Datum:9.4.2019 (úterý), od 16:00
Místo:Masarykova kolej, Praha, Česká repulika
Predictive Maintenance is about optimizing the maintenance and service of machinery. Ideally, the machinery is serviced only when it's required, and always before any costly failures. In this seminar, you will learn how MATLAB enables engineers and domain experts to easily analyze data and utilize sensor data to develop models for predictive maintenance applications. Through live demonstrations you will see how to import, preprocess and explore data to understand the state of your equipment and machinery. Finally, you will learn about the different methods to develop predictive models to estimate the condition of your equipment and to predict remaining useful life.
- Importing, exploring and visualizing data
- Developing predictive maintenance and condition monitoring algorithms using machine learning
- Deploying MATLAB algorithms to embedded and enterprise systems without manual recoding
16:10MATLAB for data analysis and predictive maintenance
17:45MATLAB for data analysis and predictive maintenance (continued)
Antti Löytynoja joined the MathWorks application engineering team in 2010. He focuses on MATLAB applications such as data analytics, machine learning, application deployment, and test and measurement. Prior to joining MathWorks, Antti was a researcher at Tampere University of Technology (TUT), where he also earned his M.Sc. degree in signal processing. At TUT, Antti specialized in audio signal processing applications, such as sound source localization.