Special Sessions
List Of
Special
Sessions
DETAILED DESCRIPTION:
SS1 – Cyber-Physical Systems and Predictive Maintenance for Enhanced Reliability and Availability in Industry 4.0
The development of Industry 4.0 has brought a paradigm change in the industry’s approach to production and maintenance. This new era leverages cutting-edge technologies such as cyber-physical systems (CPS), the Industrial Internet of Things (IIoT) and advanced data analytics to create highly responsive and efficient industrial environments. The focus is on achieving higher levels of system reliability and availability through predictive maintenance and real-time decision making.
Cyber-physical systems (CPS) play a key role in this transformation by integrating computational capabilities with physical processes to enable intelligent monitoring, control and automation of industrial operations. These systems can simulate working conditions in real time, providing valuable insights that improve production efficiency and decision-making. As a result, CPS is becoming a cornerstone in the evolution towards smart factories and intelligent production environments.
Predictive maintenance complements this approach by moving from traditional, reactive maintenance strategies to more proactive ones. By harnessing the power of big data, machine learning and artificial intelligence, predictive maintenance enables early detection of potential equipment failures, preventing costly downtime and extending the life of machinery. This change not only reduces maintenance costs, but also significantly improves overall system reliability and availability. costs, but also significantly improves overall system reliability and availability.
This special session aims to provide a platform for thought leaders, researchers, and industry practitioners to share their latest findings, innovations, and experiences. The session will cover a wide range of topics that are integral to the successful implementation of Industry 4.0 technologies, fostering an environment of collaborative learning and knowledge exchange.
Topics of interest include but are not limited to the following:
- Smart manufacturing and maintenance
- Smart factories and Industrial Internet of Things (IIoT)
- Robotics and mechatronic systems
- Mechatronics systems design
- Mechanical systems design and analysis
- Digital twins
- Multi-Agent Systems (MAS)
- Automation measuring systems and sensors
- Human-Machine Interaction and Machine-to-Machine Communication (M2M)
- Learning control and cognitive computing
- Reliability and risk assessment
- Cybersecurity applications in industrial systems
- Simulation and modeling of production systems
- Artificial intelligence in decision support systems
- Intelligent systems for predictive maintenance
Attendees will benefit from insightful presentations and discussions exploring the latest advances in CPS and predictive maintenance. They will have the opportunity to network with peers, explore innovative solutions and gain a deeper understanding of how these technologies can improve reliability and availability in the context of Industry 4.0. This session will stimulate new ideas, collaborate and advance the industrial sector.
Organizers:
Katarzyna Antosz: Rzeszow University of Technology, PL
katarzyna.antosz@prz.edu.pl
Erika Ottaviano: University of Cassino and Southern Lazio, IT,
ottaviano@unicas.it
Pierluigi Rea: University of Cagliari, IT,
pierluigi.rea@unica.it
Arkadiusz Gola, Lublin University of Technology, Poland,
a.gola@pollub.pl
Alejandro Pereira: University of Vigo Spain, ES,
apereira@uvigo.es
DETAILED DESCRIPTION:
SS2 – Industrial Engineering in Era of Digital Transformation
Nowadays, collaborative engineering approaches, tools and practices are of upmost importance for reaching a sustainable development in the current digitalization era. Thus, the development of Manufacturing, Management, and Maintenance Models, Methods, systems and platforms oriented to a collaborative and sustainable Industry 4.0 (or I4.0 for short) is a challenging outcome. This special session aims at contributing with new insights regarding manufacturing, management and/ or maintenance paradigms (strategies), methods, tools, and practices aligned with the nowadays necessity to create and implement collaborative and sustainable I4.0 manufacturing systems.
Therefore, contributions are encouraged in manufacturing, management and/ or maintenance to reach collaboration and sustainability purposes in I4.0 oriented manufacturing systems. The authors should consider in their original contributions, the clear identification of the collaboration and/or the sustainability and the I4.0 domain, the clear description of the proposed paradigm, method, tool, and/ or practices approached, and its validation in the scope of at least one of the three main domains considered in this special sessions (collaboration, sustainability and industry 4.0) for at least one of the scientific areas underlying this special session (manufacturing, management, and maintenance).
Regarding this structure for the authors’ contributions, are expected new theoretical and practical insights for the stakeholders involved in the I4.0 design, management and/ or implementation of collaborative and/or sustainable manufacturing systems.
Topics of interest include but are not limited to the following:
- Circular economy, economic, environmental, and/ or social sustainability
- Industrial engineering: manufacturing, management and/ or maintenance:
- paradigms: dynamic, integrated, distributed, intelligent, predictive, parallel and real time based management,
- methods,
- tools,
- practices,
- operations,
- critical success factors,
- metatheory,
- organizational change and transformation,
- learning organization,
- Industry 4.0 pillars:
- Cyber Physical Systems,
- Artificial Intelligence,
- Big data analytics,
- Supply chain management,
- Horizontal and vertical integration,
- Cybersecurity,
- New business models,
- Open Design,
- Cloud manufacturing,
- Additive manufacturing,
- Autonomous and Collaborative Robots,
- Simulation and augmented reality.
Organizers:
Justyna Trojanowska, Poznan University of Technology, PL
justyna.trojanowska@put.poznan.pl
Leonilde Varela, University of Minho, PT
leonilde@dps.uminho.pt
Sobowale Ademola Adeniyi, University of Minho, PT
id10361@alunos.uminho.pt
Vijaya Kumar Manupati, NITIE Mumbai, IN
manupativijay@nitie.ac.in
Michał Szaroleta, Łukasiewicz – Poznan Institute of Technology, PL
michal.szaroleta@pit.lukasiwicz.gov.pl
DETAILED DESCRIPTION:
SS3 – Engineering Applications for Medical and Healthcare Devices – ENGCARE 2025
Technologies and applications for medical and healthcare devices are part of the actual human daily life and with an increasing demand. Nowadays, we are able to find them practically everywhere, apart from the healthcare units, as integrated, among others, in our homes, body, mobile devices and vehicles, with the objective of improving our safety, comfort, performance and quality of life.
We invite researchers, academics, and professionals to submit either original research (work in progress or developed) as well as review articles that will contribute to the dissemination of Engineering Applications for Medical and Healthcare Devices.
Topics of interest include but are not limited to the following:
- Medical devices for monitoring, diagnosis, and therapy
- Blockchain in Healthcare Devices
- IoT-enabled Healthcare Devices
- Cybersecurity in Medical Devices
- Sustainable and Eco-friendly Medical Devices
- Human-Machine Interfaces for Healthcare
- Biomedical sensors
- Healthcare sensors
- Mobile healthcare
- Home healthcare
- Wearable healthcare
- In-car healthcare
- Artificial intelligence in medical devices and systems
- Ambient assistive living
- Tele-healthcare
- Serious games for healthcare and medical training
- Medical robotics
- Inclusive technology
- medical devices design
- Safety and usability in medical devices
- AR, VR or MR in healthcare and medical devices
- Emerging Technologies in medical devices and systems
Organizers:
Vítor Carvalho, 2Ai-EST,IPCA & Algoritmi RD- Minho University, PT
vcarvalho@ipca.pt
Filomena Soares, Algoritmi RD- Minho University, PT
fsoares@dei.uminho.pt
Demétrio Matos, iD+-IPCA, PT
dmatos@ipca.pt
DETAILED DESCRIPTION:
SS4 – Optimization in Industry 5.0
This proposed special session will explore optimization techniques and their applications in addressing Industry 5.0 challenges in the areas of Industrial Engineering and Management and Robotics. Potential topics may include, but are not limited to supply chain optimization, production planning, collaboration between humans and robots, resource allocation, and decision-making under uncertainty. The session aims to present innovative approaches that enhance efficiency, reduce costs, and improve overall operational performance. State-of-the-art methods and real-world case studies may help demonstrate the potential of optimization in today’s competitive industrial landscape.
Organizers:
Rui Borges Lopes, DEGEIT/CIDMA, Universidade de Aveiro, PT
rui.borges@ua.pt
Eliana Costa e Silva, CIICESI, ESTG, Instituto Politécnico do Porto and Centre Algoritmi, University of Minho, PT
eos@estg.ipp.pt
DETAILED DESCRIPTION:
SS5 – Statistical and critical thinking impact on decision making under uncertainty
UNESCO’s 2010 report highlighted engineering’s crucial role in facing global challenges, a point reinforced in the 2021 report, emphasizing engineering’s importance for sustainable development and addressing human needs. As the world becomes more data-driven and technology-focused, educators and professionals are called upon to adopt new methodologies to tackle real-world complexity and uncertainty. Central to this is the integration of statistical thinking, critical thinking, machine learning (ML), and artificial intelligence (AI) in decision-making. The rising demand for graduates with both technical and critical problem-solving skills poses a unique challenge for STEM educators.
This special session aims to bring together engineers, educators, researchers, and industry experts to share insights, experiences, and innovative practices regarding the evolving role of statistical methods, critical thinking, and AI/ML technologies in decision-making under uncertainty. We seek to explore how these tools are being integrated into engineering education, business practices, and scientific research, and how they contribute to improving decision-making processes, especially when facing complex, uncertain environments.
Moreover, this session will highlight the importance of education in statistics, focusing on how active learning approaches can cultivate critical thinking skills. In an age where data science and artificial intelligence are transforming industries, fostering a deeper understanding of uncertainty and decision-making is essential for both academia and industry.
Key topics will include the intersection of statistical methodologies with machine learning and AI, and how they are revolutionizing fields such as engineering, finance, environmental sciences, healthcare, and social sciences. The session will also address how education systems can better equip students with the critical thinking skills needed to interpret data and make informed decisions using these advanced tools.
Topics of interest include but are not limited to the following:
- Machine Learning and AI Applications in Decision Making
- The Role of Statistics and Critical Thinking in AI/ML Model Interpretation
- Teaching and Communicating Statistics in the Era of Data Science
- Data Science and Predictive Analytics in Engineering
- Statistical Methods for Uncertainty Quantification in Industry
- AI and Machine Learning in Medical Decision Making
- Educational Approaches for Teaching Statistics and Critical Thinking
- Innovative Applications of Statistics in Business, Engineering, and Social Sciences
- Ethical Implications of AI and Statistical Models in Decision Making
- Impact of Temporal and Spatial Statistics on Environmental Engineering
This session will provide a platform for academia and industry to exchange knowledge, explore new approaches, and discuss emerging challenges and opportunities related to the use of statistics, machine learning, and critical thinking in decision-making under uncertainty. We aim to foster collaboration that bridges the gap between educational methodologies and industry needs in this fast-evolving landscape.
Organizers:
A. Manuela Gonçalves – Centre of Mathematics (CMAT), School of Sciences, University of Minho, PT
mneves@math.uminho.pt
Celina Pinto Leão – Centro ALGORITM, School of Engineering, University of Minho, PT
cpl@dps.uminho.pt
M. Teresa Malheiro – Centre of Mathematics (CMAT), School of Sciences, University of Minho, PT
mtm@math.uminho.pt
DETAILED DESCRIPTION:
SS6 – Innovations in Control, Automation and Robotics
This special session addresses all aspects of control, automation and robotics related to designing safe, reliable and efficient engineering applications. Researchers and students from academia as well as industry experts are invited to share their latest findings, best practices, experiences and visions related to these important fields of engineering.
Topics of interest include but are not limited to the following:
- Modern Control Approaches;
- Modelling and Simulation for Control;
- Case Studies of Control and Automation;
- Robotics Applications;
- Software Tools for Control Systems Design, Automation and Robotics;
- New Trends in Engineering Education related to Control, Automation and Robotics;
- Networked Control systems;
- Industrial Networks;
- Industrial Communication Protocols;
- Cyber-Physical Systems;
- Internet of Things;
- Industry 4.0;
- Industry 5.0.
Organizers:
Frantisek Gazdoš, Tomas Bata University in Zlín, Faculty of Applied Informatics, CZ
gazdos@utb.cz
Jiří Vojtěšek, Tomas Bata University in Zlín, Faculty of Applied Informatics, CZ
vojtesek@utb.cz
DETAILED DESCRIPTION:
SS7 – Sustainable Development: Digitalization and 3D Information in Manufacturing Systems
This special session focuses on actual aspects of the UN Sustainable Development Strategy as it applies to research, innovation, and technology, especially industry and transport. Particular attention is devoted to the challenges of their digitalization within the concepts of Industry 4.0 and Industry 5.0, without which efforts to achieve the global Sustainable Development Goals cannot be realized.
We invite researchers, PhD students, university students, specialists from design offices and research centers, and industry and transport experts to contribute to this session. Share your latest research, innovation results, and new scientific ideas that are relevant to the critical areas of engineering in sustainable development and digitalization.
Topics of interest include but are not limited to the following:
- Current missions, strategies, and practical challenges for sustainable industrial and transport development;
- Modeling, IT technologies, and digital methods for representing, processing, and exchanging information in engineering;
- Technologies for optimizing the life cycle of complexes, systems, and products in industry and transport;
- Scientific and technical solutions to the problems of ecologization, decarbonization, green energy, and alternative energy sources;
- The role of 3D information in sustainable development;
- Digital twins;
- Augmented and virtual reality;
- Internet of Things;
Organizers:
Andrii Marchenko, National Technical University ‘Kharkiv Polytechnic Institute’, Kharkiv, UA
andrii.marchenko@khpi.edu.ua
Sergey Dobrotvorskiy, National Technical University ‘Kharkiv Polytechnic Institute’, Kharkiv, UA
sergiy.dobrotvorskyy@khpi.edu.ua
Yevheniia Basova, National Technical University ‘Kharkiv Polytechnic Institute’, Kharkiv, UA
yevheniia.basova@khpi.edu.ua
DETAILED DESCRIPTION:
SS8 – Industry 4.0: Digitalization, Advanced Product Design, and Smart Manufacturing Technologies
The organizers of this special session invite researchers to submit original research papers, surveys, and case studies in the field of Industry 4.0, focusing on areas that contribute to industrial digitalization and the modernization of manufacturing. This session aims to bring together novel contributions from researchers and practitioners addressing the latest technologies and developments in key areas of smart manufacturing, including advanced manufacturing technologies and processes, mechatronic devices, product design and development, smart materials, data and artificial intelligence, cyber-physical systems, predictive maintenance, sustainability, industrial communication, and IoT/IIoT systems. Submissions are also encouraged on emerging topics such as additive manufacturing and new hybrid processes, advanced robotics, modeling and simulation for smart manufacturing, smart material handling and transportation vehicles, vision-guided robotics, digital twins, machinery health monitoring, and edge, fog, and cloud computing. This session provides a forum for reviewing, disseminating, and identifying critical challenges that drive the industrial digitalization process, fostering the development of sustainable and efficient manufacturing systems.
Topics of interest include but are not limited to the following:
- Additive Manufacturing and New Hybrid Processes,
- Advanced Mechatronics Devices,
- Advanced Product Design and Development,
- Automation and Robotics,
- Big Data, Machine Learning and Deep Learning,
- Case Studies and Testbeds on Smart Manufacturing,
- Cyber Physical Systems,
- Developments in Intelligent Manufacturing Systems,
- Edge, Fog, and Cloud Computing,
- Health Monitoring, Failure Inspection, and Diagnosis of Machinery,
- Industrial Communication Protocols,
- Industrial Vision Systems,
- IoT and IIoT,
- Mechatronics Sensing and Control,
- Modelling and Simulation for Smart Manufacturing,
- Refurbishment And Re-Manufacturing of Machinery,
- Simulation and Digital Twins,
- Smart Actuators and Materials,
- Smart Material Handling and Transportation Vehicles,
- Sustainable Materials, Products and Processes,
- Vision Guided Robotics,
- 5G in Industry.
Organizers:
Pedro Torres, Polytechnic University of Castelo Branco, PT
pedrotorres@ipcb.pt
Nuno Fernandes, Polytechnic University of Castelo Branco, PT
nogf@ipcb.pt
Flávia Barbosa, Institute of Science and Innovation in Mechanical Engineering and Industrial Engineering, PT
fbarbosa@inegi.up.pt
DETAILED DESCRIPTION:
SS9 – Artificial Intelligence, Cognitive Systems and the Learning Brain (AICSLB)
A review of the history of the development of artificial intelligence (AI) reveals that brain science has resulted in significant breakthroughs in AI, including the advent of deep learning. Notwithstanding the considerable advancements that have been made in the field of AI and its applications, a notable disparity persists between the capabilities of AI and those of the human brain. It is of the utmost importance to establish a bridge between brain science and AI research, including a link from brain science to AI and a connection from understanding the brain to simulating it.
The goal of the Session: to strengthen scientific interdisciplinary relations and to facilitate exchange of experience between leading scientists and discussion on acute questions and promising directions in the area of artificial intelligence.
Topics include cognitive modeling (more broadly, cognitive sciences), artificial intelligence (more broadly, computer science), computational neuroscience (more broadly, brain sciences), language sciences, robotics, virtual reality, cybersecurity, quantum computer, mathematical models in economics, sociology, educational sciences, philosophy, art, management, industrial and military applications.
Although some might find the concept of AICSLBEd alienating, the algorithms and models that comprise AICSLBEd form the basis of an essentially human endeavour. AICSLBEd offers the possibility of learning that is more personalised, flexible, inclusive, and engaging. It can provide teachers and learners with the tools that allow us to respond not only to what is being learnt, but also to how it is being learnt, and how the student feels.
Topics of interest include but are not limited to the following:
- Human-Centered AI: Context plays a critical role in enabling AI systems to interact with humans and other agents naturally and appropriately.
- Human-Computer Interaction: The incorporation of context is critical to enhance user experience in AI systems. How can we design AI systems that effectively leverage contextual information to improve the overall user experience?!
- Ethical and Responsible AI: Context is critical for addressing ethical considerations in AI, including issues of privacy, bias, and fairness.
- Explainable AI: Contextualizing explanations is essential to understanding how and why AI systems work, evaluating their effectiveness and efficiency, and helping users achieve their goals.
- Machine Learning and Knowledge Representation: Contextual information must often be inferred from data, thus requiring machine learning approaches for dynamic adaptation of context models and methods for reasoning with uncertainty.
- Ambient Intelligent Systems: AmI systems are characterized by embedded, context-aware, context-sensitive, personalized, adaptive, anticipatory, and socially intelligent technologies.
- Natural Language Processing: Context is vital for natural language processing, improving accuracy and effectiveness in understanding and generating natural language.
As an interdisciplinary topic, contextual AI has clear relations to linguistics and semiotics, cognitive science and psychology, mathematics and philosophy, as well as sociology and anthropology. The MRC workshop series is highly interactive and offers a platform for researchers and practitioners from different disciplines to exchange ideas and discuss the latest advancements in contextual AI. As context research is inherently transdisciplinary, we encourage a range of publication formats that may not be commonly seen in the AI community, including narrative reviews, ethnographic stories, and artistic creations, reflecting the diverse perspectives and approaches needed to fully understand the complexities of context.
Organizers:
Olena Hrybiuk, Associate Professor, Leading Researcher, International Scientific and Technical University, Institute for Digitalisation of Education of the NAES of Ukraine, UA
olenagrybyuk@gmail.com
Dr Kamil Filipek, Centre for Artificial Intelligence and Computer Modelling, Marii Curie Skłodowska University in Lublin, PL
Dr Anna Pyzara, Faculty of Mathematics, Physics and Computer Science, Marii Curie Skłodowska University in Lublin, PL
Dr Eliza Jackowska-Boryc, Faculty of Mathematics, Physics and Computer Science, Marii Curie Skłodowska University in Lublin, PL
DETAILED DESCRIPTION:
SS10 – Designing and Engineering for Resilience: Innovation, Sustainability, and Digital Transformation
In this Special Session, we will explore how design and engineering can drive resilience in digitally transforming economies, with a focus on sustainable innovation. In a rapidly changing world, where technological, social, and environmental shifts are constant, the need to develop resilient systems, products, and processes has become imperative. This session offers a unique opportunity to discuss design and engineering strategies that create economic and social value while promoting sustainability and adaptation to change.
SS10 invites researchers, designers, engineers, and entrepreneurs to explore and share innovations that integrate resilience across different industrial sectors. We will adopt a multidisciplinary approach to strengthen collaboration between innovation, technology, and sustainability, with a vision centered on digital transformation and resource protection. The goal is to foster the creation of business cooperation and knowledge networks that contribute to building a more resilient, human-centric, and sustainable future.
Topics of interest include but are not limited to the following:
- Resilient Design for Sustainable Innovation: Design strategies that promote product adaptability and longevity.
- Digital Transformation and Sustainability: Integration of emerging technologies, such as IoT, artificial intelligence, and additive manufacturing, to enhance resilience in products and processes.
- Design and Engineering for Circular and Regenerative Economies: Approaches that maximize resource reuse and promote environmental regeneration.
- Technological Solutions for Well-Being and Productivity: Integration of smart technologies to optimize user well-being and process efficiency.
- Collaborative Design and Knowledge Networks: Creation of cooperation networks that facilitate the joint development of technological and sustainable innovations.
- Sustainable Innovations with a Focus on Endogenous Resources: Design and engineering strategies that leverage local and traditional resources to create competitive and sustainable value.
- Challenges and Opportunities in Sustainable Digital Transformation: Case studies and new trends demonstrating how digital transformation can be a lever for sustainability.
- Integration of Engineering and Design in Urban Resilience: Solutions for smart and sustainable cities, focusing on mobility, energy, and green infrastructure.
Organizers:
Maria João Félix, CIAUD, Universidade de Lisboa & Polytechnic Institute of Cávado and Ave, PT
mfelix@ipca.pt
Gilberto Santos, ID+ & Polytechnic Institute of Cávado and Ave, PT
gsantos@ipca.pt
Ricardo Simões, 2Ai & Polytechnic Institute of Cávado and Ave, PT
rsimoes@ipca.pt
DETAILED DESCRIPTION:
SS11 – Machine Learning Algorithms & Applications for Engineering and Business
This session aims to bring together cutting-edge research on the latest advancements in machine learning algorithms, from researchers and practitioners in academia and industry. Their applications to real-world problems and their potential to revolutionise the user experience, particularly in the engineering and business domains, are especially encouraged.
Submission and presentation of papers is encouraged to provide an excellent international forum for sharing knowledge and in theory, methodology and applications of on Machine Learning & Applications. The following topics reflect some of the diversity of applications and research areas.
Topics of interest include but are not limited to the following:
- Artificial neural networks
- Bayesian networks
- Data Mining
- Decision making by machine learning
- Deep neural networks
- Evaluation metrics for intelligent search
- Hybrid learning algorithms
- Integration of machine learning algorithms with other technological systems
- Intelligent virtual environments
- Learning and forecasting problems
- Learning methods and analysis
- Literature review of machine learning algorithms/applications
- Machine learning algorithms/applications
- Reinforcement learning
- Smart industries and cities
- Statistical learning
- Supervised machine learning
- Unsupervised machine learning
Organizers:
Filipe R. Ramos, CEAUL, University of Lisbon, PT
frramos@ciencias.ulisboa.pt
Fernanda A. Ferreira, UNIAG – Polytechnic Institute of Porto, PT
faf@esht.ipp.pt
Maria Teresa Pereira, Polytechnic Institute of Porto, PT
mtp@isep.ipp.pt
Marisa Oliveira, Polytechnic Institute of Porto, PT
mjo@isep.ipp.pt
DETAILED DESCRIPTION:
SS12 – Risk Management, Digital Processes, Machine Learning, Modeling and Instrumentation Applied to Sustainable and Intelligent Industrial Processes
The special session on “Risk Management, Digital Processes, Machine Learning, Modeling, and Instrumentation for Sustainable and Intelligent Industrial Processes” aims to explore the transformative role of digital innovation in modern industry. As industries seek to minimize environmental impact and optimize efficiency, advanced technologies such as machine learning and digital process modeling are essential in creating sustainable, intelligent solutions. This session will delve into the latest developments in risk management and the role of data-driven decision-making tools to mitigate operational hazards while enhancing productivity. SS12 invites researchers with a focus on applying machine learning models, advanced digital process automation, and instrumentation to industrial environments to drive sustainability goals. Topics will include predictive maintenance, resource optimization, and the integration of smart technology in industrial processes to reduce energy consumption and emissions.
Topics of interest include but are not limited to the following:
- Instrumentation to Industrial Environments
- Risk Management
- Digital Process Automation
- Machine Learning
- Industrial Modeling
- Sustainable Industry
- Intelligent Processes
- Machine Vision
- Safety Engineering Green
- Human Factors and Ergonomics
- Circular Economy
- Nanotechnology
- Artificial Intelligence & Computing
- Digital Twins
Organizers:
Delfina Gabriela Garrido Ramos, University of Trás-os-Montes and Alto Douro | INESC TEC – Institute for Systems and Computer Engineering, Technology and Science, PT
dgramos@utad.pt
José Boaventura Ribeiro da Cunha, University of Trás-os-Montes and Alto Douro, and INESC TEC – Institute for Systems and Computer Engineering, Technology and Science, PT
jboavent@utad.pt
Vítor Manuel de Jesus Filipe, University of Trás-os-Montes and Alto Douro and
INESC TEC – Institute for Systems and Computer Engineering, Technology and Science, PT
vfilipe@utad.pt
DETAILED DESCRIPTION:
SS13 – Robotics, AI, and Digital Twin for Smart Intralogistics
The integration of Robotics, Artificial Intelligence (AI), and Digital Twin technologies is transforming internal logistics processes, enabling companies to achieve unprecedented levels of efficiency, flexibility, and scalability. These technologies are key drivers in creating intelligent intralogistics systems that not only optimize operational workflows but also enhance decision-making through data-driven insights.
Robotics plays a crucial role in automating repetitive and time-consuming tasks, such as material handling and inventory management. Collaborative robots further enable seamless interaction between humans and machines, fostering productivity while maintaining workplace safety. On the other hand, AI-powered algorithms facilitate real-time optimization of logistics operations, predictive analytics, and demand forecasting, ensuring adaptability in dynamic industrial environments.
The emergence of Digital Twin technology has further revolutionized intralogistics by enabling real-time simulations, predictive maintenance, and enhanced operational visibility. By creating virtual replicas of physical systems, organizations can monitor, optimize, and even predict logistics performance with unprecedented precision.
This special session aims to bring together researchers, practitioners, and industry leaders to explore advancements, challenges, and applications of these technologies in intralogistics. It will provide a platform to share knowledge, discuss innovative solutions, and identify future directions for smart intralogistics systems.
Topics of interest include but are not limited to the following:
- Autonomous and intelligent material handling systems
- AI-driven decision support in intralogistics
- Added-value and Human-robot collaboration in intralogistics
- Digital Twin applications for real-time monitoring and optimization
- Integration and interoperability of intralogistics systems
- Quality control, predictive maintenance and operational efficiency
- Challenges and barriers to adopting advanced intralogistics technologies
- Future trends in Robotics, AI, and Digital Twin technologies
- Advanced simulation for intralogistics planning and optimization
Organizers:
Pedro Senna, INESC TEC, PT
pedro.senna@inesctec.pt
António Almeida, INESC TEC, PT
antonio.h.almeida@inesctec.pt
Ana Correia Simões, INESC TEC, PT
ana.c.simoes@inesctec.pt
DETAILED DESCRIPTION:
SS14 – Intelligent mechatronic systems – design, materials, simulation, and dynamical analysis
The special session on “Intelligent mechatronic systems design, materials, simulation, and dynamical analysis” aims to presents some innovative research results in the field of opto-mechatronics, dynamic analysis and simulation for optimization of the mechatronic systems, new materials and technologies used in construction of smart mechatronic systems, autonomous or semi-autonomous mobile mechatronic systems. The session will cover a wide range of topics that are relevant for the successful development of new mechatronic systems used in various fields.
This special session aims to bring together researchers, academics, PhD students and industry professionals to facilitate the exchange of knowledge and experience and to strengthen future collaborations.
We invite researchers, academics, PhD students and professionals to submit original research or review articles for sharing knowledge in the field of smart mechatronic applications.
Topics of interest include but are not limited to the following:
- Mechatronics of autonomous and semi-autonomous mobile systems
- AI and Data Science in mechatronics
- Intelligent motion control systems for smart mechatronics and robotics devices
- Dynamic analysis of mechatronic systems
- Opto-mechatronic systems
- Materials and technologies used in smart mechatronics
- Advanced mechatronic product design and development
- Mechatronic medical devices design
- Mechatronics applications
Organizers:
Bogdan Gramescu, National University of Sciences and Technology Politehnica Bucharest, RO
bogdan.gramescu@upb.ro
Liliana-Laura Badita-Voicu, National Institute of Research and Development in Mechatronics and Measurement Technique – INCDMTM Bucharest, RO
badita_l@yahoo.com
Doina Daniela Cioboata, National Institute of Research and Development in Mechatronics and Measurement Technique – INCDMTM Bucharest, RO
cioboatadoina@yahoo.com
DETAILED DESCRIPTION:
SS15 – Young Scientists summit on Science and Engineering
Young minds have the power to bring new perspectives and an ability to tackle problems free from conventional solutions, although lacking experience. In this event, young scientists are invited to present their research in science and engineering, with a focus on innovative solutions for a sustainable future. Researchers and students from academia as well as industry are invited to share their latest findings, best practices, experiences and visions related to important fields of science and engineering. Participation in this session provides a well-established platform for undergraduate, MSc and PhD students, postdocs, entrant engineers and other young scientists, contributing to develop presentation skills, build valuable contacts and forge durable scientific relationships.
This session covers a broad spectrum of topics, fostering multidisciplinary discussions and offering excellent opportunities for the exchange of innovative ideas and potential collaborations. Topics include, but are not limited, to energy, environment, and physico-chemical sciences and engineering.
Organizers:
Victor G. L. Souza, METRICS, NOVA School of Science and Technology, Universidade NOVA de Lisboa, PT
v.souza@fct.unl.pt
Ana Luisa Fernando, METRICS, NOVA School of Science and Technology, Universidade NOVA de Lisboa, PT
ala@fct.unl.pt
DETAILED DESCRIPTION:
SS16 – Innovation in Engineering to Prevent Failure of Mechanical Components and Structures
This important session will be an opportunity for scientists and engineers from academia and industries around the world to share their scientific findings on all topics relating to innovation in engineering to prevent the failure of mechanical components and structures. This multidisciplinary session will cover many aspects of Mechanical Fracture and Maintenance Management. It will provide rapid, high-quality synergies and communications with engineers and scientists in different areas of Mechanical and Civil Design, Condition-based Maintenance, Materials, Reliability, Risk Analysis, and Artificial Intelligence.
Topics of interest include but are not limited to the following:
- Failure Analysis
- Condition-based-Maintenance
- Fracture Analysis
- Developments of Mechanical Fracture in Advanced Materials
- Life Cycle Assessment
- Extended Life Models
- Fatigue Life Prediction Models
- Risk Management applied to Mechanical Design
- Risk Management applied to Maintenance
- Integrated Management Systems
- Artificial Intelligence applied to prevent failures
- Artificial Intelligence applied to Maintenance Management
- Optimization Models
- Case of studies of naval, aeronautic, aerospatial, automotive, railway and other industrial sectors
Organizers:
Teresa Leonor Martins Morgado, Unit for Innovation and Research in Engineering, Lisbon School of Engineering of Polytechnic University of Lisbon, PT
tmorgado@dem.isel.ipl.pt; tlrcmm@gmail.com
Suzana Paula Lampreia, Naval Research Centre, Science and Technology Department of Portuguese Naval Academy, Escola Naval, Base Naval de Lisboa, PT
suzana.paula.lampreia@marinha.pt; suzanalampreia@gmail.com
António Mário Pereira, – Centre for Rapid and Sustainable Product Development & School of Technology and Management of Polytechnic University of Leiria, PT
mario.pereira@ipleiria.pt