Anomaly detection for industrial processes and machines with MATLAB

Channel	Publish Date	Thumbnail & View Count	Download Video
	Publish Date not found	0 Views	View on YouTube Download Video

Many industries are turning to AI to increase efficiency and improve product quality by automating production process monitoring and maintenance planning. Even as production lines are equipped with sensors as part of digital transformation, engineering teams often lack the expertise needed for predictive maintenance and advanced process analytics. This webinar will demonstrate statistical and machine learning techniques in MATLAB using real-world data sets to monitor manufacturing processes and detect equipment anomalies.

Highlights:
– Preprocessing of sensor data
– Identify condition indicators
– Use of deep learning and machine learning for anomaly detection algorithms
– Operationalization of algorithms on embedded systems and IT/OT systems

Related resources:
– Example for download on File Exchange: Anomaly detection in industrial machines: https://bit.ly/46QNxWf
– Anomaly detection overview: https://bit.ly/3Re46SO
– Overview of predictive maintenance: https://bit.ly/3AUp7wR

About the moderator:
Timothy Kyung is an applications engineer at MathWorks, providing technical expertise in application deployment, third-party software interfaces, and parallelization to the government and defense industries. He holds a bachelor's and master's degree in mechanical engineering with a concentration in robotics from Carnegie Mellon University.

00:00 Introduction
02:03 Why anomaly detection?
02:40 What is an anomaly?
03:53 Challenges of anomaly detection
06:25 Anomaly detection techniques
07:03 Workflow for developing anomaly detection algorithms
07:53 Example: Process monitoring in copper production
16:20 Example: Anomaly detection in vibration data from welding robots
27:27 Use of anomaly detection algorithms
28:10 Summary

————————————————————————————————
Get a free product trial: https://goo.gl/ZHFb5u
Learn more about MATLAB: https://goo.gl/8QV7ZZ
Learn more about Simulink: https://goo.gl/nqnbLe
See what's new in MATLAB and Simulink: https://goo.gl/pgGtod

© 2023 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
For a list of other trademarks, visit www.mathworks.com/trademarks. Other product or brand names may be trademarks or registered trademarks of their respective owners.