Condition Monitoring Management & AI
Are you considering wireless monitoring for your plant but worried about security issues? David Howard addresses those concerns and also discusses how wireless monitoring can improve the safety of your plant, including during pandemics…
- Dr. M. David Howard
- Erbessd Instruments
Today's equipment maintenance relies heavily on human labor, while autonomous AI enables both efficient maintenance and increased productivity.
- Daisuke Nishimura
The best AI for vibration condition monitoring is the one that does not remove humans from the process
Industrial Artificial Intelligence (IAI) has one of the greatest potentials to affect the way companies manage their maintenance practices. Letting Machine Learning (ML) and algorithms take more responsibility can lead to more productive work routine and less unplanned stops and the high costs associated with it. But even with several proof points, why are maintenance professionals, particularly vibration analysts, still skeptical about it?
- Rajet Krishnan
- Viking Analytics
Spectral bands can be a very useful tool for the detection of machine faults. However, not all condition monitoring analysts use them or take advantage of their full potential.
There are four basic types of machine learning, based on the kind of information they give you and how the machine “learns”: supervised, unsupervised, semi-supervised, and reinforcement. Jason Tranter defines these and gives an example…
- Jason Tranter
- Mobius Institute