Abstract
This work deals with the problem of modelling operations management using fuzzy logic techniques. Our study focuses on the problem of production planning under uncertainty. Two types of uncertainties are considered: one is related to the quantity or composition of the raw materials used in production; the other involves disturbances to the production process. These situations could lead to difficulties meeting the demand. Production operations must be adapted dynamically to the existing conditions to cope with these uncertainties. A method based on fuzzy logic is proposed to model the dynamic behaviour of operations management so that decisions can be made to meet the production objectives. As an application, the case of an industrial laundry is studied. The solution proposed uses the information provided by an expert to model the behaviour of the management system. Mamdani-type fuzzy inference systems are used in the model. Simulated results demonstrate the potential of fuzzy logic as a tool for improving decisions in operations management.
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Acknowledgements
The authors gratefully acknowledge the funding granted to this researchby Fundación Cajacanarias (GreenTourist Project). Jose Manuel Gonzalez-Cava’s research was support by the Spanish Ministry of Education, Culture and Sport (www.mecd.gob.es) under the “Formación de Profesorado Universitario” grant FPU15/03347.
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González Rodríguez, G.C., Méndez, J.A., Batista, B.M., Gonzalez-Cava, J.M. (2018). A Fuzzy Modelling Approach to Laundry Industry. In: Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K., Krawczak, M. (eds) Advances in Fuzzy Logic and Technology 2017. EUSFLAT IWIFSGN 2017 2017. Advances in Intelligent Systems and Computing, vol 642. Springer, Cham. https://doi.org/10.1007/978-3-319-66824-6_14
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DOI: https://doi.org/10.1007/978-3-319-66824-6_14
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