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Hybrid evaluation of the industrial global impact on Mexican aquifers under uncertain criteria evaluations
Flores Casamayor, H. ; Carpitella, Silvia ; Izquierdo, J. ; Mora-Rodríguez, J. ; Delgado-Galván, X.
The present paper proposes an integrated methodological approach to address the problem of managing five aquifers of Guanajuato state, Mexico, according to such relevant criteria as environmental, social, economic and hydrological aspects. The goal of this research consists in formalizing a structured framework to first evaluate the various degrees of importance of criteria and to secondly get a classification of aquifers by minimizing uncertainty of evaluations. To such an aim, the Analytic Hierarchy Process (AHP) is used for calculating the vector of criteria weights, while the Fuzzy Logic (FL) theory supports in deriving quantitative evaluations of aquifers under each selected criterion. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is then proposed to formalize the final ranking of aquifers, something that will be helpful to understand which alternative matches all the differently weighted criteria in the most suitable way at a practical level. In such a way, getting a comprehensive and strategic overview about the problem of interest will be possible.
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Characterizing Uncertainty In Decision-Making Models For Maintenance In Industry 4.0
Ahmed, U. ; Carpitella, Silvia ; Certa, A.
Decision-making involves our daily life at any level, something that entails uncertainty and potential occurrence of risks of varied nature. When dealing with industrial engineering systems, effective decisions are fundamental in terms of maintenance planning and implementation. Specifically, several forms of uncertainty may affect decision-making procedures, for which adopting suitable techniques seems to be a good strategy to attain the main maintenance goals by taking into account system criticality along with decision-maker(s) opinions. A wide variety of factors contributes to uncertainty, being some of them greatly important while other ones less significant. However, all of these factors in synergy can impact the functioning of systems in a positive, neutral, or negative way. In this case, the question is whether obtaining a complete picture of such uncertainty can improve decision-making capabilities and mitigate both through-life costs and unforeseen problems. The fundamental issues include dealing with ambiguity in the maintenance decision-making process by employing numerous evaluation criteria and dealing with real-world scenarios in the maintenance environment. In this study, the Multi-Criteria Decision-Making (MCDM) approach is analysed, with particular reference to the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS), technique capable to effectively rank alternatives while dealing with uncertainty for maintenance decision-making. A final case study is developed to demonstrate the applicability of the method to the field of maintenance in industry 4.0. The proposed study may be useful in supporting intelligent and efficient decisions resulting in favorable maintenance outcomes.
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