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Systems Engineering and Management
About the Domain
We feature competences that allow us to support innovation, efficiency, and sustainability in organisations through advanced data analysis, process optimisation, and the development of people-centred systems and services. These skills include:
Digital Transformation
Operations Management
Operations Research
Service Design and Innovation
Research Challenges
The Systems Engineering and Management scientific domain bridges management and engineering to advance the design, implementation, and improvement of systems for decision support, human-centred operations, technology management and innovation. The team addresses the different activities of the systems engineering lifecycle with a focus on four research challenges:
Main Achievements
Our research in this domain has made significant contributions to the digital transformation of organisations, impacting decision-making, sustainability, and the creation of smart industrial platforms. Our solutions combine explainable AI, user-centred design, and advanced optimisation methods.
Explainable AI applied to operations management
We developed explainable Artificial Intelligence (XAI) methods to support decision-making in dynamic operational contexts, e.g., inventory management, order allocation, scheduling, and vehicle routing. These solutions combine interpretable symbolic models with human knowledge, enabling more reliable and real-world adaptive decisions. The methods have been applied in European projects and companies. Publication: here.
Service design for innovation and sustainability
We developed service design methods applied to complex systems and servitisation in industry. These approaches were essential in designing the Portuguese Electronic Health Record and involved collaborations with entities such as EDP and Experio Lab. We created the ECO-Service Design method to support sustainable transformation and citizen engagement strategies in sustainable energy solutions. Publication here.
Digital twin design methods
As part of the Transformer 4.0 (TRF4.0) project, led by EFACEC in partnership with the Massachusetts Institute of Technology (MIT), we developed a smart digital platform for the life-cycle management of power transformers, supported by digital twins, AI, and optimisation. This solution provides predictions on future equipment performance and supports decisions regarding design and grid response. Publication here.
Selected Publications
Citizen engagement with sustainable energy solutions- understanding the influence of perceived value on engagement behaviors
Banica, B;Patrício, L;Miguéis, V;
2024
ENERGY POLICY
Supporting decision-making of collaborative robot (cobot) adoption: The development of a framework
Silva, A;Simoes, AC;Blanc, R;
2024
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
Optimizing multi-attribute pricing plans with time- and location-dependent rates for different carsharing user profiles
Golalikhani, M;Oliveira, BB;Correia, GHD;Oliveira, JF;Carravilla, MA;
2024
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
Transitioning trends into action: A simulation-based Digital Twin architecture for enhanced strategic and operational decision-making
Santos, R;Piqueiro, H;Dias, R;Rocha, CD;
2024
COMPUTERS & INDUSTRIAL ENGINEERING
Team Members
Team Leaders
Team Members
Abílio Pereira Pacheco
Researcher
Ademar Aguiar
Centre Coordinator
Alexandra Francisco Alves
Alexandra Xavier
Centre Coordinator
Alípio Torre
Researcher
Américo Azevedo
TEC4 Coordinator
Ana Camanho
Research Coordinator
Ana Carolina Chaves
Researcher
Ana Carolina Tavares
Researcher
Ana Cristina Simões
Senior Researcher
Ana Maria Rodrigues
Ana Nunes Alonso
Assistant Researcher
Ana Viana
Research Coordinator
André Filipe Garcia
Researcher
André Serra Santos
Assistant Researcher