The International Workshop RECI 2022

The Second International Workshop on Reliability Engineering and Computational Intelligence

13 - 15 November 2022, Delft, The Netherlands

Excellent papers for the 1st RECI workshop demonstrated strong synergy between Reliability Engineering and Computational Intelligence but scientific differences remain. The second RECI workshop attempts to address further integration by a) presenting papers on RECI topics, b) panel discussions about future RECI research and c) a curriculum discussion for an international RECI curriculum. The workshop is organized by University of Žilina, TNO, Delft University of Technology and the University of Huddersfield. Call for papers can be downloaded here.

The workshop will be supported by the following projects:

Advanced Centre for PhD Students and Young Researchers in Informatics (ACeSYRI) (Project EACEA.CBHE no.: 610166-EPP-1-2019-1-SK-EPPKA2-CBHE-JP supported by the European Union's Erasmus+ programme)
New Methods Development for Reliability Analysis of Complex System (Project APVV-18-0027 supported by the Slovak Research and Development Agency)
Safety Enterprise Architecture (TNO project 060.51672/01.03: Occupational Safety Innovation/Huddersfield)

Participation

The workshop RECI 2022 will be a hybrid event: we facilitate contributions in-person and online from Delft University of Technology. The organizers believe that the 55 Euro fee for in-person should not be prohibitive for in-person participation. On-line participation will be free of charge. TUDelft hosts the event at the event location ‘X’ on Mekelweg 8, 2628 CD, Delft, the Netherlands

The special section “Reliability Engineering and Computational Intelligence application in healthcare” will be organized under the workshop. The goal of this section is discussion relevant topics and trends of reliability engineering, data mining, and machine learning in healthcare, medicine, and biotechnologies. The possible topics of this section will be but not limited are:

Biomedical engineering
Innovative eHealth, Precision medicine, Applications and Products
Electronic Health Records and Medical Databases
Medical Image Analysis and Biomedical Visualization
Computer-Aided Diagnosis
Telemedicine, Telehealth and Remote Monitoring
Education in eHealth and Telemedicine
Legal, Social, Ethical and Financial Aspects

The section organization is supported by the project “University-Industry Educational Centre in Advanced Biomedical and Medical Informatics” (612462-EPP-1-2019-1-SK-EPPKA2-KA)

The workshop is a post-project activity of the project “Development of methods of healthcare system risk and reliability evaluation under coronavirus outbreak”. This project APVV PP-COVID-20-0013 has been supported by the Slovak Research and Development Agency in years 2020 and 2021.

Publication

The abstracts of the presentations will be published in the book of abstracts, which will be available on the website of the workshop. Also, authors of all presentations will be able to publish their own research as papers in the journal CERES.

Authors of the selected presentations will be invited to prepare contributions to the book “Reliability Engineering and Computational Intelligence” (working title), which will be published by Springer in a series of Studies in Computational Intelligence.

The presented contributions at the workshop RECI 2020 after review by the program committee were published in the book "Reliability Engineering and Computational Intelligence"

Important Dates

Abstract submission (extended)

4 November 2022

Registration

7 November 2022

Workshop dates

13-15 November 2022

Notification of acceptance for publication

10 January 2023

Camera ready format submission

25 January 2023

Call for papers

Program

Join RECI 2022 online

Topics

The workshop develops RECI as a research domain by calling papers on current research. Topics of interest include, but are not limited to:

Mathematical and computational methods for risk analysis
Computational intelligence for risk estimation
Digital technologies for reliability engineering
Software solutions for testing fault-tolerant systems
Data mining and Knowledge discovery
Methods based on Artificial Intelligence
Accident and incident investigation
Human reliability analysis
Risk and hazard analysis
Software reliability
Hardware and software solutions
Education and e-learning
Trends in RECI

Submission of Contributions

The presentation title, authors, their affiliations, and abstract should be sent to the easychair web-page. The abstract template (.docx format) can be downloaded here.

Registration

Please enlist as a participant through the registration form by November 7, 2022. If your contribution is aimed to the RECI workshop, please select “Attendance Type: RECI”. If you participate as a member of the ACESYRI project, please select “Attendance Type: ACESYRI”. If you are travelling to Delft to attend in person, please make that clear in the submission and send also an e-mail to: c.vangulijk@hud.ac.uk to confirm your presence in Delft.

Program Committee

General Chair

Pieter van Gelder, Delft University of Technology, Netherlands

Chairs

Coen van Gulijk, TNO, Netherlands
Miroslav Kvassay, University of Zilina, Slovakia

Members

Olga Aneziris, National Center for Scientific Research "DEMOKRITOS", Greece
Christophe Berenguer, Grenoble Institute of Technology, France
Stefan Bracke, University of Wuppertal, Germany
Nicolae Brinzei, University of Lorraine, France
Radim Bris, VSB Technical University of Ostrava, Czechia
Aleksandr Cariow, West Pomeranian University of Technology, Poland
Marko Cepin, University of Ljubljana, Slovenia
Frank Coolen, Durham University, United Kingdom
Stanislaw Czapp, Gdansk University of Technology, Poland
Darya Filatova, Ecole Pratique des Hautes Etudes, France
Petr Fišer, Czech Technical University in Prague, Czechia
Roger Flage, University of Stavanger, Norway
Jillian Hamilton, Manage Damage, Australia
Tetiana Hovorushchenko, Khmelnitsky National University, Ukraine
Ivan Izonin, Lviv Polytechnic National University, Ukraine
Vyacheslav Kharchenko, National Aerospace University KhAI, Ukraine
Krzysztof Kołowrocki, Gdynia Maritime University, Poland
Jozef Kostolny, University of Zilina, Slovakia
Andriy Kovalenko, Kharkiv National University of Radio Electronics, Ukraine
Vitaly Levashenko, University of Zilina, Slovakia
Martin Lukac, Nazarbayev University, Republic of Kazakhstan
Andriy Luntovskyy, BA Dresden University of Cooperative Education, Germany
Francesco Di Maio, Politecnico di Milano, Italy
Marcio Das Chagas Moura, Federal University of Pernambuco, Brazil
Mirko Navara, Czech Technical University in Prague, Czechia
Charles El Nouty, Université Sorbonne Paris Nord, France
Luca Podofillini, Paul Scherrer Institute, Switzerland
Antoine Rauzy, Norwegian University of Science and Technology, Norway
Olivier Salvi, INERIS Développement, France
Sergey Stankevich, Scientific Centre for Aerospace Research of the Earth, Ukraine
Janos Sztrik, University of Debrecen, Hungary
Min Xie, City University of Hong Kong, Hong Kong
Ming Yang, Delft University of Technology, Netherlands
Elena Zaitseva, University of Zilina, Slovakia
Enrico Zio, Politecnico di Milano, Italy

Organizing Committee

Chair: Patrik Rusnak, University of Zilina, Slovakia
Michal Mrena, University of Zilina, Slovakia
Jan Rabcan, University of Zilina, Slovakia
Peter Sedlacek, University of Zilina, Slovakia

Piero Baraldi

Department of Energy, Politecnico di Milano, Italy

Reliability: the Contribution of Computational Intelligence to Maintenance

Predictive Maintenance makes use of condition monitoring data to detect anomalies (i.e., recognize deviations from normal operating conditions) in production processes, manufacturing equipment and products, diagnose (i.e., characterize the occurring abnormal state) and prognose (i.e., predict the future evolution of the abnormal state up to failure). The capability of performing these tasks can bring significant economic, reliability and safety benefits. This presentation will illustrate the main challenges towards the deployment of predictive maintenance and its effective integration in the operation and maintenance of industrial systems. By way of examples of application, the opportunities provided by the recent advancements of computational intelligence, such as deep learning, with respect to predictive maintenance will be discussed.

Frank P.A. Coolen and Jinlei Qin

Department of Mathematical Sciences, Durham University, United Kingdom

Reliability Evaluation of Multi-State Systems with Multi-State Components using the Survival Signature

The presentation starts with a brief introductory overview of the survival signature for quantification of system reliability, where both the components and the systems only have two states: functioning or failed. The main contribution presented consists of generalization of the survival signature methodology to multi-state scenarios, where both the components and the system can have multiple possible states. Whilst the computation of such generalized survival signatures is non-trivial, an easy algorithm is presented for systems made up of subsystems, in case the overall system state is a function of only the states of the subsystems. Challenges for practical application to large-scale systems are discussed.

Ah-Lian Kor

Leeds Beckett University, United Kingdom

Expressive Cardinal Direction Representation and Reasoning

In the lecture, I shall demonstrate how to group the nine cardinal directions into sets (known as Horizontal Vertical Constraints Model, HVCM). Mereology (‘Whole and Part’) and cardinal direction relations are combined to create a hybrid model which is more expressive. Lastly, the 2-D HVCM is adapted and extended into a 3-D Horizontal and Vertical Constraints Block model so that it facilitates easy reasoning with 3-D volumetric regions (i.e. without holes and single-pieced) in the real physical world (e.g. intelligent robotics, building construction).