Predictive Maintenance System
Award-winning predictive maintenance solution that detects machine failures early and lets you see the source of the failure.
Get rid of unexpected failures
AI-powered Industry 4.0 solution for optimal asset performance
ThingsOn Predictive Maintenance System monitors the operating conditions of your assets in real time and detects failures in advance.
See possible malfunctions in advance
Switch from periodic maintenance to predictive maintenance
Get rid of unexpected breakdowns with technology that constantly monitors and analyzes the conditions of your machines and warns you before a malfunction occurs. Reduce your maintenance costs, avoid downtime and avoid expensive equipment damage.
See the source of the problem with artificial intelligence
Don't bother diagnosing the problem
In addition to seeing the fault approaching, also see the source of the problem that caused the fault. The ThingsOn Predictive Maintenance System detects the source of the fault using precise vibration analysis and advanced algorithms.
Automatic notifications & ERP/PM integration
Access from anywhere & autonomous maintenance management
When the ThingsOn Predictive Maintenance System detects a problem, it sends a notification directing the relevant personnel to the source of the fault.
If you are using a maintenance management system, it also creates an automatic maintenance work order record.
Frequently Asked Questions
What is predictive maintenance system
How does it work?
The system consists of three main components.
Vibration Sensor: It is a measuring device that makes precise vibration measurement, has wired and wireless connection options, and communicates with the IoT Gateway.
IoT Gateway: It is a device that collects sensor data and sends processed data to the platform by performing spectrum analysis. Four sensors can be connected to one device. It has Profinet, TCP/IP and 4-20mA inputs to get speed information from the motor.
IoT Platform: It is used to store, analyze, monitor and generate notifications of processed data from sensors. It is offered with cloud-based SaaS and on-premise options.
The predictive maintenance system's ability to predict potential failures is very useful for scheduling maintenance, improving asset performance and preventing unplanned downtime.
- Reducing unplanned downtime
- Savings by increasing product quality with equipment operating at optimum performance levels
- Elimination of wasted production costs when making unplanned repairs
- Delivering products on time with reliable equipment