Outlining fuzzy decision making in maintenance planning

In any management process, decision making assumes a very important dimension. Complex systems are commonly fed with large amounts of data that are quickly made available to experts and industrial engineers who, in most cases, are not provided with adequate decision support tools. Therefore, the quality of their decisions heavily relies on the quality and experience of them. Indeed, in general, such great availability of data makes the complex systems management planning, particularly in maintenance planning, a very difficult process, by tendentially diverting analysts from the main decisional aspects. Sometimes, unrealistic decisions come out from the process. In order to overcome these difficulties, this study purposes a set of methodological guidelines based on fuzzy theory to be applied in the planning processes, leading to optimized and more realistic results. The applicability of these guidelines is illustrated by a numerical example in the maintenance planning context

Fuzzy maintenance costs of a wind turbine pitch control device

This paper deals with the problem of estimation maintenance costs for the case of the pitch controls system of wind farms turbines. Previous investigations have estimated these costs as (traditional) “crisp” values, simply ignoring the uncertainty nature of data and information available. This paper purposes an extended version of the estimation model by making use of the Fuzzy Set Theory. The results alert decision-makers to consequent uncertainty of the estimations along with their overall level, thus improving the information given to the mainte-nance support system.Fundação para a Ciência e Tecnologia (FCT), Project: FCOMP-01-0124-FEDER-02267

Maintenance decision making

In any management process, decision making assumes a very important dimension. Complex systems are commonly fed with large amounts of data that are quickly made available to experts and industrial engineers who, in most cases, are not provided with adequate decision support tools. Therefore, the quality of their decisions heavily relies on their our quality and experience, making the complex systems management planning, particularly in maintenance planning, a very difficult and subjective process, by tendentially diverting analysts from the main decisional aspects. In order to overcome these difficulties and subjectivities, this paper purposes a set of methodological guidelines based on fuzzy set theory to be applied in the planning processes, leading to optimized and more realistic results

Análise e avaliação de períodos de inspeção em sistemas de natureza tecnológica

Esta tese enquadra-se no domínio da fiabilidade e manutenção de sistemas e centra-se na análise e avaliação de períodos de inspeção em sistemas de natureza tecnológica. O projeto desenvolve um modelo analítico que permite determinar o período ótimo de manutenção e o número ótimo de manutenções preventivas até à substituição do sistema. O modelo tem como base uma política de manutenção preventiva periódica e como objetivo a minimização do custo total de manutenção. Na construção do modelo não são assumidos pressupostos que simplifiquem as expressões analíticas consideradas, não restringindo assim o âmbito da sua aplicação. Além disso, a incerteza de natureza estocástica relacionada com os processos do comportamento (falha, reparação, inspeção, etc.) é modelada por distribuições de probabilidade e a incerteza que se prende com a falta de informação quantitativa, com a escassez de dados, com a falta de conhecimento preciso de alguns parâmetros do modelo é modelada recorrendo à Teoria dos Conjuntos Difusos, o que introduz um acréscimo de realismo ao modelo. O modelo é aplicado a um sistema de controlo de potência ativo de um aerogerador, ilustrando a sua adaptabilidade a sistemas tecnológicos reais e destacando as suas potencialidades e limitações.This thesis is part of the field of systems reliability and maintenance and focuses on the analysis and evaluation of inspection periods of technological nature systems. The project develops an analytical model for determining the optimum period of maintenance and the optimal number of preventive maintenances until the system replacement. The model is based on a periodic preventive maintenance policy and aims to minimize the total cost of maintenance. In the model construction phase no assumptions are made to simplify the analytical expressions, thus not constraint its applicability to real systems. Moreover, the uncertainty of stochastic processes related to behavior (failure, repair, inspection, etc..) is modeled by probability distributions and the uncertainty due to lack of quantitative information, scarcity of data and lack of precise knowledge out some parameters of the model is modeled using the Fuzzy Set Theory, which introduces an increase of realism to the model. The model is applied to an active power control system of a wind turbine, illustrating its adaptability to real technological systems and highlighting its strengths and weaknesses