Maintenance, Modelling and Applications session

Human Factors and Human Reliability I

This workshop will provide a platform for risk, reliability, safety researchers and industry professionals to present and discuss the latest developments in modelling and analysis of energy transition risks. The focus will be on how these models and analysis can be used to inform decision making to manage the risk of failure of new energy solutions meeting the energy demand and thus comprising the energy transition to zero-carbon. The following topics are discussed: New Energy Carriers; Renewable and New Technologies; Climate Change Effects and Extreme Weather Conditions

This session presents papers that discuss reviews of accident investigations and accident modelling studies.

Maintenance and Modelling and applications II.

Human Factors and Human Reliability II

The aim of this Special Session is to provide an opportunity for the researchers to share and exchange their knowledge and experience on fields relevant risk and resilience assessment of critical infrastructures while accounting for climate change. Related topics are listed as, but not limited to: 1)  Natural hazards modelling as stressors for critical infrastructures; 2) Spatial/temporal modelling and simulation of extreme climate events; 3) Climate change and their impact on critical infrastructure networks resilience; 4) Climate adaptation; 4) Natural hazards risk and susceptibility maps; 5) Extreme spatial hazards and risk of disruptions of multiple infrastructure systems; 6) System-of-system approach to risk and resilience assessment of interdependent critical infrastructure networks; 7) Cascading failures.

Human Factors and Human Reliability III

Human Factors and Human Reliability IV

This session focuses on the challenges facing Arctic organisations, companies and communities that threaten their ability to be resilient to potentially disastrous events. The purpose of this special session is to present ongoing research on the impact of these hazards and to discuss the conceptual implication the findings have for social systems’ future mitigation and adaptation. During the discussions, we will explore conceptual commonalities across the different cases and present subjects of further research and collaboration.

Prognostics and Systems Health Management I

The goal of this special session is to explore the relation between the resilience of an Industrial Plant and the human factors in a socio-technical setting. Deepening the resilience analysis is strongly linked to human factors, control theory and safety engineering, not excluding the integration with the new Industry era. Precisely from this consideration arises the need to understand how people can adapt to an environment full of dangers and pitfalls and, in other words, how people who are part of a system can present “resilient characteristics. ”, Such as modifying the very Resilience of the system with the new technologies. The result that will be presented will describe how the whole industrial system and the human factor are connected to Resilience.

This special session aims to bring together experts from academia and industry on digital twinning in order to address the following challenges:

• Computational cost (and stability in fact) to propagate uncertainty through a high-fidelity simulation: intrusive vs non-intrusive approaches.
• Quantify the uncertainty in the simulation and model: how twin is the twin?
• How to assimilate data from different sources and different quality and different representations into the model?
• How to control the different fidelity levels of the digital twin in different tasks or analyses?

Prognostics and Systems Health Management II

Human Factors and Human Reliability V

The objective of this session is to discuss advances in Nuclear safety research. Topics discusses involve risk modelling, assessment and management.

Prognostics and Systems Health Management III

S.25: Human Dependability & Automation for Robotic, Intelligent and Autonomous systems

 The aim is to promote a discussion between academic research and industrial about state-of-the-art solutions proposed in the field of standardization of safety related topics with a preference to topics covered by Machine Directive (2006/42/EC). We intend to test best the practice with examples of theoretical models (probabilistic) and empirical data (relative frequencies) related to safety and risk analysis in standardization. We also welcome comparisons between different standardization paradigms with clear examples to support the discussions.

 The possibilities of generating and using digital twins using advanced technologies (AI, immersive technologies, sensor technology) will be considered in the special session.  To this aim, novel and innovative approaches from interdisciplinary research will be brought together and the diverse application and linkage possibilities of a digital twin in critical infrastructures from different disciplines (traffic road construction, energy systems, hospital systems) will be demonstrated.

S.14: Next Generation Methodologies for System Safety Analysis

Prognostics and Systems Health Management IV

The topics covered in this session should be at the intersections of the followings:

• Modelling the dynamics of system behaviours for the production processes, IoT systems, and critical infrastructures (System Safety Engineering)
• Designing and implementing processes capable of monitoring interactions between automated systems and the humans destined to use them (Human Factors/ Neuroergonomics)
• Using data analytics and AI to create novel human-in-the-loop automation paradigms to support decision making and/or anticipate critical scenarios
• Managing the Legal and Ethical implications in the use of physiology-recording wearable sensors and human performance data in AI algorithms.

The special session will focus on contributions made towards addressing scarcity in data (inputs and/or targets) including scenarios where inputs and/or labels are scarce (or not available at all), or are not sufficiently representative of all operating conditions of the system. Specifically, the following approaches for building ML models for risk and reliability assessment in the low data-regime will be considered:

• Reliability of machine learning models built from digital twins
• Physics-informed machine learning
• Uncertainty quantification of deep learning models (Bayesian models, ensemble methods, and others)
• ML approaches to handle scarcity in input and target data, and poor representativeness of training data (active learning, semi-supervised learning, unsupervised learning, generative modelling, data augmentation, and others).

Prognostics and Systems Health Management V

The topics covered in this session should be at the intersections of the followings:

• Modelling the dynamics of system behaviours for the production processes, IoT systems, and critical infrastructures (System Safety Engineering)
• Designing and implementing processes capable of monitoring interactions between automated systems and the humans destined to use them (Human Factors/ Neuroergonomics)
• Using data analytics and AI to create novel human-in-the-loop automation paradigms to support decision making and/or anticipate critical scenarios
• Managing the Legal and Ethical implications in the use of physiology-recording wearable sensors and human performance data in AI algorithms.

This session discusses risk and risk modelling issues in the Chemical and Process industries.

Digital twins – in short, digital replicas of physical objects, can be an enabling technology for hybrid PHM in industry, by continually updating physical models as new data is acquired. The objective of the session is to make this statement more precise by showcasing examples of successes and presenting remaining challenges.

We expect this special session to result in coherent and focused contributions on the topic of hybrid PHM driven by Digital Twins. By carefully selecting complementary contributions from academia and industry, we expect this special session will be a forum to exchange knowledge between these two worlds.