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About Systems Engineering and Management

Systems Engineering and Management

Systems Engineering and Management research seeks to advance the design, implementation, and improvement of systems for decision support, human-centred operations, intelligence, technology management, and innovation.

Significant challenges arise from optimisation in complex organisations and networks at multiple levels, customercentric service design, and technologybased innovation management and policy, targeting improvements in business performance, productivity, innovation,resiliency, and economic, social, and environmental sustainability.

news
Systems Engineering and Management

Three years of progress: SoTecIn Factory boosts circular innovation in industry

Launched in 2022 under the leadership of INESC TEC, to contribute to the development of a more sustainable and resilient industry sector, SoTecIn Factory is now, three years later, showcasing dozens of technologies designed to boost the circularity of value chains. Over two days, the SoTecIn Factory Start-up Day presented high-impact circular solutions across the plastics and packaging, textile, and agro-food sectors - aiming to connect them with companies and organisations interested in increasing the circularity of their processes.

29th May 2025

Systems Engineering and Management

INESC TEC leads project to facilitate the adoption of Generative AI in industry

INESC TEC is leading a project aimed at making Generative Artificial Intelligence (AI) more accessible, efficient, and applicable within industrial contexts.

27th May 2025

Systems Engineering and Management

Digitalisation in the agro-food sector: a key step towards decarbonisation

Digitalisation plays a vital role in decarbonisation, serving as an enabler of energy efficiency, process optimisation, and the transition to more sustainable operations. In a sector like agro-food, where energy consumption is often high, digital transformation allows for real-time monitoring and control of resource use, while supporting data-driven decision-making.This is where INESC TEC comes in. As part of the Roadmap for Decarbonising the Agro-Food Sector, the institute developed specific methodologies to support the digital transformation of companies within the sector; let’s take a closer look.

26th May 2025

Systems Engineering and Management

Europe’s Leading Robotics and AI Forum Held in Stuttgart, with INESC TEC in Attendance

Recognised as the most important European meeting point in robotics and artificial intelligence (AI), the European Robotics Forum took place in Stuttgart at the end of March. INESC TEC was present at the event, showcasing projects and demonstrating technologies at its own exhibition stand and presenting a scientific paper.

30th April 2025

Systems Engineering and Management

What should we know to make our homes more energy efficient? There's a European project that can support us.

Homes in Europe are estimated to be responsible for approximately 40% of the European Union's energy consumption and 36% of greenhouse gas emissions. DECODIT, a European project featuring INESC TEC, will support the energy transition of homes, through the development of digital services to support citizens in the decision-making process of renovating and managing the energy of their homes. These services will help us choose the solutions that best meet our personal needs.

18th February 2025

Publications

2025

The impact of digital influencers on product/service purchase decision making-An exploratory case study of Portuguese people

Authors
Caiado, F; Fonseca, J; Silva, J; Neves, S; Moreira, A; Gonçalves, R; Martins, J; Branco, F; Au Yong Oliveira, M;

Publication
EXPERT SYSTEMS

Abstract
The growing use of technology and social media has resulted in the emergence of digital influencers, a new profession capable of changing the mentalities and behaviours of those who follow them. This study arises to better understand the potential impact digital influencers might have on the Portuguese population's purchase behaviour and patterns, and for this purpose, seven hypotheses were formulated. An online questionnaire was conducted to respond to these theoretical assumptions and collected data from 175 respondents. A total of 129 valid answers were considered. It was possible to conclude that purchase intention does not necessarily translate into a purchase action. It was also concluded that the relationship between social network use and the purchase of products/services recommended by influencers is only statistically significant for Instagram. Furthermore, the individuals' generation is not statistically significant / linked with purchasing a product/service recommended by influencers. Yet further, a small percentage of respondents have also identified themselves as impulsive shoppers and perceived Instagram as their favourite social network. With the results of this study, it is also possible to state that the influencer's opinion was classified as the last factor considered in the purchase decision process. Additionally, there is a weak negative association between purchasing a product/service recommended by influencers with sponsorship disclosure and remunerated partnership, which decreases credibility and discourages purchasing, in Portugal, a feminine culture which dislikes materialism.

2024

Educational Practices and Strategies With Immersive Learning Environments: Mapping of Reviews for Using the Metaverse

Authors
Beck, D; Morgado, L; O'Shea, P;

Publication
IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES

Abstract
The educational metaverse promises fulfilling ambitions of immersive learning, leveraging technology-based presence alongside narrative and/or challenge-based deep mental absorption. Most reviews of immersive learning research were outcomes-focused, few considered the educational practices and strategies. These are necessary to provide theoretical and pedagogical frameworks to situate outcomes within a context where technology is in concert with educational approaches. We sought a broader perspective of the practices and strategies used in immersive learning environments, and conducted a mapping survey of reviews, identifying 47 studies. Extracted accounts of educational practices and strategies under thematic analysis yielded 45 strategies and 21 practices, visualized as a network clustered by conceptual proximity. Resulting clusters Active context, Collaboration, Engagement and Scaffolding, Presence, and Real and virtual multimedia learning expose the richness of practices and strategies within the field. The visualization maps the field, supporting decision-making when combining practices and strategies for using the metaverse in education, highlights which practices and strategies are supported by the literature, and the presence and absence of diversity within clusters.

2024

Energy-efficient job shop scheduling problem with transport resources considering speed adjustable resources

Authors
Fontes, DBMM; Homayouni, SM; Fernandes, JC;

Publication
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

Abstract
This work extends the energy-efficient job shop scheduling problem with transport resources by considering speed adjustable resources of two types, namely: the machines where the jobs are processed on and the vehicles that transport the jobs around the shop-floor. Therefore, the problem being considered involves determining, simultaneously, the processing speed of each production operation, the sequence of the production operations for each machine, the allocation of the transport tasks to vehicles, the travelling speed of each task for the empty and for the loaded legs, and the sequence of the transport tasks for each vehicle. Among the possible solutions, we are interested in those providing trade-offs between makespan and total energy consumption (Pareto solutions). To that end, we develop and solve a bi-objective mixed-integer linear programming model. In addition, due to problem complexity we also propose a multi-objective biased random key genetic algorithm that simultaneously evolves several populations. The computational experiments performed have show it to be effective and efficient, even in the presence of larger problem instances. Finally, we provide extensive time and energy trade-off analysis (Pareto front) to infer the advantages of considering speed adjustable machines and speed adjustable vehicles and provide general insights for the managers dealing with such a complex problem.

2024

A literature review of economic efficiency assessments using Data Envelopment Analysis

Authors
Camanho, AS; Silva, MC; Piran, FS; Lacerda, DP;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
This paper presents a literature review on Data Envelopment Analysis assessments of economic efficiency, covering methodological developments and empirical applications. We review the seminal models for economic efficiency measurement, involving the optimization of cost, revenue, and profit. The applications of the different modelling approaches are also discussed. Based on a content analysis of papers published between 1978 and 2020 in various sectors, the main areas of study are identified, and the pathways of research developments are discussed. Most studies are based on disaggregated quantity and price data. In addition, the use of panel data is prevalent compared to cross-sectional studies. There is a preponderance of input -oriented studies focused on cost efficiency rather than revenue or profit efficiency. Informed by the historical evolution of economic efficiency assessments portrayed in this review, we suggest directions for future developments. (c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

2024

Synchronisation in vehicle routing: Classification schema, modelling framework and literature review

Authors
Soares, R; Marques, A; Amorim, P; Parragh, SN;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
The practical relevance and challenging nature of the Vehicle Routing Problem (VRP) have motivated the Operations Research community to consider different practical requirements and problem variants throughout the years. However, businesses still face increasingly specific and complex transportation re-quirements that need to be tackled, one of them being synchronisation. No literature contextualises syn-chronisation among other types of problem aspects of the VRP, increasing ambiguity in the nomenclature used by the community. The contributions of this paper originate from a literature review and are three-fold. First, new conceptual and classification schemas are proposed to analyse literature and re-organise different interdependencies that arise in routing decisions. Secondly, a modelling framework is presented based on the proposed schemas. Finally, an extensive literature review identifies future research gaps and opportunities in the field of VRPs with synchronisation.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

2024

Deep Reinforcement Learning-Based Approach to Dynamically Balance Multi-manned Assembly Lines

Authors
Santos, R; Marques, C; Toscano, C; Ferreira, HM; Ribeiro, J;

Publication
FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING: ESTABLISHING BRIDGES FOR MORE SUSTAINABLE MANUFACTURING SYSTEMS, FAIM 2023, VOL 1

Abstract
Assembly lines are at the core of many manufacturing systems, and planning for a well-balanced flow is key to ensure long-term efficiency. However, in flexible configurations such as Multi-Manned Assembly Lines (MMAL), the balancing problem also becomes more challenging. Due to the increased relevance of these assembly lines, this work aims to investigate the MMAL balancing problem, to contribute for a more effective decision-making process. Therefore, a new approach is proposed based on Deep Reinforcement Learning (DRL) embedded in a Digital Twin architecture. The proposed approach provides a close-to-reality training environment for the agent, using Discrete Event Simulation to simulate the production system dynamics. This methodology was tested on a real-world instance with preliminary results showing that similar solutions to the ones obtained using optimization-based strategies are achieved. This research provides evidence of success in terms of dynamic resource assignment to tasks and workers as a basis for future developments.