Machine Health and Maintenance
Stickershock™ with its full range of impact, vibration and motion sensors can capture, store and analyze relevant data in real-time to identify process improvements, anomalous behavior and preventative maintenance repairs.
Predictive maintenance
Go beyond traditional routine maintenance metrics like hours-in-use, and start detecting actual behavioral trends in machinery such as progressive wear and optimal service periods and times. Leverage Stickershock™ to minimize repair costs, maximize machine performance and prolong machine life.
Anomalous behavior
Stickershock™ can collect and analyze real-time data and issue alerts whenever behavior falls outside of standard performance parameters. Detect anomalous conditions in critical machines before they lead to downtime or failure. Use it to identify production bottlenecks and inefficiencies.
Machine learning
Stickershock™ can use machine learning for advanced analysis of real-time data to generate predictive maintenance models, especially valuable for assets that require early detection to avoid critical or catastrophic failures. Failure of early detection could lead to expensive repair or replacement costs, shutting down operations or evacuating personnel.
Improved workflow
With Bluetooth wireless connectivity, Near-Field communication and visual indication features, Stickershock™ can be used to direct maintenance personnel to problem areas and to open and close service tasks.