ENBIS Spring Meeting 2026
Granada, Spain
Welcome to the ENBIS Spring Meeting
Granada, Spain, May 28-29, 2026
Reliability, maintenance and safety in the data-driven era
In a context of increasing system complexity, digital transformation, and growing societal demands for safety, resilience, vulnerability reduction, and sustainability, the field of reliability and maintenance engineering is undergoing a profound evolution. This year’s Spring Meeting aims to serve as a cross-disciplinary platform for researchers, practitioners, and industry experts to exchange cutting-edge developments and strategic insights. At its core, the meeting focuses on how data, models, and algorithms can transform the design, monitoring, and maintenance of engineering systems, both in theory and in practice. We welcome both contributions that advance traditional maintenance and reliability models and those that push boundaries using AI-based methods to support smarter and more adaptive systems.
Beyond technical depth, the conference will encourage discussions on strategic challenges and opportunities in the field, including the deployment of digital twins, integration of AI into safety-critical systems, and the incorporation of sustainability into reliability-centered maintenance planning. The goal of this Spring Meeting is to facilitate a dynamic exchange of ideas that promotes scientific advancement and its effective translation into practical solutions, fostering meaningful collaboration with industry and society in the reliability and maintenance field.
Topics of interest include, but are not limited to:
- Data-driven reliability and maintenance.
- Stochastic processes for reliability and failure modelling.
- Condition monitoring, diagnostics, and prognostics.
- Predictive maintenance and digital twins.
- Machine learning and neural networks in reliability engineering.
- Structural health monitoring and sensor system design.
- Uncertainty and sensitivity analysis for safety evaluation of critical structures.
- Value of information analysis for improved decision-making in structural safety.
- Resilience engineering and infrastructure systems management.
- Sustainable maintenance.
- Bayesian methods in reliability and maintenance modelling.
- Partially Observable Markov Processes for Condition-Based Maintenance.
- Deep Learning for Remaining Useful Life (RUL) Prediction.
- Hybrid AI-Statistical Models for Fault Diagnosis.
- Reliability and Maintenance Strategies for Industry 5.0.
Organizing committee
María Luz Gámiz, University of Granada, Spain (Chair)
Juan Eloy Ruiz Castro, University of Granada, Spain
Rocío Raya Miranda, University of Granada, Spain
Fernando Navas Gómez, University of Granada, Spain
Delia Montoro Cazorla, University of Jaen, Spain
Nuria Caballé Cervigón, Complutense University of Madrid, Spain
Lucía Bautista Bárcena, University of Extremadura, Spain
Scientific program committee
Inma T. Castro, University of Extremadura, Spain (Chair)
Mari Carmen Segovia García,University of Granada, Spain
Rosa Elvira Lillo Rodríguez, Carlos III University of Madrid, Spain
Massimiliano Giorgio, University of Naples Federico II, Italy
Jacqueline Asscher, Kinneret College, Technion, Israel
Nikolaus Haselgruber, CIS consulting in industrial statistics GmbH, Austria
ENBIS Spring Meeting 2026 Highlights
Special Session:
This special session highlights how cutting-edge reliability engineering and maintenance technology enables safe, reliable operation of fusion facilities and other Big Science installations. These assets include first-in-the-world prototypes that operate under vacuum, cryogenics, high magnetic fields and radiation, while needing high availability and strong safety margins. Unexpected downtime severely impacts costs and availability, components have long procurement times, and most operations require remote handling, making reliability, maintainability, inspection planning and logistics inseparable from design and operation.
By bringing together top voices from fusion industry, major Big science installations and academia, the session aims to build a shared roadmap—priority areas, benchmark problems, transferable methods, data standards, and collaboration opportunities—that accelerates learning and knowledge cross-pollination. Participants will leave with concrete lessons learnt from industry, new research questions to tackle jointly, and collaboration opportunities to help scaling fusion technology and Big Science operations for tomorrow.
- Hear first-hand case studies from leading fusion and Big Science organisations on how they manage reliability, maintainability and safety at real scale.
- Learn what data is actually available (and missing), which methods work in practice, and how to make GenAI and digital-twin approaches auditable for safety-critical use.
- Network with statisticians, engineers and decision-makers, identify collaboration opportunities, and help shape a shared research and benchmarking agenda.
Session Organizers:
Prof. Juan Chiachio | Email: jchiachio@ugr.es
Department of Structural Mechanics & Hydraulic Engineering
Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI)
University of Granada, Spain
Prof. Manuel Chiachio | Email: mchiachio@ugr.es
Department of Structural Mechanics & Hydraulic Engineering
Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI)
University of Granada, Spain
Plenary speakers
Professor Nikolaos Limnios (Université de Technologie de Compiègne, SorbonneUniversity Alliance (France))
Nikolaos Limnios, is an Emeritus Professor (Exceptional class Full Professor) at University of Technology of Compiègne (UTC) Sorbonne University, and former Director of the Laboratory of Applied Mathematics. He has obtained his diploma in 1979 at AUTh Greece, PhD in 1983, and Dr of Sciences (Doctoratd'Etat) in 1991 at UTC France. In 1988 he was appointed assistant professor (Maitre de conferences), and in 1993 a Professor at UTC in the Laboratory of Applied Mathematics. His research interest include stochastic processes and statistics with applications in biostatistics, in reliability/maintenance, statistical seismology, stochastic mechanics, etc. He is the Editor-in-Chief of book series “Mathematics and Statistics” in iSTE with J. Wiley. He has published more than 150 journal papers and about 15 books on theory and applications of stochastic processes and statistics; including the books: Semi-Markov chains and hidden semi-Markov Chains toward applications, Springer, 2008 (with V. S. Barbu); Stochastic Systems in Merging Phase Space, World Scientific, 2005 (with V. S. Koroliuk); Semi-Markov Processes and Reliability, Birkhauser, 2001 (with G. Oprisan).
Anne Barros, PHD, is professor in reliability and maintenance modelling at Ecole CentraleSupélec, University of Paris-Saclay, France. Her research focus is on resilience analytics, degradation modelling, prognostics, condition based and predictive maintenance. She got a PHD then a professorship position at University of Technology of Troyes, France (2003-2014) and spent five years as a full-time professor at NTNU, Norway (2014-2019). She is currently heading the research department of Industrial Engineering and the Chair of Risk and Resilience of Complex Systems (in the Risk Resilience and Reliability – R3 Group "http://r3.centralesupelec.fr/") with the ambition to improve resilience assessment and maintenance modelling methods for complex systems.
ENBIS Next-Gen Session
As part of the ENBIS Spring Meeting, a special session for PhD students (ENBIS Next-Gen Session) will be organized. This session will be an excellent opportunity for doctoral students to
- Present the current progress of their PhD research
- Share ideas and challenges with peers
- Receive feedback from senior researchers in this area
Application submission deadline: March 6.
PhD students interested in participating in this session should:
- Submit their abstract via the conference website
- Send an email to the session organizer, Antonio Piscopo, including a short CV.
Special Issue:
delegates will be invited to submit papers to a Special Issue in
Venue
IMAG – Instituto de Matemáticas de la Universidad de Granada
Rector López Argüeta Street
18071 Granada, Spain
https://wpd.ugr.es/~imag/
Contact information
For any question about the meeting venue and scientific programme, registration and paper submission, feel free to contact: Inma Torres and Maria Luz Gamiz.