mechmine predictive maintenance
About us
Mechmine processes machine data from plants like vibrations. It combines and exploits advanced digital signal processing and machine learning/AI techniques. Since we partially rely on AI only, we do not need huge amounts of training data of defects. We operate our own testbenches to produce vibration data of defective bearings. Our algorithms can deal with data from very slow running machines and variable speed shafts also. Our retrofit mmBox hardware is more sensitive, sees further and wider than others and contains anomaly detection also. Our tool mmViewer offers unique trend charts, automatic diagnosis, Click & Run (automated monitoring & alarm threshold setting), is safe thanks to special system architecture, presents intuitive results and is user friendly (results and graphs interpretable by anyone). Finally, we are independent and transparent, have no affiliation to any third party.
Products
mmBox Mk.2
Edge-Device for high-rate high-quality data acquisition and real-time monitoring 8/16-channels for vibration sensors 12 temperature channels 2 RPM channels 4 types of alarms configured via Mechmine's cloud-based monitoring service mmViewer
mmViewer
Cloud-based machine monitoring service mmViewer for bearings and gears/drives enables - judging the health of bearings and gears of rotating machines by analysing the vibration data in person - monitoring the state of bearings and gears, and detecting trends - automatic and continuous vibration monitoring of bearings and gears - downloading analysis reports, i.e. graphs Useful for OEMs (machine manufacturers), B2B (machine operators), and vibrationexperts who want to increase their efficiency and be able to offer 24/7 monitoring.
IEPEMULATOR
Problem: generating signals for testing cables or Edge-Devices without the need for an IEPE sensor or shaker Application: testing vibration monitoring signal chains from the sensor onwards Purpose: IEPE sensor alike reference signal generation for field or lab use Ideally suited for equipment connected to 2-wire IEPE-based acceleration sensors
LS100 Loadsensor
Retrofit sensor for safe data collection of power information Advanced Condition Monitoring and Predictive Maintenance software tools rely today on artificial intelligence (AI) or machine learning methods, and consequently on a huge number of annotated data. Machine operators prefer non-intrusive data collection, means no access to their control system, which complicates data collection, thus the need for appropriate and easy add-on measurement hardware. The data collected comprises various parameters, however, power consumed or power output is cumbersome to collect without access to the control software. This inexpensive add-on sensor enables the safe data collection of power information by means of measuring the current flow (magnetic field) in the power cords.
mmBox-mini
Unexpected machine break-down quickly leads to medium production losses. Detect roller bearing or gearbox damage, misalignment or imbalance at an early stage before damage and unexpected production downtime occur. The mmBox-mini is suitable for cost-effective 24/7 monitoring of machines with only typ. 2 bearings but using high-resolution vibration data.