Industrial Artificial Intelligence – From automated Process to Cognitive Analytics

Abstract: 

Industry and transportation are suffering revolution in which artificial intelligence applications, from virtual assistants to advanced robotics, disrupt end-to-end value chains amid radical shifts in demand. The scope of change compels many manufacturers to adopt new plant designs, reshape their manufacturing footprints, and devise new supply chain models. Advances in AI technologies is enabling the industry to leverage rapid growth in the volume of data to optimize processes in real time. They can shorten development cycles, improve engineering efficiency, prevent faults, increase safety by automating risky activities, reduce inventory costs with better supply and demand planning, and increase revenue with better sales lead identification and price optimization.
The talk will show how the growth of industrial artificial intelligence (AI) is reimagining the industries in many dimensions. Companies are learning how to use their data to not only analyze the past but predict the future as well. Indeed, one industry that can expect to see unprecedented savings from AI is manufacturing where AI can usher in a new era of productivity. AI is not just helping with failure predictions, it is also supporting operators on the front line to understand their machines even better than before, having all the historical data in one easy-to-access dashboard and keeping everyone at your company on the same page in order to make it easier for machines to get serviced, faster.
However, the great benefit of the AI in industry is the accurate prediction of the performance and the failure in order to replace the traditional O&M. While effective, there are certain drawbacks to these methods since robustness and resilience of AI are still unclear in some sectors. In fact, it’s not an exact science and risks must be properly quantified or else AI triggers some fears for the deployment in the field. This disruptive transformation of manufacturing is traumatic that is why confidence in the industrial AI is crucial.

Bio: 

Dr. Diego Galar is Full 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 AI and Big Data. He was also involved in the SKF UTC center 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 a 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 a 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 at University of Sunderland (UK), University of Maryland (USA), and Chongqing University in China.

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