Suggested time commitment: 4 hours
This course is self-paced for your convenience. Thus, there are no live components to the course, nor are there required login hours. Please use the video lectures for instruction along with the course exercises to gain experience working with the key concepts presented.
In this lab, we walk through scenarios to illustrate the use of process data and machine condition data and a layered approach to maintenance via usage-based, condition-based and predictive maintenance. Data sources include traditional plant instrumentation such as PLCs and SCADA, the newer IoT devices, and from machine condition monitoring such as vibration, oil analysis etc. In this lab will also discuss predictive maintenance use cases that require advanced analytics, including machine learning, such as APR (advanced pattern recognition), anomaly detection, and others.
Course Access: Unlimited access. The only exception is the Training Cloud Environment for which you have 30 day access. After those 30 days you can purchase additional access with one of the two options below: