Wireless sensors, artificial intelligence and machine learning offer the promise to deliver advances in predictive maintenance by automating the monitoring of your machine health.
- Matthew Moore
Maintenance (like many other functions) depends greatly on data. Maintenance data has always been a concern for most of the organizations due to many reasons and factors during the different phases of the asset life cycle.
- Ahmed Kotb
Have you ever wondered exactly how machine learning works? Where does the system get the data for equipment that is not allowed to fail often? Jason Tranter goes into a method an AI system might use to tell us whether a bearing is about to fail…
- Jason Tranter
- Mobius Institute
The 2020 calendar year has certainly brought with it many challenges for a variety of industries. The medical field, pulp and paper industry and food supply chain have all been significantly impacted by the unprecedented COVID-19 pandemic. At the grocery store, people experienced (or are still experiencing) empty shelves, limited food supply and less variety when doing weekly shopping. In March 2020, grocery and supply sales increased 29% from the previous year (3).
- Spectro Scientific
- Spectro Scientific
What makes your electric motor maintenance program a winner? Answer: A Trending Data program along with Troubleshooting and Quality Control. Watch this video to see how one part of the program, Trending, helps you reach your goal of a winning program in your facility.
- Noah Bethel
- PdMA Corporation
Online monitoring is the process of utilizing permanently mounted sensors to regularly check the condition of a machine. Online monitoring should consist of more than just vibration sensors. Given there are many different failure modes it is best to utilize a variety of sensor types to monitor the necessary variable to ensure early warning of failure.
- Dr. M. David Howard
- Erbessd Instruments
Vibration analysis requires a correct identification of the rotational speed of the machine. How the different frequencies of the spectrum are related to RPM, identifying with high accuracy the order of each frequency, is essential for the analysis process.