How to implement predictive maintenance using artificial intelligence
Designing and building machines that provide end users with improved overall equipment effectiveness and increased productivity is a challenge many OEMs face. Whilst artificial intelligence offers the potential to predict component failure, reduce unplanned downtime, and enable a preventative maintenance approach, it is not always clear how best to implement this technology.
This webinar recording aims to demystify industrial AI with a step-by-step explanation:
- What is industrial AI?
- Why use AI and how it can contribute to the efficient deployment of people and assets?
- How do you use industrial AI to improve efficiency & quality and reduce downtime?
We address OEMs' fundamental choice: whether to develop their own AI tools or source them from a supplier. We then look at the pros and cons of each option.
This webinar recording concludes with an explanation and demonstration of Festo's latest AI-based tools and how to integrate them into your new and existing machines.
This recording is ideal for design and controls engineers in OEM’s as well as production and maintenance engineers in End-Users / manufacturers looking to use artificial intelligence to improve machine reliability and increase overall OEE.
Sign up to improve machine reliability and increase your overall Overall Equipment Effectiveness!
You will be sent an email with instant access to the on-demand video.
Meet our presenters:
Sebastian Werler is a Product Manager for Digital Business responsible for bringing digital added-value solutions to the market that enhance the Festo hardware product range with Industrial AI Solutions. A computer scientist by profession, Sebastian enjoys converging the latest machine learning technology with Festo’s manufacturing and automation know-how.
Sebastian Werler
Product Manager
Peter Potters is a product manager for pneumatic motion, functional actuators and vacuum. He is motivated by finding the right solution for customers and the variety of application challenges. He enjoys problem solving using engineering tools to make machine designs more efficient and sustainable.
Peter Potters
Product Manager
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