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31st European Safety and Reliability Conference | 19-23 September 2021, Angers, France

Separated by coma

Panel Sessions

  • Model-Based Safety Assessment approach: Increase trust in models


    MILCENT Frédéric, frederic.milcent @ | Naval Group

    [download pdf]


    Model-Based Safety Assessment (MBSA) exists since many years now and the advantages of this approach are well known. However, modelers are sometimes confronted with the same old questions: Is the model really valid? Are the results correct? Those questions often take their origins in a lack of knowledge of the MBSA approach but reveal an important issue: how to prove the validity of models and results?

    The following topics will be addressed:

    1. Modeling process
    2. Training & Communication
    3. Model representativeness
    4. Model-Checking
    5. Tools & Software
    6. Documentation & Capitalization



    The aim of this panel session is to give leads to modelers to prove the validity of their models. An example of modeling process will be proposed. Based on this process, few solutions will be presented:

    • Plan MBSA to define inputs needed, objectives and development specification
    • Model-Based System Engineering (MBSE) / MBSA coupling initiatives (S2C, S2ML…) and others methods to ensure the model representativeness to the corresponding system
    • Model-checking for the verification of the consistency of the model
    • Validation activities (step-by-step simulation…)
    • Provide documentation with model for explanation
    • MBSA supporting activities (training & communication) and resources (database, existing patterns…)
    • Possibilities offered by MBSA tools & languages to assist modelers

    Panel list

    BATTEUX Michel, Michel.Batteux @ | IRT SystemX

    DE BOSSOREILLE Xavier, xavier.debossoreille @ | APSYS AIRBUS

    PROSVIRNOVA Tatiana, Tatiana.Prosvironova @ | ONERA

  • RAM and PHM Synergy


    Dersin, Pierre, pierre.dersin @ | ALSTOM, France, and Luleå University of Technology(LTU), Sweden



    RAM (Reliability-Availability-Maintainability) Engineering is by now a mature discipline, tracing its roots back to the immediate post-World War II period.It deals with statistical properties of a population of assets, characterizestheir failure modes and aims at optimizing the design of future equipment based on past experience, analysis and tests. It takes into account maintenance and operations context and also provides inputs to the elaboration of maintenance plans and logistic support.RAM analysis at the design stage is typicallymodel-based(while exploiting past data), andRAM Monitoring is data-driven but may be supported by models.PHM (Prognostics & Health Management)emerged at the turn of the 21stcentury. It deals typically with individual assets which are equipped withsensors and aims at monitoring their health and its progressivedegradation,so as to diagnose impending failures, and to avoid them by taking preventive actions when possible. Three main pillars of PHM are detection, diagnostics and prognostics.

    PHM relies on model-based, data-driven or hybrid approaches.Typically the two communities are separate for historical reasons.The question we would like to raise here is: can the two communities both benefit from stronger links?For example, the first stage in developing a PHM system is a failure mode, mechanisms and effects analysis(FMMEA), which is typically a RAM task. And one key expected outcome from a PHM strategy is increased availability.While RAM focuses on estimating the probability distribution of the lifetime of a population, in a givenenvironmentwith an average mission profile, PHM, on the other hand, focuses on predicting the rate of function loss for an individual asset, with a customized profile and context. RAM deals with discrete events (failures), and metrics such as failure rate and MTTF or MRL (mean residual life); while PHM deals with continuous, degradation data, and metrics such as health indicators (or indices) and RUL (remaining useful life). While RAM leads to maintenance decisions (such as spares management and determination of maintenance intervals)for a whole fleet, PHM supports maintenance decisions for one individual asset.The ‘M’(maintainability) in RAM includestestability, which addresses the ability todetect and diagnosefaults—an essential concern for PHM.The IoT paves the way for individualized monitoring. Both RAM and PHM can be supported by machine learning techniques along with classical statistics. Therefore the borders between the two disciplines may be getting blurred.Can cross-fertilization occur in both directions ? For instance, can PHM not draw on the considerable body of knowledge accumulated by RAM specialistsover decades (including the venerable theories of the ‘founding fathers’, such as Barlow & Proschan, or Gnedenko, which PHM engineers often are not familiar with).And at the same time, cannotRAM Engineering be rejuvenated by machine learning algorithms and perspectives (which often RAM Engineers do not necessarily have in their toolbox)?Should corporate RAMS departments give way to RAM/PHM departments?And what are the implications for higher education and research ?

    Panel lists

    Kumar, Uday (Prof.),  uday.kumar @ | Luleå University of Technology(LTU), Sweden

    Tinga, Tiedo (Prof.),  t.tinga @ | University of Twente, The Netherlands (TBC)

    Fink, Olga (Prof.), Fink Olga fink @ | ETH-Zürich, Switzerland

    Prof. dr. Marielle Stoelinga,  Professor of risk management for high-tech systems, University of  Twente, The Netherlands.

  • TC12 on risk analysis and safety of large structures and component


    Leksandar Sedmak, | (asedmak @ Faculty of Mechanical Engineering, University of Belgrade, Serbia

    Snežana Kirin | Innovation Center of the Faculty of Mechanical Engineering, Belgrade, Serbia

    Nenad Milošević | Innovation Center of the Faculty of Mechanical Engineering, Belgrade, Serbia



    European Structural Integrity Society (ESIS) is leading association of scientists and researchers who deal with failures, fracture mechanics, structural integrity and related topics like reliability and safety. The ESIS has a number of Technical Committees specialized in different topics, including TC12 on Risk analysis and safety of large structures and component, coordinated by Aleksandar Sedmak & Snežana Kirin, Belgrade, Serbia, José A.F.O. Correia & Abílio M.P. De Jesus, Porto, Portugal and Vladimir Moskvichev & Elena Fedorova, Krasnoyarsk Russia. Ongoing collaborative research covers Fracture Mechanics Applied to the Risk Analysis and Safety of Technical Systems, Degradation Theory of Long Term Operated Materials, Fatigue Evaluation in Offshore and Onshore Structures, Fatigue Analysis in Bridge Structures, Modeling of Offshore Structures, International Symposiaon Risk Analysis and Safety ofComplex Structures and Components, Workshop on Risk based Fracture Mechanics Analysis.

    Recent Projects include:

    1. The European “FASTCOLD -FAtigue STrength of COLD formed structural steel details” aims to develop design fatigue curves of details made of cold-formed profiles.

    2. The National project called “FIBERBRIDGE -Fatigue strengthening and assessment of railway metallic bridges using fiber-reinforced polymers” aims the fatigue strengthening and assessment of railway metallic bridges using fiber-reinforced polymers.

    3. Research projects financed by the Serbian Ministry for Education, Science and Technological Development: Risk analysis in mining industry and New Advances in Fracture Mechanics and Structural Integrity.

    The ESIS TC12 is organized in several working groups: WG1 on Engineering Structures and Technologies, Chairs José António Correia, Grzegorz Lesiuk & Pedro Montenegro, WG2 on Safety of Technical Systems, Chairs Aleksandar Sedmak & Vladimir Moskvichev, WG3 on Reliability and Probabilistic Approaches, Chairs: Miguel Calvente & Shun-Peng Zhu, WG4 on Environmental effect on structural integrity, Chair Elena Federova, and WG5 on Structural integrity of composite materials and structures, Chairs Lothar Kroll & Wojciech Błażejewski


  • Autonomous system safety, risk, and security


    Thieme, Christoph A., christoph.thieme @ | Norwegian University of Science and Technology
    Ramos, Marilia, marilia.ramos @ | University of California Los Angeles
    Utne, Ingrid B., ingrid.b.utne @ | Norwegian University of Science andTechnology
    Mosleh, Ali, mosleh @ | University of California Los Angeles


    This special session will be organized in the format of a panel for discussing autonomous systems safety, risk, and security (SRS). The session will discuss the results of the First International Workshop on Autonomous Systems Safety (IWASS), as well as early findingsof the 2ndIWASS. Key experts will be invited to discuss autonomous systems SRS from an interdisciplinary and cross-industrialperspective. The panelis expected to present the results from IWASSdiscussions and make them more accessible to a wider audience. Participants may present additional thoughts on the discussions and workshop outcomes.


    The First IWASS was organized by the Department of Marine Technology at the Norwegian University of Science and Technology (NTNU) and the B. John Garrick Institute for the Risk Sciences at the University of California, Los Angeles (UCLA). IWASS took place in Trondheim, Norway, from March 11thto 13th,2019. The 47 participants were selected and individuallyinvitedto the workshoponly and included 47. Thesubject matter experts came from Europe, Asia, Australia, and the U.S.A., working in both academia and industry.The 2ndIWASS is planned as a virtual event to be held in April 2021.Autonomous systems on land, in the air and on the sea are being widely applied. Thesafety issues concerning these systems are the focus of many research projects and publications, yet each industry and academic field attempts to solve arising safety issues on their own. Given theidentifiable similarities, could common solutions be envisioned and developed? Answering these and related questions motivatesthis panelas an opportunityfor an interdisciplinary discussion on risks, challenges, and foremost potential solutions concerning safe autonomous systems and operations.

  • COVID-19 pandemic: Risk analytics

    Bracke, Stefan, |  (bracke @,)University of Wuppertal, Chair of Reliability Engineering and Risk Analytics, Gausstrasse 20, 42119 Wuppertal, Germany

    Structure: Two impulse speeches/presentations, discussion actual trends and risk and safety methodologies

    [download pdf]

    Since December 2019, the world is confronted with the COVID-19 pandemic, caused by the Coronavirus SARS-CoV-2. The COVID-19 pandemic with its incredible speed of spread shows the vulnerability of a globalized and networked world. The first months of the pandemic were characterized by heavy burden on health systems and severe restrictions on public life within a lot of countries, like educational system shutdown, public traffic system breakdown or a comprehensive lockdown. The focus of the panel is the discussion of risk and safety analytics regarding the analyse of several control strategies or combinations of them, like restrictions, medical care actions and medical prevention activities.

    The COVID-19 pandemic continues to this day. The impact of the pandemic continues to influence life in various countries around the world. Methods from reliability and safety engineering can help regarding the estimation of risks and can be a fundament for finding proper actions to control the pandemic.

    Panel list
    • Bracke, Stefan;,University of Wuppertal
    • Van Gulijk, Coen;; University of Huddersfield
    • [t.b.c]