Keynote Lecture: Prof. Diego Galar

by admin last modified Jul 25, 2018 05:05 PM

Diego Galar

Data science in industry and transport: The black swan effect and the swan song desire

Professor Diego Galar

Lulea University of Technology & Tecnalia, Sweden

Date & Time: July 30 (Monday), 2018; 09:30am - 10:20am
Location: Galleria B-C

Industrial systems can be considered in a system of systems approach and are extremely complex in both their technology and their operation. For the operations and maintenance of such complex assets, a viable solution is to use data science and decision-making processes based on data harvested by pervasive computing.

Industry 4.0 refers to the fourth industrial revolution typified and enabled by instrumentation, interconnection and intelligence. As part of this revolution, maintenance must employ smart systems that predict failure. However, the increasing complexity of assets makes early detection of failure extremely challenging. For complex assets, much information needs to be captured and mined to assess the overall condition of the whole system. Various information on the asset must be integrated to get an accurate health assessment and determine the probability of a shutdown or slowdown. All efforts are focused on the search for the moment just before the shutdown or unexpected stoppage of an asset, or the time of its ‘swan song’. Unfortunately, the data collected are not generally sufficient.

The black swan event is a metaphor for an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of hindsight A key issue is the inability of risk assessment and probability theory to capture extreme events with a very low probability, at least from data science perspective. This talk includes an in-depth analysis of what a black swan means in relation to asset failure, uncertainty and probability. It explains how the black swan effect in industry may pop up in rare events not considered by data driven models.

The talk will address the issues and challenges of data science in industry and transport, emphasizing the positive effects of swan song identification and detection while considering the limitations if black swans are neglected.


Dr. Diego Galar is Professor of Condition Monitoring in the Division of Operation and Maintenance Engineering at LTU, Luleå University of Technology where he is coordinating several H2020 projects related to different aspects of cyber physical systems, Industry 4.0, IoT or industrial Big Data. He was also involved in the SKF UTC centre located in Lulea focused on SMART bearings and also actively involved in national projects with the Swedish industry or funded by Swedish national agencies like Vinnova.

He is also principal researcher in Tecnalia (Spain), heading the Maintenance and Reliability research group within the Division of Industry and Transport. 

He has authored more than five hundred journal and conference papers, books and technical reports in the field of maintenance, working also as member of editorial boards, scientific committees and chairing international journals and conferences and actively participating in national and international committees for standardization and R&D in the topics of reliability and maintenance.

In the international arena, he has been visiting Professor in the Polytechnic of Braganza (Portugal), University of Valencia and NIU (USA) and the Universidad Pontificia Católica de Chile. Currently, he is visiting professor in University of Sunderland (UK), University of Maryland (USA), and Chongqing University in China.

Filed under: , ,