Avoid downtime & reduce costs
852 billion euros: that's how much global industry loses every year due to unplanned machine downtime, according to a recent study by Siemens. The solution? Our AI based software, which acts as a digital maintenance assistant and enables precise real-time monitoring of machines. Potential problems are displayed on a dashboard and can be rectified before they cause downtime.
The advantages of the aiomatic solution
First maintenance software that simulates human thinking
Algorithm can be flexibly applied to a wide range of machines
High reliability of predictions
No need for large amounts of data
Possible applications of the predictive maintenance software from aiomatic
Infrastructure
Medical Technology
Energy
Mobility
Chemistry
Pet food
Metal plants
Tools
Prerequisite for good suitability of our software
Measurement and process variables are already captured digitally
Sensor data allows conclusions to be drawn about the condition of your machines
High investment volume or valuable dependent process
5 steps to Predictive Maintenance with aiomatic
1. Define goals & machines
Goals are e.g. the minimization of breakdowns and maintenance costs as well as the implementation of predictive maintenance measures. You select relevant machines based on our questions.
2. Establish prerequisites
Seamless data integration is important for analyzing your machine data and determining the normal state. Our guidance and plug-and-play hardware will help.
4. Configure software
Your machine is displayed in our digital assistant. We support you with workshops and detailed instructions for the configuration.
5. Live
monitoring
Our AI models are now continuously trained with new data. The software recognizes anomalies in real time and evaluates the condition of the machines from 0 - 100 %.
These companies trust our solution
The future of maintenance faces challenges with skilled labor shortages. However, with aiomatic's AI-based solution, the outlook is much brighter. The team can now allocate their focus to other tasks, as aiomatic handles monitoring and provides early warning alerts.
Andreas Weber, Canyon Bicycles
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