine as FSEM can handle the multiple criteria with
the help of evaluation matrix generated from membership function and weight
matrix generated by Analytical Hierarchy Process (AHP). The purpose of this research is to minimize the wash
time. By applying FSEM, we get
a wash time which is less than that wash time got from applying the Mamdani approach in FCS. An
example is given for illustration. For more reduction of wash time, statistical averaging
method is also used. To reduce the wash time, statistical averaging method can be used in Mamdani
approach also.
References
[1]
Mufozzal, S. and Nuzakkir, S.M. (2017) Application of Creative Design Methodology in Improved Conceptual Design of a Top Load Washing Machine for Better and Gentle Cleaning. International Journal of Engineering Technology, Management and Applied Sciences, 5, 55-61.
[2]
Wang, M. (2018) Research on the Washing Machine Design Improvement of Specific Consumption Groups. MATEC Web of Conferences, 176, Article ID: 01014. https://doi.org/10.1051/matecconf/201817601014
[3]
Laitala, K., Klepp, I.G., Kettlewell, R. and Wiedemann, S. (2020) Laundry Care Regimes: Do the Practices of Keeping Clothes Clean Have Different Environmental Impacts Based on the Fibre Content? Sustainability, 12, Article No. 7537. https://doi.org/10.3390/su12187537
[4]
Pakula, C. and Slamminger, R. (2010) Electricity and Water Consumption for Laundry Washing by Washing Machine Worldwide. Energy Efficiency, 3, 365-382. https://doi.org/10.1007/s12053-009-9072-8
[5]
Onasch, J. (2011) A Feasibility and Cost Comparison of Perchloroethylene Dry Cleaning to Professional Wet Cleaning: Case Study of Silver Hanger Cleaners, Bellingham, Massachusetts. Journal of Cleaner Production, 19, 477-482. https://doi.org/10.1016/j.jclepro.2010.07.015
[6]
Sung-Min Kim, S. (1999) Agitator Mechanism for a Clothes Washing Machine. US Patent No. US005931029A.
[7]
Gooijer, H. and Stamminger, R. (2016) water and Energy Consumption in Domestic Laundering Worldwide—A Review. Tenside Surfactants Detergents, 53, 402-409. https://doi.org/10.3139/113.110456
[8]
Shahmohammadi, S., et al. (2018) Quantifying Drivers of Variability in Life Cycle Greenhouse Gas Emissions of Consumer Products—A Case Study on Laundry Washing in Europe. International Journal of Life Cycle Assesses, 23, 1940-1949. https://doi.org/10.1007/s11367-017-1426-4
[9]
Bain, J., et al. (2009) Reducing the Environmental Impact of Clothes Cleaning: A Research Report Completed for Defra. BIO Intelligence Service in Collaboration with Girah and Intertek, London.
[10]
Laitala, K., et al. (2017) Use Phase of Wool Apparel: A Literature Review for Improving LCA. Proceedings of the Product Lifetimes and the Environment—PLATE 2017, Delft, 8-10 November 2017, 202-207.
[11]
Islam, M.A. and Hossain, M.S. (2021) Optimizing the Wash Time of the Washing Machine Using Several Types of Fuzzy Numbers. Journal of Bangladesh Academy of Sciences, 45, 105-116. https://doi.org/10.3329/jbas.v45i1.54432
[12]
Wang, B., Mo, C., He, C. and Yan, Q. (2017) Fuzzy Synthetic Evaluation of the Long-Term Health of Tunnel Structures. Applied Sciences, 7, Article No. 203. https://doi.org/10.3390/app7020203
[13]
Zang, C.W., Huang, H.W. and Zhang, Z.X. (2004) Forecasting the Strata Condition of a Long Road Tunnel by Using Fuzzy Synthetic Judgment. International Journal of Rock Mechanics and Mining Sciences, 41, 267-272. https://doi.org/10.1016/j.ijrmms.2004.03.052
[14]
Atanasova-Pacemska, T.P., Lapevski, M. and Timovski, R. (2014) Analytical Hierarchical Process (AHP) Method Application in the Process of Selection and Evaluation. International Scientific Conference, Gabrovo, 21-22 November 2014.
[15]
Abihana, O.A. and Gonzalez, O.R. (1993) Design and Implementation of Fuzzy Logic Controllers. Electrical and Computer Engineering Faculty Publication.
[16]
Li, F.C., et al. (2013) Fuzzy Synthetic Evaluation Model Based on the Knowledge System. International Journal of Innovative Computing Information and Control, 9, 4073-4084.
[17]
Saaty, T.L. (1990) How to Make a Decision: The Analytic Hierarchy Process. European Journal of Operation Research, 48, 9-26. https://doi.org/10.1016/0377-2217(90)90057-I
