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How Machine Learning Can Help With Predictive Maintenance for Industrial Applications
Predictive maintenance is a data- and technology-based method of carrying out proactive maintenance. The main goal of predictive maintenance is to identify potential machine issues well before they lead to critical situations with shutdowns. This is realized through constant equipment performance monitoring enabled by sensors, data collection, and near-real-time communication between equipment and software. The new rise of interesting automation equipment & parts enable this in part or can at least run C++, which is of great help in such a context. Predictive maintenance can offer numerous, unparalleled benefits in productivity and efficiency — benefits which you will be able to understand from this predictive maintenance session between RealPars and Edge Impulse. It is also important to understand predictive maintenance challenges exist, but are well worth the future ROI of a edge ML enabled predictive maintenance solution.


Shahpour Shapournia: Co-founder & CEO, RealPars

Ken Bourke (BEng): Senior Automation & Controls Engineer, RealPars

Dr. Jan Jenke: Product/Project Manager, Analytics, WAGO

Mihajlo Raljic: Director, Sales & Business Development EMEA, Edge Impulse

Louis Moreau: Senior DevRel Engineer, Edge Impulse


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Ken Bourke
Senior Automation & Controls Engineer @RealPars
Ken Bourke has worked in the automation industry for close to a decade. Throughout his career, he has worked on global projects as a commissioning engineer, controls project engineer, controls architect, and software consultant. Since 2022, Ken has worked with RealPars in his free time developing training programs to make careers in automation more accessible to people around the world.
Mihajlo Raljic
Director, Sales & Business Development EMEA @Edge Impulse
Mihajlo Raljic, has history of industrial engagements where he worked for over 10 years for companies such as BASF, Bayer, Boehringer Ingelheim and Q-Cells. His roles were in Production & Technology, Marketing and Sales. Prior to joining the edge machine learning endeavors in 2019 he worked for another 10 years in renewable industry. Here he got a lot of exposure to solar photovoltaic production, technology and the quirks of getting solar farms of the ground including all aspects such as grid connection/stability, permitting and technical design including O&M for energy storage based systems.
Louis Moreau
Senior DevRel Engineer @Edge Impulse
Louis started his career developing a low-power and GPS-based IoT solution to protect rhinos in an African conservancy. He is now working at Edge Impulse as Senior DevRel Engineer. When not hacking development boards or automating repetitive tasks, you can see him riding an electric skateboard in Lille, northern France or scuba diving in some paradise places.
Shahpour Shapournia
Co-founder & CEO @RealPars
Shahpour has 8 years of experience as a PLC programmer mainly in the oil, gas, and steel industry. He understands the challenges of becoming a successful automation engineer, because he was once like his students—ready to grow, but not knowing how to go about it. He loves taking complicated engineering concepts and explaining them in an easy-to-follow format.
Dr. Jan Jenke
Product/Project Manager, Analytics @WAGO
Jan has been working at WAGO in Minden, Germany since 2018 and holds a PhD in physics. His great passion is to continually optimize processes. To this end, he implements data-driven, customized solutions with his Analytics team and develops products that generate added value from data. He works across industries and is active in the areas of industry, buildings, and utilities.