Predictive maintenance is one of the mostly mentioned and actually used IoT use cases. Predictive maintenance is used to determine when a manufacturing plant, machine or component would fail and with that it is possible to reduce downtime, reduce maintenance costs, understand the root causes of failures and improve operational effectiveness and safety.
The article gives overview of some typical use cases like: 1. Will this equipment fail in a given period? 2. What is the remaining life of your equipment? 3. Is there an anomaly in equipment behavior? 4. Optimize equipment settings.
The IoT data gathered is typically heat, vibration, and sound produced by machinery, then also visual inspection and machine vision is used, batteries voltage is recorded etc. Other categories are metadata about equipment, usage history and maintenance data. Here is the link to the first out of the three posts. The posts will probably (as a typical content marketing) softly suggest to use GCP for your predictive maintenance projects, but nevertheless the information presented is good and useful 🙂