WITH ARTIFICIAL INTELLIGENCE FOR MAXIMUM PRODUCTIVITY

INTELLIGENT SENSORS
LISTEN INTO THEIR SYSTEMS

With the tepcon Machine learning solution, your production systems will always keep you up to date on how they are doing. Are all critical wear parts still in order and when should they ideally be replaced? Can all quality standards be maintained and are productivity increases possible? Your equipment will tell you all this. The systematic collection of valuable data with special sensors as well as the linking, processing and evaluation of this data in the IoT portal are dadei the communication key. AI in mechanical engineering represents an elementary success factor and sets new standards in terms of efficiency, planning reliability and convenience.

predictive maintenance

Efficient utilization of the lifetime of all critical wear parts, scheduled repairs, no unscheduled machine downtimes and thus higher overall productivity - all these are the advantages of predictive maintenance. Through the systematic acquisition and evaluation of sensor data, you always have an overview of the wear status of critical machine parts 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 at 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 analyzing important influencing factors on product quality, reworking and scrap rates are reduced. Optimized production processes are achieved by enabling the user of the machine learning system to recognize at an early stage whether the machine load should be reduced or whether an increase in productivity is possible. 

RELIABLE HARDWARE...

sensors

sensors

Both optical and acoustic sensors are used to record machine parameters and provide reliable measured values.

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data acquisition

data acquisition

Special data acquisition systems process both analog and digital sensor data and are significantly more powerful than conventional measurement solutions.

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... AND INNOVATIVE SOFTWARE

IoT Portal

IoT Portal

The evaluation and presentation of the results of the machine learning as well as the control of the IPC are carried out via our IoT portal.

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Cloud

Cloud

Storage and evaluation of sensor data in the cloud or on premise.

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Edge

Edge

The data transfer from the DAQ to the IPC, as well as from the IPC to the Cloud is done using the AWS S3 standard.

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