AI
Case Studies and Stories
Simple and Easy Steps for Implementing Predictive Maintenance in Machinery using High Frequency Vibration Data and Edge AI
Currently, the most commonly used standard for maintenance processes is Time-based Maintenance (TBM) that involves inspection, repair, and part replacement at regular intervals. In general, TBM is not optimal and cost effective. On the other hand, Condition-based Maintenance (CBM) involves the utilization of various types of sensor data collected from machines to perform repairs or other countermeasures before malfunctions or anomalies occur, hence reducing the unnecessary cost of maintenance.
- Vikas Kumar Singh
- Macnica
10 Minute Talk
An IIoT + AI-Based PdM Approach to Overhead Crane Monitoring
As technology improves every day, Wireless Sensors are able to successfully monitor equipment. Wireless Sensors are easy to install anywhere, and there is no need for local networks, modems, or gateways. Dries Van Loon gives more detail on the benefits of these sensors.
- Dries Van Loon
- NanoPrecise
10 Minute Talk
Signal vs Data Processing (AI) in CM
Ed Spence, founder and manager of the Machine Instrumentation Group, explains the key differences between signal and data processing (AI) in condition monitoring…
- Ed Spence
- The Machine Instrumentation Group
Articles
The First Step in AI Based Predictive Maintenance
With the increasing demand of IIoT in the age of digitalization, data-driven maintenance optimization of industrial equipment is one of the most trending topics among maintenance professionals. At the beginning, data gathered by various sensors placed on the machines or embedded in the machine itself are pre-processed.
- Anil Ulusoy
- Sensemore.io
10 Minute Talk
Terminology and Background of AI Systems
Do you know the difference between AI, machine learning, predictive analytics, data analytics, IIoT, and predictive maintenance? Jason Tranter goes into the definitions with examples…
- Jason Tranter
- Mobius Institute
10 Minute Talk
Bearing Problems – Fault Frequency and Artificial Intelligence-Based Methods
The early detection and fault analysis of bearing problems is crucial. When a rolling-element bearing develops flaws on the races and/or rolling elements, there are four vibration frequencies that can result...
- Pawel Lecinski
- CMRP
Articles
5 Ways Machine Learning Improves Asset Performance in Power Plants
A 500 MW power plant generates about 10,000 data points every second. It’s impossible for humans to review all this data and use it to optimize plant performance.
- Mohan Amasa
- AssetSense
Five Minute Facts
Training Machine Learning Models
When we’re training the model, we’re looking for normal behavior and, along with the client’s domain experts, come together with a model that represents the behavior they are trying to control…
- Robert Kalwarowsky
- Rob's Reliability Project
Webinars
Industrial AI for Asset Performance Management: A Framework for Success in Digital Transformation
Industrial AI has the potential to radically improve asset optimization. It also has the potential to exponentially increase backlog and overwhelm plant staff. Thousands of sensors, thousands of alerts, floods of data...What assets do you monitor? Which alerts must be responded to? What do you DO when get an alert? The value of digitalization for managing asset performance is only achieved when the right work is done to the right assets at the right time.
- Tacoma Zach
- MentorAPM
