The International Workshop on Reliability Engineering and Computational Intelligence

27-29 October 2020

The international workshop on Reliability Engineering and Computational Intelligence organized by IEEE Chapter of Reliability Society of the Czechoslovakia Section in cooperation with the European Safety and Reliability Association will be an online discussion in relevant trends of Reliability Engineering with application of methods of Artificial Intelligence, Data Mining, Knowledge Discovery and Computational Intelligence.

The workshop will be supported by the following projects:

Because the workshop will be held online, it is necessary to register by using this link.


The workshop is focused on a wide range of applications of computer systems. Topics of interest include but are not limited to:

  • Reliability analysis and risk estimation
  • Testing and fault-tolerant systems
  • Accident and incident investigation
  • Human reliability analysis
  • Risk and hazard analysis
  • Software reliability
  • Data mining and knowledge discovery
  • Hardware and software solutions
  • Education, e-learning

Submission of Contributions

The presentation title, authors, their affiliations and abstract of 1,000 symbols should be sent to the easychair web-page.

All abstracts can be accessed here.


The workshop presentations will not be published as papers. The abstracts of presentation will be accepted at the workshop web-page. Authors of all presentation will be invited to publish papers in the journal CERES ( ) Authors of selected presentations will be invited to prepare the contributions for the book “Reliability Engineering and Computational Intelligence”, which will be published by Springer in series of Studies in Computational Intelligence (word template).


If you will present your research results in the form of a poster, please use the following template (Template .pptx).

All posters can be accessed here.

Important Dates

Abstract submission

18 September, 2020

Selected contributions for the book notification

9 October, 2020

Camera-ready contributions for the book

20 October, 2020

Final program

20 October, 2020

Program Committee



Organizing Committee

Keynote Speakers

Dr. Nicolae Brinzei

CRAN - Centre de Recherche en Automatique de Nancy, Université de Lorraine, France

System reliability analysis and assessment by means of graph models issued from Hasse diagram

For system that can be described by a reliability structure function, we present an approach to assess the systems reliability relying on concepts of graph models. This approach exploits the partial order relation on the set of system components’ states which is represented by the Hasse diagram. Representing the system state on the Hasse diagram, we obtain a ordered graph of system states and, so, this approach is a first step to unify the modeling of systems represented both by structure functions or stochastic processes. The monotony property of the reliability structure function of coherent systems allows us to automatically obtain this ordered graph of system states from only the knowledge of the minimal path-sets or minimal cut-sets of the system that can be obtained previously by logic differential calculus or other methods. In a first time, this approach is developed in the case of binary systems for which it gives a way to obtain a minimal disjoint form of their structure functions based on a reduction method of the ordered graph. Also, this ordered graph allows to develop an algorithm to directly obtain the analytical expression of system reliability without resorting to an intermediate Boolean polynomial. Next, this algorithm is extended to the case of non-coherent systems which no longer respect the monotony property of the structure function. Thereafter these graphs and this approach are extended to multi-state systems. The system probabilities to be in each of its progressive (perfect or degraded) operating states can be assessed using a proposed extension of the algorithm defined for binary systems, and consequently reliability of multi-state systems can be determined also. These algorithms are applied to some case studies, for both binary and multi-state systems, coherent or non-coherent, and the results compared with those computed using standard reliability block diagram or fault tree models.

Prof. Frank P.A. Coolen

Department of Mathematical Sciences, Durham University, United Kingdom

Quantification of system reliability using the survival signature

The structure function describes the functioning of a system dependent on the states of its components, and is central to theory of system reliability. The survival signature is a summary of the structure function which is sufficient to derive the system's reliability function. Since its introduction in 2012, the survival signature has received much attention in the literature, with developments on theory, computation and generalizations.
This presentation will be an introductory overview of the survival signature, including some recent developments. We will also discuss considerations and challenges for practical use of survival signatures for large systems and networks.

Prof. Coen van Gulijk

Institute of Railway Research, University of Huddersfield, United Kingdom

Making Reliability Engineering SMARTER with Computational Intelligence

Computational Intelligence has a huge potential for improving reliability of systems and the safety of systems. Promising cost savings and efficiency in practical working environments it can facilitate tremendous progress in engineering systems. But this is not just a matter of making better CI methods; it has to fit in with daily practice and add value there. This paper addresses this point by briefly discussing of a vision of digital safety delivery for the future, enterprise architecture as a means to assess the added value of tools and a fairly straightforward approach to help CI designers assess the value of their systems in the wider enterprise environment: the SMARTER mnemonic for the design of projects.

Prof. Vyacheslav Kharchenko, DSc.

National Aerospace University “KhAI”; Centre for Safety Infrastructure Oriented Research and Analysis, RPC Radiy, Kharkiv, Ukraine

Big Accidents and Markov’s Chains Based Assessment of Safety Critical IT-Systems

Objective of the talk is to discuss the influence of Big Data Analytics (BDA), Internet of Things (IoT)) on safety and security of human and industry domains. The benefits and limitations of application of BDA and IoT technologies in safety critical systems to avoid, monitor and minimize consequences of severe accidents are analysed. Markov’s chain (MC) based techniques for assessment of safety critical IT-systems (parametrization, models development and simulation results) and problems caused by complexity and accuracy are discussed. The examples of MC applications for safety critical systems (reactor trip system, accident monitoring system of NPP, IoT based health system) are considered.

Dr. Miroslav Kvassay

Faculty of Management Science and Informatics, University of Zilina, Slovakia

Methods of reliability analysis based on logic differential calculus

Logic differential calculus is a mathematical methodology developed for analysis of dynamic properties of Boolean and logic functions. This methodology can also be used in reliability analysis to analyze properties of structure function. In this way, it allows us to find situations in which a component of the system is critical for operation of the system. Based on knowledge of these situations, we can evaluate importance of the system components and identify those that have the greatest or the least influence on system operation.
In this lecture, we will focus on the basic terms of reliability analysis and logic differential calculus. We will present how Boolean and logic derivatives can be computed based on the structure function and how they can be used in evaluation of importance of the system components.

Dr. Jan Rabcan

Faculty of Management Science and Informatics, University of Zilina, Slovakia

Generation of Structure Function Based on Uncertain Data by Fuzzy Decision Tree

Any system analysis requires a mathematical representation of the system. In reliability engineering, such representation is called mathematical model of the system. One of these models is the structure function. The structure function determines system performance according to the states of its components. In this paper, the new method of structure function construction is considered. The fuzzy decision tree is used to transform data about real-world system behavior to structure function. The main novelty of this method is in the handling of incompletely specified and uncertain data.

Prof. Antoine Rauzy

Faculty of Engineering, Norwegian University of Science and Technology, Norway

New Challenges and Opportunities in Reliability Engineering of Complex Technical Systems

In this article, we discuss the impacts of technological transformations currently at work on reliability engineering of complex technical systems.
We consider transformations both in systems and in means to study them.
We review challenges to meet in order to manage the current technological paradigm shift.
We advocate the potential benefits of the so-called model-based approach in probabilistic risk assessment.
We exemplified this approach by presenting the S2ML+X modeling technology.

Organized by

Chapter of IEEE Reliability Society of the Czechoslovakia Section

Faculty of Management Science and Informatics, University of Žilina, Slovakia

European Safety and Reliability Association

In Cooperation with

Nazarbayev University

Satbayev University

Institute of Information Technologies

Supported by

Slovak Research and Development Agency

Advanced Centre for PhD Students and Young Researchers in Informatics