Consultants' Network: "PHM Analytics for Industrial Internet (aka Industrial AI)”"
on June 8, 2020 from 6:00 PM to 8:00 PM
Dr. Piero P. Bonissone
Topic: “PHM Analytics for Industrial Internet (aka Industrial AI)”
Speaker: Piero P. Bonissone, CEO, Piero P Bonissone Analytics, LLC
The Industrial Internet is the third disruptive wave, after the Industrial and the Internet revolutions. It is transforming our industries, just like the Internet revolution transformed our commerce. In this new context, we face a combination of hyper-connected intelligent machines, interacting with other machines and people, and generating large amounts data that need to be analyzed by descriptive, predictive, and prescriptive models. As a result, we see the resurgence of analytics as a key differentiator for creating new services, the emergence of cloud computing as an enabling technology for service delivery, and the growth of crowdsourcing as a new phenomenon in which people play critical roles in creating information and shaping decisions in a variety of problems. We explore the intersection of these three concepts from the perspective of a machine-learning researcher and show how his job and roles have evolved over time.
In the past, analytic model creation was an artisanal process, as models were handcrafted by experienced, knowledgeable model-builders. More recently, the use of meta-heuristics, such as evolutionary algorithms, has provided us with limited levels of automation in model building and maintenance. In the short future, we expect data-driven analytic models to become a commodity. We envision having access to a large number of data-driven models, obtained by a combination of crowdsourcing, cloud-based evolutionary algorithms, outsourcing, in-house development, and legacy models. In this context, the critical issue will be model ensemble selection and fusion, rather than model generation.
First, we will review the application of data-driven analytic models to assets diagnostics and prognostics, (PHM) such as aircraft engines, medical imaging devices, and locomotives. We will cover a few case studies on anomaly detection, diagnosis, prediction, and optimization.
Then we will describe the evolution of analytic models with the advent of cloud computing, and propose the use of customized model ensembles on demand, inspired by Lazy Learning. This approach is agnostic with respect to the origin of the models, making it scalable and suitable for a variety of applications. We successfully tested this approach in a regression problem for a power plant management application, using two different sources of models: bootstrapped neural networks, and GP-created symbolic regression models evolved in the cloud. We will also present results on the fusion of models for FlyQuest, a GE-sponsored Kaggle competition in which we crowd-sourced the generation of models predicting the estimated runway and gateway arrival (ERA, EGA) over a month of US flights.
Finally, we will explore research trends, challenges and opportunities for Machine Learning techniques in this emerging context of big data and cloud computing.
Dr. Piero P. Bonissone Piero P Bonissone Analytics LLC, CEO [Retired Chief Scientist, Coolidge Fellow GE Global Research]
Dr. Bonissone is an independent consultant specialized in the use of analytics for Industrial AI applications. He provides consulting services in machine learning (ML) analytic applications, covering project definition and risk abatement, project evaluation, transition from development to deployment, and model maintenance. He defined and shaped new projects for GE Oil & Gas, prior to their integration with Baker Hughes Inc. During the previous two years, he was an Advanced Analytics Advisor for Schlumberger (SLB), where he played a key role in SLB Digital Transformation, such as part forecasting, market intelligence, PHM projects related to equipment reliability, etc. A former Chief Scientist at GE Global Research (GE GR), where he retired in 2014 after 34 years of service, Dr. Bonissone has been a pioneer in the field of analytics, machine learning, fuzzy logic, AI, and soft computing applications. During the eighties, he conceived and developed the Diesel Electric Locomotive Troubleshooting Aid (DELTA), one of the first fielded expert systems that helped maintenance technicians in troubleshooting diesel-electric locomotives. He has been the PI in many DARPA programs, from Strategic Computing Initiative, to Pilot's Associate, Submarine Operational Automation System, and Planning Initiative (ARPI). During the nineties, he led many projects in fuzzy control, from the hierarchical fuzzy control of turbo-shaft engines to the use of fuzzy logic in dishwashers, locomotives, and resonant converters for power supplies.
He is a Life Fellow of the Institute of Electrical and Electronics Engineers (IEEE), a Fellow the Association for the Advancement of Artificial Intelligence (AAAI), the International Fuzzy Systems Association (IFSA), and a Coolidge Fellow at GE Global Research. He received the 2012 Fuzzy Systems Pioneer Award from the IEEE Computational Intelligence Society (CIS). From 2010 to 2015, he chaired the Scientific Committee of the European Centre for Soft Computing. In 2008 he received the II Cajastur International Prize for Soft Computing from the European Centre of Soft Computing. In 2005 he received the Meritorious Service Award from the IEEE CIS. He has received two Dushman Awards from GE Global Research. He received 74 patents issued by the US Patent Office (and 10+ pending patents). From 1982 until 2005 he has been an Adjunct Professor at Rensselaer Polytechnic Institute, in Troy NY, where he supervised 5 PhD theses and 34 Master theses. Currently he is the Vice-Chair of the IEEE Fellows Comm.
Virtual Meeting - Connection information available after June 8th 4:00 pm on Vtools (link below)
This meeting will be held online. Please RSVP Here on IEEE Vtools. We will send an e-mail to all registered participants on Sunday evening with meeting connection information. That same information will post at 4:00pm on the day of the meeting on the VTools link.
June 8, 2020 (Monday) 6:00 - 7:30 pm – Presentation 7:30 - 8:00 pm – Introductions and Announcements
We meet on the second Monday of every month, same time.
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