Predictive Maintenance - the Essentials
Predictive maintenance requires monitoring the performance and condition of equipment during normal operation to identify patterns and predict probable issues that can lead to equipment failure. To evaluate equipment condition, predictive maintenance uses non-destructive techniques such as infrared, vibration, 3D movement, sound level measurements, acoustic, airborne ultrasonic, oil analysis, and other sensor measurements. An industrial IoT platform tool is utilized to model, test and apply the predictive maintenance solution to the collected dataset. The tool includes algorithms and data analytics to detect patterns in asset data.

Predictive Maintenance - the Benefits

Reduced maintenance time and cost - Maintenance schedules based on actual equipment conditions reduce maintenance times by 20-50%. Maintenance costs can also be reduced by as much as 10%. These savings can have positive impacts to the organization's bottom-line results.
Improve throughput and efficiency - Advanced analytics and prediction minimize the need for redundant asset management while reducing downtime, thereby improving overall equipment effectiveness (OEE).
Competitive advantage - Predictive maintenance can establish improved company branding to customers while boosting customer satisfaction due to a greater sense of predictability and confidence.