Industry
4.0 holds many promises for manufacturers; however, a shortage of qualified
employees has prevented a swift adoption of the revolution's new technologies.
Engineer and Economist Klaus Schwab argues Education 4.0 is the key to addressing
the employee shortage and preparing future generations for the shifting labor
market. To support Education 4.0, classes must allow students to engage emerging
technologies that help bridge Operational Technology (OT) and Informational
Technology (IT). The thesis detailed an educational laboratory that
demonstrates the application of data analytics (an IT tool) and optimize the
performance of a cyber-physical system composed of industrial (OT) components. The
lab experience focuses on a disc's controlled positioning (levitating) using a
PLC-based PID controller and a VFD. The activity requires students to capture
data of a moving discs, create a machine learning function representing the
disc's movement, and use the machine learning function for classification and
PID optimization problems. A comparative analysis of a PID cycle ensures a regressions
model accurately represents the physical model using measurements including
peak-overshoot, rise time, settling time, and the flight plots' Means of their
Squared Error. Further, the study examines multiple ML models each built using various
features to identify the systems relevant and redundant data.<br>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/15070830 |
| Date | 29 July 2021 |
| Creators | Dylan James Imbus (11197911) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/An_Industrial-Grade_Cyber-Physical_Platform_for_Introducing_Machine_Learning_Concepts/15070830 |
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