Keynote Speakers 1

Michael Beer


Institute for Risk and Reliability, Leibniz Universität Hannover, Germany

Institute for Risk and Uncertainty, University of Liverpool, UK

International Joint Research Center for Engineering Reliability and Stochastic Mechanics (ERSM), Tongji University, China

Title: Efficient Systems Analysis Addressing Complexity and Uncertainties

ABSTRACT: Engineered systems are critical for the functionality of our economic and societal life, they are the technical backbone of our society. A key requirement is, thus, to ensure their reliable performance. Reliability and performance analysis, however, become increasingly complicated due to uncertainties and complexity. In our developed societies, engineered systems are characterized by a rapid growth in scale and complexity. The amount of information needed to model these systems with their complexity is, thus, growing as well. In contrast to this increasing need for information the available information remains almost at the same level. Hence, with increasing scale and complexity the gap between required and available information is growing quickly, so that uncertainties and risks are involved in our models and analyses to a greater extent than ever before. This keynote lecture will highlight selected approaches to address this challenge. Concepts for dealing with epistemic and hybrid uncertainties are discussed, including applications to systems reliability assessment. In order for numerical efficiency to deal with complex systems, survival signature is presented as powerful systems model in combination with advanced simulation technologies for performance and reliability assessment. Novel pathways to capture interdependencies between systems are discussed. Engineering examples are presented to demonstrate the capabilities of the approaches and concepts.

Bio: Prof. Michael Beer is Professor and Head of the Institute for Risk and Reliability, Leibniz Universität Hannover, Germany, since 2015. He is also part time Professor at the University of Liverpool and at Tongji University, Shanghai, China. He obtained a doctoral degree from Technische Universität Dresden and pursued post-doctoral research at Rice University. From 2007 to 2011 Dr. Beer worked as an Assistant Professor at National University of Singapore. In 2011 he joined the University of Liverpool as Chair in Uncertainty in Engineering and Founding Director of the Institute for Risk and Uncertainty and established a large Doctoral Training Center on Quantification and Management of Risk & Uncertainty. Dr. Beer’s research is focused on uncertainty quantification in engineering with emphasis on imprecise probabilities. Dr. Beer is Editor in Chief (joint) of the Encyclopedia of Earthquake Engineering, Associate Editor of the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Associate Editor of the International Journal of Reliability and Safety, and Member of thirteen Editorial Boards including Probabilistic Engineering Mechanics, Computers & Structures, Structural Safety, Mechanical Systems and Signal Processing, and International Journal for Uncertainty Quantification. He has won several awards including the CADLM PRIZE 2007 – Intelligent Optimal Design and a Certificate for Highly Cited Research in Structural Safety. His publications include a book, several monographs and a large number of journal and conference papers. He is a Fellow of the Alexander von Humboldt-Foundation, Chair of the C(PS)2 of the Bernoulli Society and Member of ASCE (EMI), ASME, IACM, ESRA, EASD, and GACM.

Keynote Speakers 2

Weidong Zhu


University of Maryland

Baltimore, MD 21250, USA

Title: Model- and Non-model-based Damage Detection Methods Using Vibration Data

Abstract: Recent advances in model- and non-model-based damage detection methods using vibration data such as natural frequencies and mode shapes are presented. Two major challenges associated with model-based methods are addressed: accurate modeling of structures and development of a robust inverse algorithm to detect damage, which are defined as the forward and inverse problems associated with model-based damage detection methods, respectively. To resolve the forward problem, new physics-based finite element modeling techniques for fillets in thin-walled beams and bolted joints are developed, so that complex structures with thin-walled beams and/or bolted joints can be accurately modeled with a reasonable model size. To resolve the inverse problem, a robust iterative algorithm that uses Levenberg-Marquardt method is developed to accurately detect locations and extent of damage using a minimum number of measured natural frequencies.
Non-model-based methods that use vibration shapes measured from scanning laser vibrometry, without use of any a priori information of undamaged structures that is usually not available in practice, are introduced. Curvature vibration shapes are compared with those from polynomial fits with proper orders to yield curvature damage indices to identify damage. A new multi-scale differential geometry scheme is developed to calculate curvature vibration shapes. Spatially detailed vibration shapes can be measured by a continuously scanning laser Doppler vibrometer system developed in-house in a rapid and accurate manner. Application of the methodology to detect delaminations in composite plates are demonstrated. Use of operational modal analysis and digital image correlation to detect damage in membranes is also demonstrated.

Bio: Prof. Weidong Zhu is a Professor in the Department of Mechanical Engineering at the University of Maryland, Baltimore County, and the founder and director of its Dynamic Systems and Vibrations Laboratory and Laser Vibrometry Laboratory. He received his double major BS degree in Mechanical Engineering and Computational Science from Shanghai Jiao Tong University in 1986, and his MS and PhD degrees in Mechanical Engineering from Arizona State University and the University of California at Berkeley in 1988 and 1994, respectively. He is a recipient of the 2004 National Science Foundation CAREER Award, has been an ASME Fellow since 2010, was an Associate Editor of the ASME Journal of Vibration and Acoustics from 2007-2014, and is a Subject Editor of the Journal of Sound and Vibration. His research spans the fields of dynamics, vibration, control, applied mechanics, structural health monitoring, metamaterials, and wind energy, and involves analytical development, numerical simulation, experimental validation, and industrial application. He has published 140 archival journal papers in these areas and has five U.S. patents.

Keynote Speakers 3

Dariusz Mazurkiewicz

Professor, Editor-in-Chief of "Eksploatacja i Niezawodnosc - Maintenance and Reliability"

Lublin University of Technology, Lublin, Poland

Title: Management of production systems reliability based on time series modelling

Abstract: The implementation of automation for data analysis and interpretation has become inevitable. Also the realities of IIoT-based companies and easier access to advanced diagnostic solutions are extremely important in this context. The ongoing revolution has established the need for proper and effective analysis of big datasets collected by the systems for the monitoring of machine and machinery component condition.Data from monitoring or maintenance systems are a significant part of any typical database, and they require suitable processing and inferring with respect to taking decisions concerning optimal management of technical infrastructure and its reliability. Examining values collected in the databases, we usually try to design mathematical models which could describe as accurately as possible the investigated phenomenon or a technological process. The behaviour of a system is usually modelled by a stochastic process with discrete time, which is known as a time series. The dynamic prioritization of detected and predicted malfunctions together with risk analysis, planning of the scope of the service, scheduling of the workflow with associated economical optimization should be effectively and automatically analyzed and distributed to defined end users. This requires adequate data analysis techniques and mathematical models for failure prediction. In addition, integration of data from multiple sources is needed to be included in the final decision. From this point of view, some important aspect of production systems reliability management based on time series modelling will be discussed and presented.

Bio: Prof. Dariusz Mazurkiewicz is a professor and ​head of the Metrology and Computerization in Production Engineering Chair at the Lublin University of Technology (Lublin, Poland). He is also the ​Editor-in-Chief of the quarterly "Eksploatacja i Niezawodnosc - Maintenance and Reliability". Previously he was a visiting scholar or research fellow of the Cambridge University Engineering Department (Cambridge, UK), Kobe University (Kobe, Japan) or of the System Research Institute (Polish Academy of Sciences, Warsaw, Poland).  His research skills and experience are in maintenance and reliability, predictive maintenance, IIoT, numerical modeling, transportation systems (including mining technology), mining engineering technology, production engineering, data mining, artificial neural networks and fuzzy logic, innovation, regional innovation policy. He is an expert of the European Commission, Research Executive Agency. Member of the Scientific Committee of the Motor Transport Institute (Warsaw, Poland), nominated by the Minister of Infrastructure and Construction of the Republic of Poland. Member of the Economic Council, Kraśnik County, Poland. Member of the Board of Directors, Entrepreneurship Incubator of the LUT. He was an external expert in the “National Foresight Programme – results implementation” carried out on behalf of the Ministry of Science and Higher Education, Warsaw. Expert responsible for preparation of the Regional Innovation Strategy up to 2020, Marshal Office of the Lubelskie Region. Member of the Board of Directors, FAWAG S.A., Lublin, Poland (2012-2014). External expert of the project “Innovative technologies foresight for automation, robotics and measurement techniques”, System Research Institute, Warsaw University of Technology. Member of the Regional Cooperation Conference responsible for regional development politics, as a delegate of the Minister of Science and Higher Education. External expert of the National Programme Foresight Poland 2020, Ministry of Science and Higher Education. Expert in the project within the project “RIS EVALLUB Lubelskie”. Expert in the project within the EU FP6. Supervisor of the research project of the State Committee for Scientific Research and of the Lublin Regional Authorities: “Innovation Strategy for Lublin Region”.

Keynote Speakers 4

Insu Jeon

Professor, President of Reliability Engineering Division of KSME

School of Mechanical Engineering, Chonnam National University

Buk-gu, Gwangju 61186, Republic of Korea

TitleDevelopment of a high-resolution X-ray CT microscope for inspection of micro-scale defects in materials

Abstract: The procedure for developing an X-ray CT microscope system for inspection of micro-scale defects in materials is introduced. For generating X-rays of various wave lengths, a simple-structured anode exchangeable X-ray tube was developed. For taking high resolution X-ray projection images, multilayer X-ray mirrors, which can reflect only the characteristic X-ray and increase its intensity were designed and fabricated. Also, a glass thin film scintillator, on which nano-scale column CSI(Tl) layer was formed by DOD (Dynamic Oblique angle Deposition) technique was developed. After line up of the developed components, magnified X-ray projection images of micro-scale defects can be obtained using CCD camera and optical lenses with magnifying power of 40 installed in front of the camera. An improved mathematical CT (Computed Tomography) reconstruction technique, MSIRT (Modified Simultaneous Iterative Reconstruction Technique) and an image interpolation technique for calculating X-ray projection images were developed and combined with each other, and will be applied to obtain magnified CT images of micro-scale defects. Taking the CT images of various micro-scale defects in materials is now under studying.

Bio: Prof. Insu Jeon is a Professor in the School of Mechanical Engineering, Chonnam National University, Korea, and the leader of the reliability division of KSME. He received his BS degree in Mechanical Design Engineering from Pusan National University in 1993, and his MS and PhD degrees in Mechanical Engineering from Korea Advanced Institute of Science and Technology in 1995 and 2000, respectively. Previous he was a visiting Professor in the School of Engineering and Applied Sciences, Harvard University from 2013 to 2014. And he was also a tenure-track research scientist of Materials Research Institute for Sustainable Development, National Institute of Advanced Industrial Science and Technology (AIST) in Japan from 2004 to 2006. He has got the Best Paper Awards for many times in some academic activities. His current research involves Functional Materials, Biomaterials & Biomechanics, X-ray Physics and Systems, Fracture Mechanics and Non-destructive Evaluations. He has Published 45 journal papers in these areas and 2 professional books.

Keynote Speakers 5

Liudong Xing


University of Massachusetts (UMass), Dartmouth, USA

Title: Competing Failure Analysis in the Internet of Things System with Functional Dependence

Abstract: As an emerging paradigm, the Internet of Things (IoT) aims to improve the quality of life by connecting various smart objects and technologies. These objects often interact with each other, complicating the system reliability modeling and analysis. This talk focuses on one such interaction caused by functional dependence, where the malfunction of certain system component may cause some other components within the same system to become isolated (unusable or inaccessible). In addition, the system components may undergo propagated failures, causing extensive damages to the rest of the system. A time-domain competition exists between the isolation effect and the failure propagation effect; different occurrence sequences can lead to dramatically different system statuses. An efficient combinatorial methodology is discussed, which practices the divide-and-conquer principle to address the competing effects in the reliability analysis of the IoT systems. Examples of the IoT systems in smart homes and body sensor networks are presented to demonstrate the interacting behavior considered and the methodology. 

Bio: Prof. Liudong Xing is a Professor at the University of Massachusetts (UMass), Dartmouth, USA. She received her PhD degree in Electrical Engineering from the University of Virginia, Charlottesville in 2002. Her research focuses on reliability modelling, analysis and optimization of complex systems and networks. She has published two books entitled “Binary Decision Diagrams and Extensions for System Reliability Analysis (Scrivener-Wiley, 2015) and Dynamic System Reliability: Modeling and Analysis of Dynamic and Dependent Behaviors” (Wiley, 2019). Prof. Xing was the recipient of several only one per year awards of UMass Dartmouth, including the Leo M. Sullivan Teacher of the Year Award (2014), Outstanding Women Award (2011), and Scholar of the Year Award (2010).  She was the recipient of the IEEE Region 1 Outstanding Teaching in an IEEE Area of Interest Award (2018), Changjiang Scholar Award from the Ministry of Education of China (2015), and IEEE Region 1 Technological Innovation (Academic) Award (2007). She was also co-recipient of 2018 Premium Award for Best Paper in the journal of IET Wireless Sensor Systems, and the Best (Student) Paper Award at several international conferences. She is or was an Associate Editor or Editorial Board member of multiple journals including Reliability Engineering & System Safety, International Journal of Systems Science, IEEE Transactions on Reliability, etc.