Risk Assessment of Maintenance activities using Fuzzy Logic

Gallab, Maryam; Bouloiz, Hafida; Alaoui, Youssef El; Tkiouat, Mohamed

doi:10.1016/j.procs.2019.01.065

Cited by 61 publications

(41 citation statements)

References 17 publications

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“…Fuzzy logic has been used to analyze occupational health and safety [9][10][11], for risk assessments of various equipment failures [12], for a pipeline risk assessment [13], for a deepwater drilling riser [14], and in mining equipment [15]. It has also been used in Risk Based Maintenance (RBM) [16][17][18].…”

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confidence: 99%

Fuzzy Model for Risk Assessment of Machinery Failures

et al. 2020

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The main goal of this research was the development of an algorithm for the implementation of negative risk parameters in a synthesis model for a risk level assessment for a specific machine used in the mining industry. Fuzzy sets and fuzzy logic theory, in combination with statistical methods, were applied to analyze the time picture state of the observed machine. Fuzzy logic is presented through fuzzy proposition and a fuzzy composition module. Using these tools, the symmetric position of the fuzzy sets with regard to class was used, and the symmetric fuzzy inference approach was used in an outcome calculation. The main benefit of the proposed model is being able to use numerical and linguistic data in a risk assessment model. The proposed risk assessment model, using fuzzy logic conclusions and min–max composition, was used on a mobile crushing machine. The results indicated that the risk level of the mobile crushing machine was in the “high” category, which means that it is necessary to introduce maintenance policies based on this high risk. The proposed risk assessment model is useful for any engineering system.

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confidence: 99%

Fuzzy Model for Risk Assessment of Machinery Failures

et al. 2020

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“…As stated by Gallab et al [11], fuzzy logic is based on the theory of fuzzy sets developed by Zadeh [14], and is a generalization of the classical set theory. This technique provides flexibility for reasoning and considers inaccuracy, subjectivity, uncertainty, imprecision.…”

Section: Fuzzy Logic Algorithmmentioning

confidence: 99%

“…It also provides wide opportunities for working with imprecise linguistic data by defining rules and membership functions in sets called "fuzzy sets" [15]. Gallab et al [11] also state that the fuzzy sets theory is applicable when assessing indicators for which there is no conventional model for estimating and measuring, or if the model is too complex. This theory, presented by Zadeh [16,17], is the most suitable formalism to qualitatively describe linguistic variables.…”

Section: Fuzzy Logic Algorithmmentioning

confidence: 99%

“…The proposed fuzzy decision support system follows the methods presented by Erozan [10] to manage the maintenance activities of critical components in manufacturing systems, and those by Gallab et al [11] to quantify the risks associated with maintenance activities, by coupling the risk analysis method with fuzzy logic. This branch of artificial intelligence allows the transfer of knowledge generated in the experiments, to a decision system that clearly defines the correct selection parameters necessary to obtain greater efficiency in the results, toward their application in the treatment of resistant effluents.…”

Section: Introductionmentioning

confidence: 99%

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Hydrogen Peroxide Production in an Electrochemical Flow-by Reactor using Gas Diffusion Electrodes Modified with Organic Redox Catalysts

Forti¹,

Matulovic²,

Neto³

et al. 2020

Int J Innov Educ Res

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This paper presents a proposal to use an electrochemical flow-by reactor for hydrogen peroxide electrogeneration using cathodes formed from the incorporation of organic redox catalysts (2-ethylanthraquinone, 2-tert-butylanthraquinone, alizarin, and azobenzene) in the structure of gas diffusion electrodes. These electrodes help circumvent the low solubility of oxygen in aqueous solutions. Organic redox catalysts, which typically contain quinone or azo groups in their structure, were added to the electrode mass in a 10% proportion. The electrodes were used to study the electrogeneration of hydrogen peroxide in situ, in an acid medium (0.1 mol L-1 H2SO4 and 0.1 mol L-1 K2SO4, pH 1), inside an electrochemical flow-by reactor. Comparative analysis among the different catalysts indicated that the best electrode for hydrogen peroxide electrogeneration was the gas diffusion electrode modified with 10% of 2-ethylanthraquinone. With an underflow rate of 200 L h-1, hydrogen peroxide was formed with a maximum yield of 998.12 mg L-1 after 2 h at -2.0 V vs Pt//Ag/AgCl, for which the energy consumption was 11.21 kWh kg-1. The use of the electrochemical flow-by reactor was much more efficient, in that it yielded higher concentrations of hydrogen peroxide with extremely low energy consumption, compared to that obtained when using an electrochemical cell. In addition, for ensuring appropriate usage of the electrodes, optimizing their potential for the maximum generation of hydrogen peroxide, and obtaining the highest efficiency for the reduction of oxygen, a fuzzy algorithm was developed to help support the user’s decision.

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“…The different measures of each attribute are combined using a weighting scheme so fuzzy clustering analysis of multi-attribute data can be performed. In the absence of a quantitative probability model, fuzzy logic considering field data and expert opinions was proposed by Maryam Gallab [33] and K. Antosz [34], and the classification and evaluation of key risks could be completed. A new type of multicriteria decision making (MCDM) was proposed by Soumava Boral [35], that is, the fuzzy analytic hierarchy process (FAHP) and improved fuzzy multi-attribute ideal comparative analysis (FMAIRCA) were combined to improve the robustness of fault evaluation.…”

Section: Introductionmentioning

confidence: 99%

Preventive Maintenance Strategy for Train Doors Based on the Competitive Weibull Theory

he¹,

Zhang²,

Yan-jun³

et al. 2020

Preprint

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In view of the problems of over-maintenance and under-maintenance in the current urban rail transit maintenance strategy and the reliability of single processing of fault data, which is often inconsistent with the actual situation, an incomplete preventive maintenance strategy based on the competitive Weibull model is proposed in this paper. To make the fault mechanism processing method for urban rail vehicles more accurate, fault feature attributes and fault information sequences are introduced to classify fault data. Fuzzy cluster analysis of vehicle fault data can be performed using the formula of the competitive Weibull model, and parameter estimation of the reliability model can be performed by combining it with the graph parameter estimation method. In addition, the fault rate increase factor and service age reduction factor are introduced into the maintenance strategy, and the optimal preventive maintenance cycle and maintenance times are obtained by combining maintenance and replacement according to reliability. A quantum-genetic intelligent algorithm is used to optimize the model-solving process. Finally, the maintenance of urban rail transit train doors is taken as an example. The results of this study show that compared with the traditional maintenance strategy, the reliability of the proposed maintenance strategy is closer to the actual situation. At the same time, the proposed maintenance strategy can effectively reduce the number of parked vehicles, reduce maintenance costs, and ensure the safety of train operation, maintenance economy and performance of tasks.

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Risk Assessment of Maintenance activities using Fuzzy Logic

Cited by 61 publications

References 17 publications

Fuzzy Model for Risk Assessment of Machinery Failures

Fuzzy Model for Risk Assessment of Machinery Failures

Hydrogen Peroxide Production in an Electrochemical Flow-by Reactor using Gas Diffusion Electrodes Modified with Organic Redox Catalysts

Preventive Maintenance Strategy for Train Doors Based on the Competitive Weibull Theory

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