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About

First degree in Mechanical Engineering by FEUP (1982). Master of Science (1984) in Engineering Production and Management and Doctor of Philosophy (1989) in Engineering Production and Management in the scientific area of Quality, Reliability and Maintenance by the University of Birmingham (UK). Assistent Professor of the Faculty of Engineering in the Industrial Engineering and Management Department since 1982. Between the years of 2001 until 2011 I was in an Extraordinary Service Commission in IPB (Polytechnic  Institute of Bragança) as Coordenator Professor and where, among others functions, I was the Head of the Industrial Engineering Department and the  Coordenator of the  Erasmus Program of ESTIG. Since 1990 I have been  involved with several institutions (University Lusíada, ISEE, University Minho, University Nova, ISQ) where I teach subjects in the scientific area of Operations Management and Quantitative Methods with particular relevence to Reliability and Maintenance field. I have conducted several research work in these areas as well as business consulting.

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004
Publications

2021

Resource definition and allocation for a multi-asset portfolio with heterogeneous degradation

Authors
Dias, L; Leitao, A; Guimaraes, L;

Publication
RELIABILITY ENGINEERING & SYSTEM SAFETY

Abstract
When making long-term plans for their asset portfolios, decision-makers have to define a priori a maintenance budget that is to be shared among the several assets and managed throughout the planning period. During the planning period, the a priori budget is then allocated by managers to different operation and maintenance interventions ensuring the overall performance of the system. Because asset degradation is stochastic, a considerable amount of uncertainty is associated with this problem. Hence, to define a robust budget, it is essential to account for several degradation scenarios pertaining to the individual condition of each asset. This paper presents a novel mathematical formulation to tackle this problem in a heterogeneous multiasset portfolio. The proposed mathematical model was formulated as a mixed-integer programming two-stage stochastic optimization model with mean-variance constraints to minimize the number of scenarios with an insufficient budget. A Gamma process was used to model the condition of each individual asset while taking into consideration different technological features and operating conditions. We compared the solutions obtained with our model to alternative practices in a set of generated instances covering different types of multi-asset portfolios. This comparison allowed us to explore the value of modeling uncertainty and how it affects the generated solutions. The proposed approach led to gains in performance of up to 50% depending on the level of uncertainty. Furthermore, the model was validated using real-world data from a utility company working with portfolios of power transformers. The results obtained showed that the company could reduce costs by as much as 40%. Further conclusions showed that the cost-saving potential was higher in asset portfolios in worse condition and that defining a priori operation and maintenance interventions led to worse results. Finally, the results showcased how different decision-maker risk-levels affect the value of taking uncertainty into account.

2021

An unsupervised approach for fault diagnosis of power transformers

Authors
Dias, L; Ribeiro, M; Leitao, A; Guimaraes, L; Carvalho, L; Matos, MA; Bessa, RJ;

Publication
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL

Abstract
Electrical utilities apply condition monitoring on power transformers (PTs) to prevent unplanned outages and detect incipient faults. This monitoring is often done using dissolved gas analysis (DGA) coupled with engineering methods to interpret the data, however the obtained results lack accuracy and reproducibility. In order to improve accuracy, various advanced analytical methods have been proposed in the literature. Nonetheless, these methods are often hard to interpret by the decision-maker and require a substantial amount of failure records to be trained. In the context of the PTs, failure data quality is recurrently questionable, and failure records are scarce when compared to nonfailure records. This work tackles these challenges by proposing a novel unsupervised methodology for diagnosing PT condition. Differently from the supervised approaches in the literature, our method does not require the labeling of DGA records and incorporates a visual representation of the results in a 2D scatter plot to assist in interpretation. A modified clustering technique is used to classify the condition of different PTs using historical DGA data. Finally, well-known engineering methods are applied to interpret each of the obtained clusters. The approach was validated using data from two different real-world data sets provided by a generation company and a distribution system operator. The results highlight the advantages of the proposed approach and outperformed engineering methods (from IEC and IEEE standards) and companies legacy method. The approach was also validated on the public IEC TC10 database, showing the capability to achieve comparable accuracy with supervised learning methods from the literature. As a result of the methodology performance, both companies are currently using it in their daily DGA diagnosis.

Supervised
thesis

2021

Definição de uma Metodologia de Manutenção para a Verificação de Tolerâncias de Equipamentos numa Unidade de Produção de Pneus

Author
José Pedro Tavares Pedro Bernardo

Institution
UP-FEUP

2021

Melhoria contínua aplicada a uma empresa de Serviços Industriais

Author
Inês da Fonseca Moreira

Institution
UP-FEUP

2021

Innovation in Sustainability Communication - A proposal towards a holistic communication framework

Author
Beatriz Fidelis Thomaz Maya

Institution
UP-FEUP

2021

Uma Nova Abordagem na Gestão da Manutenção de Equipamentos Fitness Recorrendo a Tecnologias de Identificação

Author
Ana de Assis Duarte

Institution
UP-FEUP

2020

Optimizing O&M plans for flexible hydropower systems

Author
Xavier Tarrio Fernandes

Institution
UP-FEUP