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Maintenance Management
Publication . Dinis, Duarte; UNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e Industrial; DEMI - Departamento de Engenharia Mecânica e Industrial; Elsevier
Maintenance management is defined as "all management activities that determine the maintenance requirements, objectives, strategies and responsibilities, and implementation of them by such means as maintenance planning, maintenance control, and improvement of maintenance activities and economics". The purpose of this research work is to present a brief review on key problems in maintenance management and on selected solutions to address these problems, particularly within aviation maintenance, framed within business analytics (BA), which comprises descriptive, predictive, and prescriptive perspectives. Unlike manufacturing, in which most activities are deterministic by nature, characterized by well-defined execution lead times and required resources, being it labor, tools, or parts and materials, maintenance presents an important stochastic component. Maintenance can be divided into preventive maintenance and corrective maintenance. The former refers to prespecified tasks, carried out at predetermined intervals, being its work essentially deterministic. The latter results from the probabilistic nature of failures, performed upon a fault is identified, being its work inherently stochastic. The workload resulting from corrective maintenance can be more than half of the total maintenance workload according to some studies, making it an important challenge for effective and efficient maintenance management. This research work is expected to be of interest for researchers and practitioners alike, by identifying the sources of uncertainty associated with maintenance management and by providing references on relevant methods to model and control such uncertainty.
The role of artificial intelligence in smart city systems usage
Publication . Santos, Joao Pedro Ferreira dos; de Matos, Celso Augusto; Groznik, Aleš; NOVA Information Management School (NOVA IMS); Elsevier
Smart city and smart home systems are among the most impactful technological advancements of recent years, offering innovative solutions while also presenting new challenges for businesses and society. This study aims to investigate the antecedents (both drivers and barriers) of smart city system adoption, specifically those that incorporate artificial intelligence, and to analyse their effects on behavioral outcomes—more specifically, well-being and individual impact. The proposed model was tested using structural equation modelling with data from a survey of 211 individuals in Portugal. The main findings indicate that ubiquity and gamification were the most influential drivers of smart city system adoption. Conversely, perceived risks associated with these systems hindered their adoption. Additionally, our study demonstrated that trust significantly interacts with empowerment, perceived risk, and usage intention. Finally, usage intention was found to have a positive impact on well-being and individual outcomes in daily life.
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Fundação para a Ciência e a Tecnologia
Programa de financiamento
Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017/2018) - Financiamento Base
Número da atribuição
UIDB/00097/2020