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Predictive Maintenance and anomaly detection with MATLAB and AI techniques


This webinar is Part 2 of the Artificial Intelligence in Industrial Automation and Machinery series.

Predictive maintenance has emerged as one of the most important applications driving the digital transformation. However, many organizations are struggling to develop predictive maintenance services. According to many studies, this is most often due to lack of required skills or concerns about data quality.

In this webinar, we will use machine/deep learning techniques in MATLAB to tackle various challenges related to predictive maintenance and anomaly detection. Using data from a real-world example, we will explore importing and pre-processing data, identifying condition indicators, and training predictive models.

In addition to live demonstrations from MathWorks, Danfoss High-Pressure Pumps will share how they got started with condition monitoring using MATLAB, enabling them to improve the reliability of their pumps and build new data-driven services.


  • Preprocessing sensor data
  • Identifying condition indicators
  • Machine learning for anomaly detection and diagnostics
  • Operationalizing algorithms on embedded systems and IT/OT systems
  • Bridging the data gap

About the Presenters

Antti Löytynoja joined the MathWorks application engineering team in 2010. He focuses on MATLAB applications such as data analytics, machine learning, predictive maintenance and application deployment. 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.

Rainer Mümmler works as a Principal Application Engineer at MathWorks focusing on Data Analysis/Analytics, Artificial Intelligence, Connectivity to Hardware and on solutions for the Internet of Things. Before joining MathWorks he worked as a wind tunnel test engineer and as a freelancer for various Aerospace companies.

Rareș Curatu is responsible for driving the business development of the Industrial Automation & Machinery industry for MathWorks in EMEA. Working with companies in energy generation and transmission, machine building, and automation equipment manufacturing, Rareș helps them to adopt Industry 4.0 and Industrial IoT workflows based on MATLAB and Simulink

Product Focus

Predictive Maintenance and anomaly detection with MATLAB

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