Getriebüberwachung Inmox GmbH A new generation MAXIMUM EFFICIENCY of gearbox monitoring LEARN MORE
WHO WE ARE

OUR VISION

We have set ourselves the goal of making mechanical engineering more sustainable through digitization. By integrating a new, intelligent technology, we aim to redefine predictive maintenance and set a new standard in the field of condition monitoring.
Aviation

Aviation

Substantial safety enhancement by immediate in-situ characterization of wear particles
Energy

Energy

Precise gearbox monitoring provides planable maintanance and security in operation, even after many years of use
Ships

Ships

Optimal readiness, cost reduction and safe operation through early detection of drivetrain failure
Industry

Industry

Prevention of unnecessary downtime or maintenance by detailed monitoring of wear particles in industrial plants

A new type of

The measurement process enables a new type of intelligent monitoring of critical components in gearboxes and power trains. It enables not only the detection but also an automatic characterization of wear particles during operation. Specific information about the state of the gearbox is available within a few seconds.

The new sensor system, supported by machine learning, supplies data by which the risk potential of the wear particles can be determined and assigned to individual component groups. The measurement system does not require moving wear particles, nor is its functionality limited by slowly rotating components or complex assemblies. The retrofit design enables a simple integration of the sensor in both new and existing systems.

Machine learning supported sensorics
Monitoring of complex assemblies and low ratio gears
Measurement method independent of the lubricant flow rate
Easy system integration

A new type of

The measurement process enables a new type of intelligent monitoring of critical components in gearboxes and power trains. It enables not only the detection but also an automatic characterization of wear particles during operation. Specific information about the state of the gearbox is available within a few seconds.

The new sensor system, supported by machine learning, supplies data by which the risk potential of the wear particles can be determined and assigned to individual component groups. The measurement system does not require moving wear particles, nor is its functionality limited by slowly rotating components or complex assemblies. The retrofit design enables a simple integration of the sensor in both new and existing systems.

Machine learning supported sensorics
Monitoring of complex assemblies and low ratio gears
Measurement method independent of the lubricant flow rate
Easy system integration

A new type of

The measurement process enables a new type of intelligent monitoring of critical components in gearboxes and power trains. It enables not only the detection but also an automatic characterization of wear particles during operation. Specific information about the state of the gearbox is available within a few seconds.

The new sensor system, supported by machine learning, supplies data by which the risk potential of the wear particles can be determined and assigned to individual component groups. The measurement system does not require moving wear particles, nor is its functionality limited by slowly rotating components or complex assemblies. The retrofit design enables a simple integration of the sensor in both new and existing systems.

Machine learning supported sensorics
Monitoring of complex assemblies and low ratio gears
Measurement method independent of the lubricant flow rate
Easy system integration
ABOUT INMOX

An innovation comes
to life

An idea is born. A revolution follows. Learn more about our brand.
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CEO/CO-FOUNDER

DI Michael Aufreiter

Mechanical engineering (transmissions for aviation and materials science, TU Wien)
6 years of professional experience/development sensorics and automation
5 years of professional experience/project leader & development medical devices
CEO/CO-FOUNDER

DI Michael Aufreiter

Mechanical engineering (transmissions for aviation and materials science, TU Wien)
6 years of professional experience/development sensorics and automation
5 years of professional experience/project leader & development medical devices
CTO/CO-FOUNDER

DI Dr. Daniel Kagerbauer

Physics (low temperature physics and superconductivity, TU Wien)
5 years of professional experience/consulting magnetism and magnetic field detection
4 years of professional experience/international science project superconductivity
CTO/CO-FOUNDER

DI Dr. Daniel Kagerbauer

Physics (low temperature physics and superconductivity, TU Wien)
5 years of professional experience/consulting magnetism and magnetic field detection
4 years of professional experience/international science project superconductivity

Team

David Bader

Software Development Lead

Oliver Jin

Data Scientist

Stefan Riesenberger

Hardware Development Lead
EXPERT KNOW-HOW

Scientific Advisory Board

We are looking for

Inmox GmbH

Mariahilfer Straße 123/3. Stock
1060 Wien

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Do you have questions?  Do not hesitate to contact us!