Block

With
artificial intelligence
for maximum productivity

Intelligent sensors listen into your systems

With the tepcon machine learning solution, your production facilities always keep you informed about how they are doing.

All this is communicated to you by your systems. The systematic collection of valuable data with special sensors and the linking, processing and evaluation of this data in the IoT portal are the communication key. AI in mechanical engineering represents a fundamental success factor and sets new standards in terms of efficiency, planning reliability and convenience.

predictive maintenance

Efficient utilisation of the lifetime of all critical wear parts, repairs according to schedule, no unplanned machine downtimes and thus higher productivity overall - all these are the advantages of predictive maintenance.

By systematically recording and evaluating sensor data, you always have the wear status of critical machine parts in view and can reliably predict their ideal replacement time.

Bottlenecks in spare parts procurement and manpower are a thing of the past. The service technician with the right spare part is always in the right place at the right time - because with tepcon at your side, you have the far-sighted planning for this in your hands!

Condition monitoring

More performance in production: Machine learning monitors and ensures your quality standard. By analysing important factors influencing product quality, rework and reject rates are reduced. Optimised production processes are achieved by the user of the machine learning system being able to recognise at an early stage whether the machine load should be reduced or whether an increase in productivity is possible.

Innovative software

Cloud
Storage and evaluation of sensor data in the cloud or on premise.
IoT Edge
Data transmission from the measuring system (DAQ) to the IPC, as well as from the IPC to the cloud, is carried out using the AWS S3 standard.

... and reliable hardware

Sensors
Both optical and acoustic sensors are used to record machine parameters and provide reliable measured values.
Data collection
Special data acquisition systems process both analogue and digital sensor data and are significantly more powerful than conventional measurement solutions.
Sascha Spitz

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