Organizers

Pasquale Cito, pasquale.cito @ unina.it (pasquale.cito @ unina.it) | University of Naples Federico II, Department of Structures for engineering and architecture, Italy
Eugenio Chioccarelli, eugenio.chioccarelli @ unirc.it (eugenio.chioccarelli @ unirc.it) | Mediterranea University of Reggio Calabria, Department of Civil, Energy, Environmental and Material Engineering, Italy

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Description

This special session welcomes papers presenting innovative contributions to the reliability assessment of structures and infrastructure, at different scales in terms of time and space, with respect to seismic actions and combined effects of seismic and other triggered hazards (e.g., landslides, explosions, etc.).

Motivation

The quantification of the socio-economic losses due to earthquakes and/or events triggered by seismic events needs a large amount of information that are usually categorized in hazard, vulnerability and exposure models. Consolidated methodologies for seismic reliability assessment are available nowadays, yet recent researches prove the importance of developing models/methodologies able to account for some issues that may affect the results, such as, for example: ground motion characteristics not considered in traditional approaches, time-variability of systems’ exposure and vulnerability (e.g., state-dependent fragility functions), stochastic interaction between multiple hazards or different components at risk.

Objective

This session encourages those works focusing on the following aspects, among the others:
• Spatially correlated ground motions for reliability assessment of building portfolios or infrastructural systems;
• Time-dependent seismic hazard;
• Time-variant structural vulnerability;
• Dynamic exposure;
• Seismic loss assessment;
• Recovery and resilience assessment for structures and infrastructure interested by seismic events;
• Cost benefit analyses to be used in the seismic emergency management;
• Combined effects of earthquakes and other triggered hazards.

Organizers

Dr. Tanguy MORO, tanguy.moro @ irt-jules-verne.fr (tanguy.moro @ irt-jules-verne.fr) |  Institut de Recherche Technologique Jules Verne

Dr. Jean-Marc JUDIC, jean-marc.judic @ faurecia.com (jean-marc.judic @ faurecia.com) | Faurecia Seating

Dr. Pierre BEAUREPAIRE, pierre.beaurepaire @ sigma-clermont.fr (pierre.beaurepaire @ sigma-clermont.fr) | SIGMA Clermont

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Description

In industry, the modelling of product / process assemblies is based on the theory of Geometrical Product Specification – GPS – and Tolerancing Analysis. This industrial approach follows several international ISO GPS standards to specify the parts and build stack-ups models of tolerances of an assembly. The main hypothesis of these standards is the rigid workpiece principle. However, in many cases, for large dimensions thin parts and their assemblies as example, the effects of gravity and of the forces and/or displacements imposed by active tools or other internal forces coming from potentially desired over constraints (hyperstatism), this rigid bodies assumption is not is not relevant : some deformations due to existing forces are higher than parts tolerances. Thus, “classic rigid stack-ups” can lead to non-representative results on functional requirements. Sometime resulting geometry of assemblies can be good, but the problem comes from installed constraints potentially harmful for the reliability (undesired crack during assembly, reduced performance in fatigue...). Sometime, the geometry of a sub assembly seems to be not conform, from GPS conformity point of view, but with no consequence for the assembly at upper level, taking advantage of elasticity. In all of these cases, flexibility is a key factor, helping or disturbing the result, and the key criteria to analyze are often not in mm, but potentially in Newton or N/mm²...

Thus, to take into account the flexibility of the parts and assemblies in the 3D tolerancing stack-ups, some recent academic and industrial works have proposed several methods, coupling the tolerancing theory, the uncertainties propagation methods and FEM simulations. For example, some scientific challenges are: -Geometrical, stochastic and meshing modelling of geometrical characteristics, -Uncertainties propagation in assembly FEM models, -Massive stochastic dimensions of stack-ups models. So flexible tolerancing analysis is close enough structural reliability analysis and some methods are common between the two disciplines.

Motivation

Participants to this special session will gain knowledge about the innovations in the tolerancing domain and the lessons learnt about the practical use of existing tolerancing frameworks. Flexible tolerancing analysis was introduced in the late 2000 to handle the geometry and safety analysis of complex assemblies and to ensure their compliance with the geometrical product / process functional requirements, with non-rigids parts. This transverse discipline is promised also to ease the dialogue between CAD specialists, tolerancing specialists and FEA specialists as well as the active sharing of the hybrid models building, validation and application. Flexible tolerancing is currently applied with different maturity levels in industries. Articles on industrial application could be presented to argue the benefits and limits of these approaches.

Objective

Contributions on the following topics are welcome: -Geometrical, stochastic and meshing modelling of geometrical characteristics of parts, -Stochastic process modelling and simulation, -Uncertainties propagation in assembly FEM models for tolerancing analysis, -Massive stochastic dimensions of stack-ups models, -Tolerancing results and analysis and direct impact on structural reliability and safety analysis, -Illustration of industrial cases where elasticity and internal forces and stress becomes key factors in product performances and variability.

Organizers

Assoc. Prof. Jorge MENDOZA, jorge.mendoza @ hec.ca (jorge.mendoza @ hec.ca) | HEC Montréal

Dr. Hai-Canh VU, hai-canh.vu @ utc.fr (hai-canh.vu @ utc.fr) | Université de Technologie de Compiègne

Dr. Florian DELAVERNHE, florian.delavernhe @ univ-angers.fr (florian.delavernhe @ univ-angers.fr) | Université d’Angers

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Description

In the context of Industry 4.0,industrial systems become more and more complex. They couldbe an integration of many components of different natures with their complex interconnections and dependencies (e.g. cyber-physical systems). This special session focuseson themaintenance decision-making including maintenance modeling and maintenance optimization of such complex systems. The discussion will be also opened to the geographically-distributed systems where the maintenance resource allocation would be a big issue in such context.

Motivation

The maintenance-decision making of the complex systems has to face many challenges due to a large number of components, their interactions, and the allocation of the maintenance resources such as operators in a geographically distributed environment. Advanced maintenance models (predictive maintenance, dynamic grouping/opportunistic/routingmaintenance) and maintenance optimization methods (Metaheuristic optimization) should be developedto overcome all these above challenges.

Objective

This session aims to provide researchers, industrial experts and practitioners the opportunity to present and discuss recent solutions to the above-mentioned issues, as well as to share new perspectives. The topics of interest include, but are not limited to:

• Maintenance strategies for complex systems (Multi-level maintenance decision-making, Dynamic grouping/opportunistic maintenance, Predictive maintenance decision-making etc.)

• Maintenance modeling of complex systems(system modeling, dependence modeling)

• Maintenance operator routing

• Metaheuristic optimizationfor the maintenance decision-making

• Case studies and applications of maintenance-decision making for complex systems

Organizers

Sylwia Werbińska-Wojciechowska, sylwia.werbinska @ pwr.edu.pl (sylwia.werbinska @ pwr.edu.pl) | Wroclaw University of Science and Technology

Mitra Fouladirad, mitra.fouladirad @ utt.fr (mitra.fouladirad @ utt.fr) | University Technology of Troyes

Anne Barros, anne.barros @ centralesupelec.fr (anne.barros @ centralesupelec.fr) | CentraleSupélec / Université Paris-Saclay

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Description

This special session has an objective to share the knowledge in both maintenance and asset management. It is intended to provide a platform for common understanding of the role and value provided by the maintenance function, especially in conditions of significant uncertainty occurrence in modern organizations.

Motivation

In the presence of ongoing global competition and increasing demands from stakeholders, all companies have begun to focus on achieving higher performances, i.e. higher quality of their products/services, lower costs, or sustainability control. To achieve these goals, effective and balanced management of physical assets becomes particularly important. This implies the necessity of proper performance of maintenance tasks, especially in the fields of setting pre-asset acquisition strategies for planning and initiating assets, asset operation and maintenance, performance monitoring, together with allied asset accounting and economics, or audit and renewal analysis.

Objective

This session aims to present the state-of-art of theoretical developments and applications in the area of physical asset management in various industry sectors. The key aspects of this special session
are, among others:
- development of technical systems maintenance in conditions of significant uncertainty,
- assessment of organizations’ maturity in maintenance management,
- promoting research for innovative approaches to decision support systems and multi-criteria decision making methods,
- development of assessment methods and presentation of their implementation,
- development of asset and risk management strategies,
- reliability and risk assessment in maintenance,
- resilience engineering.

Organizers

Barros Anne, anne.barros @ centralesupelec.fr (anne.barros @ centralesupelec.fr) | CentraleSupélec – Paris Saclay University
Fang Yiping, yiping.fang @ centralesupelec.fr (yiping.fang @ centralesupelec.fr) | CentraleSupélec – Paris Saclay University
Zeng Zhiguo, zhiguo.zeng @ centralesupelec.fr (zhiguo.zeng @ centralesupelec.fr) | CentraleSupélec – Paris Saclay University

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Description

Critical infrastructures are more and more highly interdependent, meaning that the services they are supposed to provide are dependent on each other. For example, the availability of a transportation system may depend on the availability of an energy distribution system which may depend on the availability of a telecommunication system. In such a context, risk analysis needs to consider how failures occurring in one given infrastructure affect the other infrastructures performances. Similarly, resilience analysis should focus on the capacity of several interconnect infrastructures to recover from one or more degraded states so that
a global or a specific end-user performance criteria is satisfied.

Motivation

The current state of the art related to risk and resilience analysis for interdependent critical infrastructures is rather poor. Up to now, most of the existing methods are mainly dedicated to one specific type of infrastructure by incorporating the physics, models and functional analysis of the related technical areas (energy distribution, telecom network, transportation systems, etc…). New failure modes and failure propagation due to interdependences between several types of infrastructures are not taken into account, neither their possible mitigation, nor the optimal maintenance strategies to prevent of correct them. In addition, the risk and resilience metrics are often defined at a local level for one given infrastructure and may not highlight properly the different needs of different interconnected infrastructures.

Objective

The objective of the session is to gather academics and researchers from industry to discuss recent advances in modelling techniques related to risk and resilience analysis for interdependent infrastructures. We intend also to highlight challenges and problem statements in risk and resilience analysis coming from industry or activity areas dedicated to critical infrastructures management.

Organizers

Monica Luigi, l.monica @ inail.it (l.monica @ inail.it) | Department of technological innovation and safety of plants, products and anthropic settlements (DIT) of INAIL, Italy
Di Nardo Mario, mario.dinardo @ unina.it (mario.dinardo @ unina.it) | Department of Materials Engineering and Operations Management, University of Naples, "Federico II" Italy

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Description

Humans’ new role needs to be recognized in the highly technological and innovative scenario for Industry 4.0, characterized by a set of enabling technologies and a deep interconnection of resources. In the smart factories, interactions among the socio-technical elements make the organizations more complex even if also easy to be controlled for safety. This session focuses on human factors' role in the new interaction with smart devices and collaborative machines.

Motivation

The increasing development of new technologies that drive innovation and new applications leads to continuously changing workplaces and organization processes, designing a smart worker's new concept in a smart organization.
The new cognitive and physical load work is defined in order to design the new smart industry workplaces and tasks inefficiently and safely way considering the arising needs. Furthermore, the current pandemic condition has provided a reactive boost to working remotely, thanks to digitalization and technology.

Objective

Different theoretical and practical approaches consider the human factor as a critical role in smart society's design. Several studies concerning all the aspects to define and measure the worker’s performance in a more and more complex organization, also focusing on new models about safety and emerging risks, are some topics discussed in this session.

Organizers

BOUILLAUT Laurent, laurent.bouillaut @ univ-eiffel.fr (laurent.bouillaut @ univ-eiffel.fr) | Université Gustave Eiffel, GRETTIA
ANTONI Marc, marc.pierre.antoni @ gmail.com (marc.pierre.antoni @ gmail.com) | UIC

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Description

Reliability analysis and maintenance optimisation has become an integral part of system design and operation. This is especially true for systems performing critical tasks, such as in the railway field.

Motivation

If the optimization of maintenance is a particularly challenging issue in most of industrial fields, this is particularly true in the railway industry since it deals with integrated systems, where all parts can interact. Indeed, a degradation on the track can impact the catenary integrity through changes on the rolling stock dynamic. To address this challenging issue that is optimizing the maintenance of such systems, many studies were done using probabilistic tools… from the use of simple lifetime distributions or of specific stochastic processes to the development of decision support tools based on probabilistic graphical models. But, the railway field is in perpetual evolution, with new availability and operating constraints but also with a new need for economical effectiveness. This is the reason why new research are always needed to optimize maintenance strategies for rail systems.

Objective

The main objective of this session is to provide a forum for participants, both academics and industrials, to discuss new research for the optimisation of railway maintenance.

Organizers

Dr. Mário Coelho, mcoelho @ civil.uminho.pt (mcoelho @ civil.uminho.pt) | University of Minho, Portugal,
Pr. Emilio Bastidas-Arteaga, ebastida @ univ-lr.fr (ebastida @ univ-lr.fr) | La Rochelle Université, France

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Description

In the present special session, the probabilistic vulnerability and lifetime assessment of existing and new infrastructure to interceptable and non interceptable events under various climate change scenarios is addressed. Adaptation of infrastructure to these new climate change related events is also covered in this special session. For example, coastal infrastructure in the Atlantic area is subjected to progressive deterioration (corrosion) and sudden events (floods, extreme winds, etc.) that affect their serviceability and safety. Therefore, considering the uncertainty associated with the occurrence of the natural hazards, the vulnerability of the infrastructures, as well as the ongoing climate change variability and its effect on both hazard and vulnerability, the use of probabilistic tools is of particularly relevance.

Objective

This special session aims at gathering contributions from the research community and industry developing and applying probabilistic tools in the context referred before. The topics include, but are not limited to:

•  Approaches for uncertainty and spatial variability quantification of structural condition and deterioration processes.
• Probabilistic service life prediction (e.g., physical or surrogate models), impact quantification and digital twinning considering climate change and variability effects.
•  Decision-making, mitigation strategies and adaptation of infrastructure systems related to climate hazards.
• Study cases

Organizers

Liang Zheng-Lin, zhenglinliang @ mail.tsinghua.edu.cn (zhenglinliang @ mail.tsinghua.edu.cn) | Department of Industrial Engineering, Tsinghua University
Sun Mu-Xia, muxiasun @ mail.tsinghua.edu.cn (muxiasun @ mail.tsinghua.edu.cn) | Department of Industrial Engineering, Tsinghua University
Coit David, coit @ soe.rutgers.edu (coit @ soe.rutgers.edu) | Department of Industrial & Systems Engineering, Rutgers University
Li Yan-Fu, liyanfu @ tsinghua.edu.cn (liyanfu @ tsinghua.edu.cn) | Department of Industrial Engineering, Tsinghua University

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Description

In reliability engineering, significant advancement has been made for the modelling of complex systems. Amongst them, the challenging issues of stochasticity, heterogeneity, dependency have been effectively addressed. It improves the performance of estimating reliability and optimizing maintenance in systems, such as production line, infrastructure system, and power system, etc. Currently, some networked systems, such as 5G telecommunication system, health care system, should also bring to attention due to their significance and high requirement of reliability. How to effectively estimate their reliability and optimize their maintenance policy for such networked systems are still open questions.

Motivation

With technology development, new systems such as 5G telecommunication, blockchain have become the backbone for supporting contemporary society. Their reliability is often a matter of stability and security for regions. Furthermore, during the pandemic, health care and vaccine distribution system are critical infrastructures to fight against the COVID19, which also has a low tolerance for disruption. Could reliability engineering provide effective solutions for such types of networked systems is a new and important question that to be answered.

Objective

This section aims to invite researchers to share their successful experience and knowledge on the modelling of the reliability and maintenance of practical systems. Innovative approaches to addressing these issues in the context of networked systems, such as the 5G telecommunication system, the health care system, are preferred. A list of related candidate topics includes but not limited to:

• Reliability assessment for telecommunication systems
• Risk analysis for health care systems
• Risk analysis in hierarchical networks
• Modelling of degradation for practical networked systems
• Predictive maintenance for networked systems
• Maintenance optimization for networks

Organizers

Umberto Alibrandi, umbertoalibrandi @ eng.au.dk (umbertoalibrandi @ eng.au.dk) | Aarhus University

Paolo Gardoni, gardoni @ illinois.edu (gardoni @ illinois.edu) | University of Illinois at Urbana Champaigne

Khalid M. Mosalam, mosalam @ berkeley.edu (mosalam @ berkeley.edu) | University of California at Berkeley

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Description

Urban resiliencehas conventionally been defined as the ”measurable ability ofany urban community to maintain continuity through all shocks and stresses,while positivelyadapting and transformingtowardsurban sustainability. Totarget sustainable growth models of the urban communities and green transitionparadigms, city governments are relying more and more on digital technologies.Novels tools, methods and frameworks of data-driven uncertainty quantificationand risk-analysis are going to be developed and implemented to this aim.

Motivation

The Digital Twin (DT) is a virtual replica of buildings, processes, structures,people, systems created and maintained in order to answer questions about itsphysical part, the Physical Twin (PT). Multiple sources of uncertainty duringthe lifecycle challenge our prediction capabilites. It follows the significance ofthe Risk-Informed Digital Twin (RDT) for urban resilience and sustainability,uncertainty quantification, random vibrations, risk analysis, decision makingunder uncertainty, network theory, machine learning and computer science arefully integrated.

Objective

This special sessions aims at presenting state-of-the-art and new algorithms andtools of data-driven uncertainty quantification and risk analysis, including noveldesign concepts and methodologies related to the broad area of risk-informeddigital twins for the built environment. Practical applications and real worldexamples are encouraged. The contributions of this special session are expectedto lay the foundations of a novel paradigm of Sustainable and Resilient BasedEngineering (SRBE).

Organizers

Brînzei Nicolae, nicolae.brinzei @ univ-lorraine.fr (nicolae.brinzei @ univ-lorraine.fr) | University of Lorraine

Andrews John, john.andrews @ nottingham.ac.uk (john.andrews @ nottingham.ac.uk) | University of Nottingham

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Description

This special session welcomes papers that address the application of different kinds of Petri net (stochastic, with predicates and assertions, coloured, high level...) for modelling, analyse and probabilistic assessment of systems reliability and safety and maintenance decision-making. Both recent developments on Petri nets (PN) and their applications will be considered.

Motivation

In system engineering, the analysis and probabilistic assessment of reliability, safety and maintenance policies are important issues due to the increasing complexity of current systems characterized by grow and large interactions between their components and with their environment. Moreover, the reinforcement of digital integration leads to more failure detection capabilities, and although digital components are more reliable than the analogue components they replace, some characteristics raise specific issues on the modelling and assessment of systems and further increase the complexity of their analysis and assessment. Petri nets have proven to be a powerful tool to take into account the behaviour of complex dynamic systems. Petri nets are able to develop flexible models for components and the whole system allowing a qualitative analysis (by means of analysing the model properties such as reachability of specific safety or dangerous states, liveness or blocking, ...) or quantitative assessment (by means of exact resolution of stochastic processes underlying a PN model or by Monte-Carlo simulation).

Objective

The main aim of this special session is to promote and disseminate recent research works on Petri nets and their variants to meet challenges of both academia and industry.

Organizers

Bonato Marco, marco.bonato @ valeo.com (marco.bonato @ valeo.com) | Valeo Thermal Systems France

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Description

The special session aims to present hands-on case studies illustrating modern methods and tools employedto perform reliabilitypredictions within theindustrial environment.Main topics of the session would include:
- Statistics analysis of final users (usersmission profiling)
- Strategies for extended warranty period
- Development of more representative accelerated validation tests
- Life data analysis of accelerated life tests
- Pitfalls of product validation (during planning, execution and analysis of accelerated life tests)
- Digitalized product validation
- Data Science applied to predictive reliability.

Motivation

The digital transformation of manufacturing and production is rapidly shaping modern industry, with some sectors particularly exposed(energy, aerospace, transportation). From a reliability perspective, new challenges are faced also for every-day use products (from smartphones to electrical cars): from the one hand highly reliable products are inprogressive demand among end-users; on the other hand the emergence of highly competitive worldwide markets results in tight profit margins, while extended warranty periods impose more severe validation specifications. In the framework, the importance of reliability predictions during early design phases and throughout the life cycle is a key part of product validation and risk assessment. Modern industry has to adapt to this new scenario, and be able to effectively deploy state of the art methods and tools to perform such predictions.

Objective

This special session is dedicated to foster discussion over the state of theart of reliability predictions (methods, tools, models, best practice and lesson learnt) commonly performed on the industry. The objective is to gather applied case studies of such predictions performed by all industrial actors: product manufacturers, tier 1 suppliers, software suppliers, consulting firms, etc.

Organizers

Ramos, Marilia, marilia.ramos @ ucla.edu (marilia.ramos @ ucla.edu)   | University of California Los Angeles

Thieme, Christoph A., christoph.thieme @ ntnu.no (christoph.thieme @ ntnu.no) | Norwegian University of Science and Technology

Utne, Ingrid B., ingrid.b.utne @ ntnu.no (ingrid.b.utne @ ntnu.no) | Norwegian University of Science and Technology

Mosleh, Ali, mosleh @ ucla.edu (mosleh @ ucla.edu) | University of California Los Angeles

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Description

Papers submitted to this special session should discuss advancements on autonomous systems under the perspective of safety, risk, and reliability (SRS). Papers addressing the following topics either conceptually or through applications are welcomed:
● Risk and safety assessment methods
● Safety and security co-analysis
● Validation and verification
● Intelligent, risk aware systems
● Human Reliability and human on the loop
● Ethical design and operation
● Legal and regulatory aspects of safe operation

Motivation

Autonomous systems are emerging and are crucial for enabling new operations, such as autonomous land-based, maritime, and air transportation, mapping and monitoring of oceans and areas on land, and inspections of physical structures that are difficult to access. Autonomous technologies are intended to be a step towards safer and more efficient operations. However, the complexities concerning software and advanced control, human-software-hardware interaction, and emerging failures, pose formidable challenges to identification and removal of cause of functional failure, safety issues, and security concerns.
Recent accidents have put emphasis on the need to discuss the safety aspect of these systems. The development of safe solutions for autonomous systems are, more than ever, crucial for their use. In particular, it is essential to:
• Recognize, understand and assess the risks involved with autonomous systems operations;
• Implement safe solutions in the design phase of these systems;
• Monitor, follow-up, and ensure that the risk level is acceptable during operation;
• Establish regulations and procedures that assure safe operations;
• Communicate safety to society in order to establish trust in autonomous systems.

Objective

The object of this special session is to map out challenges and propose solutions with respect to autonomous systems SRS. This special session shall contribute to recognizing cross-industrial and interdisciplinary synergies to address these challenges and develop such solutions.

Organizers

Dr. Khanh T.P. NGUYEN, tnguyen @ enit.fr (tnguyen @ enit.fr) | INPT-ENIT, University of Toulouse, France.
Dr. Zeina AlMASRY, zeina.al.masry @ ens2m.fr (zeina.al.masry @ ens2m.fr) | FEMTO-ST, École Nationale Supérieure de Mécanique et des Microtechniques, France.
Dr. Raymond HOUENGOUNA, raymond.houe-ngouna @ enit.fr (raymond.houe-ngouna @ enit.fr) | INPT-ENIT, University of Toulouse, France.
Prof. Kamal MEDJAHER, kamal.medjaher @ enit.fr (kamal.medjaher @ enit.fr) | INPT-ENIT, University of Toulouse, France.
Prof. Noureddine ZERHOUNI, noureddine.zerhouni @ ens2m.fr (noureddine.zerhouni @ ens2m.fr) | FEMTO-ST, École Nationale Supérieure de Mécanique et des Microtechniques, France.

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Description

Nowadays, the fourth industrial revolution is making systems more intelligent and ultra-connected day by day. This requires the availability and reliability of production systems as well as the safety of the working environment. One of the levers to achieving these goals is to develop adapted methods, algorithms, and tools that monitor systems to early detect abnormal operating modes, diagnose probable causes, anticipate failures and take appropriate decisions accordingly. These tasks a reconducted in the framework of Prognostics and Health Management (PHM), which allows the development of predictive maintenance strategies to improve systems health states while reducing their maintenance and operating costs.

Motivation

In the context of Industry 4.0, the important growing of intelligent and efficient ultra-connected systems poses many challenges for fault detection, diagnostic, prognostics, and maintenance functionalities. Indeed, complex system structures and behaviors need to be studied, analyzed and modeled in a thoughtful and intelligent way. The use of multiple heterogeneous sensor sources requires new powerful methods for acquisition, storage, fusion, and online computing of monitoring data. The prediction of remaining useful lifetime of these complex systems requires effective methods and algorithms for handling multiple sources of uncertainties, such as processes, models, measurements and future operating conditions. The merging of digital and physical worlds leads to an increasing number of options to weigh in the optimization of the entire production and maintenance strategy. To achieve these goals with high accuracy, machine learning techniques are becoming complex and less meaningful tohumans (especially decision-makers). Explainability therefore appears as a mainstream topic to address in PHM community.

Objective

This session aims to provide researchers, industrial experts and practitioners the opportunity to present and discuss recent solutions to theabove-mentioned issues, as well as to share new perspectives. The topics of interest include, but are not limited to:

• Data acquisition, data processing, data fusion and related issues.
• Data-driven, model-based and hybrid fault detection, diagnostics and prognostics.
• Uncertainty quantification and remaining useful life bounds for online decision-making.
• Explainable Artificial Intelligence for Prognostics and Health Management.
• Decision support for condition-based and predictive maintenance.
• Case studies on Prognostics and Health Management

Organizers

Rasa Remenyte-Prescott, r.remenyte-prescott @ nottingham.ac.uk (r.remenyte-prescott @ nottingham.ac.uk) | University of Nottingham, UK, Lead of ESReDA PG on Resilience Engineering and Modelling of Networked Infrastructure
Giovanni Sansavini, sansavig @ ethz.ch (sansavig @ ethz.ch) | ETH Zurich, Chair of the ESRA Technical Committee on Critical Infrastructure

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Description

This special session will focus on highlighting and disseminating current state-of-the-art methods and their practical applications in resilience engineering of critical infrastructures. We expect to have contributions for this special session jointly supported by the membership of ESReDA Project Group on Resilience Engineering and Modelling of Networked Infrastructure and by the members of the ESRA Technical committee on Critical Infrastructure.

Motivation

We believe that this topic is important to the field of safety and reliability assessment. Our modern society is dependent on many critical infrastructure systems. These include transport networks (rail, metro, highway, air traffic and shipping routes), utilities (electricity, gas, water) and communications (mobile phone, land line phones, internet). The disruption of such systems can have a big impact on the communities that they serve. The nature of the threats to these systems is also changing and includes failures, especially of aging infrastructure, natural disasters, the effects of climate change and deliberate acts such as terrorism. Such critical systems need to be resilient and there is a need for knowledge and skills of how to model and assess resilience of such systems.

Objective

To promote and disseminate the current state-of-the-art methods and their applications for improving resilience of critical infrastructures.

Organizers

Yiliu Liu, yiliu.liu @ ntnu.no (yiliu.liu @ ntnu.no) | Norwegian University of Science and Technology NTNU
Baoping Cai, caibaoping @ upc.edu.cn (caibaoping @ upc.edu.cn) | China University of Petroleum (East China)

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Description

The recent advances in digitalization have paved the way to more efficient approaches for operations in different industries. Digital twins are regarded as the key to digital transformation, where a twin is not only a visualization of physical asset, but a common set of data and information can be shared across departments throughout the operations lifecycles of the asset. The digital twin approach is expected to be effective to monitor and estimate the performance of physical systems, and provide clues to the real-time decision-making on system operations.

Motivation

The digital twin approach is playing an active role in engineering fields, but to date, a gap is still existing between digital twin and most analyses and implementations with the purpose of advising on maintenance strategies and risk controlling measures for accident prevention.

Objective

The special session is proposed to share new algorithms, twinning methods and philosophies to integrate the considerations of production and maintenance, data collection, processing and maintenance-related decision-makings, risk issues and risk reduction measures into the digital twin approach, so as to increase system availability and productivity, and prevent accidents in a more cost-effective way.

Organizers

Kammouh Omar, o.kammouh @ tudelft.nl (o.kammouh @ tudelft.nl) | Delft University of Technology
Nogal Maria, m.nogal @ tudeflt.nl (m.nogal @ tudeflt.nl) | Delft University of Technology
Adey Bryan T., adey @ ibi.baug.ethz.ch (adey @ ibi.baug.ethz.ch) | ETH Zurich

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Description

This special session calls for research works proposing quantifiable approaches to support practitioners in their decision-making process using realistic cases and/or scenarios. Such cases/scenarios should be characterized by the uncertainty of future disturbances (e.g., hazards), the high interdependency among the interconnected systems, and the existence of monetary-based decisions-making, which might conflict with other requirements, such as societal and political interests.

Motivation

Resilience assessment of engineering systems has attracted much attention from researchers in the last decade. Nevertheless, practitioners are still struggling to figure out how the tools and methods developed in the context of engineering resilience can be utilized in their daily activities and strategic plans to achieve structures and infrastructure that are proven to be resilient.

Objective

Analytical instruments designed to inform and prioritize actions and investments in competitive contexts, real and realistic case studies discussing mitigation plans and strategies, and value for money assessments of programs that aim at boosting the resilience of engineering systems are examples of the topics that this session will support.

Organizers

Dersin Pierre, pierre.dersin @ alstomgroup.com (pierre.dersin @ alstomgroup.com) & pierre.dersin @ ltu.se (pierre.dersin @ ltu.se) | ALSTOM and Luleå Technology University (LTU)
Fink Olga, fink @ ibi.baug@ethz.ch (fink @ ibi.baug@ethz.ch) | ETH-Zürich
Bérenguer Christophe, Christophe.Berenguer @ Grenoble-inp.fr (Christophe.Berenguer @ Grenoble-inp.fr) | Univ. Grenoble Alpes – Grenoble INP

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Description

This special session will offer a place for discussions and exchanges on how artificial intelligence approaches and techniques can be leveraged in order to operate complex systems in a safe, dependable and secure way. It will also include corresponding challenges to both industry and academia

Motivation

Increasingly connected societies and ever-more highly interdependent complex systems raise challenges in many different areas: industry 4.0, multi-modal transportation, telecommunications, energy generation, transmission and distribution, and much more.
As complexity increases (to the point of leading sometimes to “systems of systems”), at the same time the requirements which those systems have to meet are ever more stringent, as new threats must be confronted in addition to managing traditional risks.
In the new environment, cyber-attack threats need to be anticipated, detected and countered; at the same time, man-made and natural hazards must be coped with; and systems need to be operated and managed efficiently to achieve very high dependability at reasonable life-cycle costs.
To meet those sometimes conflicting goals, a holistic vision of operation and maintenance is in order. Decisions must be made at different levels and on different time horizons with all of the above objectives in mind.
Addressing that problem leads to highly distributed dynamic decision making under uncertainty, dealing with nonlinear feedback loops at several levels. Traditional approaches usually fail to rise fully to these challenges, and this is where AI may help, by leveraging the significant progress made recently in techniques such as deep learning, deep reinforcement learning, transfer learning, physics-informed machine learning, geometric learning and more.

Objective

This session proposal aims at opening a session to address these emerging issues related to the use of AI approaches for safe, dependable and secure operation of complex system. Gathering both researchers and practitioners, theoretical advances, new developments as well as opened issues related to AI approaches for complex systems operations, including the maintenance and asset management aspects, will be addressed in the framework of this special session.