AI-powered machine monitoring

Predictive Maintenance software

Is manually monitoring your machinery a challenge? Our digital maintenance assistant helps - automatically, easily and reliably:
Real-time insights into machine states
Detect and fix machine faults early
Avoid failures & save maintenance costs
Engineer monitors Predictive Maintenance Software Dashboard
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Cost savings
Reduce maintenance costs & extend machine life
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Relief & safety
Real-time insights without maintenance staff
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Easy integration
Seamless integration into
existing systems
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Scalability
Algorithm expandable on other machines

Typical industry challenges

Maintaining machines is a major challenge for companies — especially when undetected errors suddenly lead to production downtime and delivery delays. Reactive maintenance—whether through repairs or component replacements—leads to extended downtimes and maintenance bottlenecks. Even preventive maintenance, which is carried out regularly, does not help: It often wastes resources and causes unnecessary costs.
Comparison of reactive, preventive, and predictive maintenance

Typical industry challenges

Maintaining machines is a major challenge for companies — especially when undetected errors suddenly lead to production disruptions and delivery delays. Reactive maintenance through repairs or replacement of components results in long downtimes and bottlenecks for maintenance personnel. Even preventive maintenance, which is carried out regularly, does not help here: It often wastes resources and causes unnecessary costs.
Comparison of reactive, preventive, and predictive maintenance

Benefits of Predictive Maintenance

Our Predictive Maintenance software offers a solution to this challenge by working like a preventive health check for machines. Through data analysis and machine learning, potential failures are predicted at an early stage. Thanks to predictive AI, there are far-reaching advantages: Companies can identify and plan maintenance requirements at an early stage, resulting in less downtime, optimized use of resources and lower maintenance costs.
Longer equipment life
Optimized deployment of maintenance personnel
Reduce downtime
Higher operational efficiency

Predictive Maintenance

Real-time analysis of sensor data
More understandable health assessment
Early detection of anomalies and faults
Visual analysis to identify key causes
More about our software
Dashboard of aiomatic displaying and analyzing machine health
To see Lena with a quote
“Only 23% of companies consider themselves well-positioned in the area of digitization — a clear sign that there is an urgent need to catch up! Technologies such as Predictive Maintenance are not “nice-to-haves,” but crucial factors for the future viability of our economy.”

Lena Weirauch, CEO & Co-Founder of aiomatic
Photo: Henning von Holdt

5 steps to Predictive Maintenance

From identifying the use case to implementation and continuous optimization of the maintenance plan — we help you with every step of your Predictive Maintenance project.
‍
Book appointment for consultation
Explanation of the five steps to Predictive Maintenance

5 steps to predictive maintenance

From identifying the use case to implementation and continuous optimization of the maintenance plan — we help you with every step of your predictive maintenance project.
‍
Book appointment
Explanation of the five steps to Predictive Maintenance

How does Predictive Maintenance software work?

Diagram explaining the functionality of a Predictive Maintenance software
Diagram explaining the functionality of a Predictive Maintenance software

Predictive Maintenance requirements

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High level of digitization of your machines as well as a secure and scalable data infrastructure.
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Reliable sensor data that allows conclusions to be drawn about the status of the systems.
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Powerful analysis software required.

The highest potential for you

Success factors for a Predictive Maintenance project with aiomatic

Our Predictive Maintenance software helps you optimize your machine performance and maintenance cycles. We recommend these basics to maximize the added value of your project:
Your machines generate 5 - 200 data channels each, which we monitor for you
You can provide your machine data via digital interfaces such as OPC UA.
You have an in-house process/machine expert as well as
Maintenance personnel and development engineers available.

Success stories with our software from different industries

Large industrial plant in the energy sector
Gas storage & compressor
Monitoring of the entire system, in particular the fast-rotating, sensitive turbines.
Section of a machine for processing animal feed
Milling machines for animal feed
Monitoring of storage temperatures and drive performance for reliable & efficient production.
Illustration of a complex coating system
Inline coating machine
Monitoring of the pumps required for the water cycle in the coating plant.
Download Use Case Portfolio
“aiomatic is pioneering. For example, the application of AI to real-time data has already predicted imminent warehouse damage for one of our systems. As a result, we were able to act early and avoid an unplanned downtime of more than 8 hours.”
Dirk Schlamann
Lead maintenance at Nitto

Support

Frequently asked questions

Here you can find answers to the most common questions about predictive maintenance and our software solution.
What types of data are used for Predictive Maintenance?
Predictive Maintenance uses sensor data such as temperature, vibration, and pressure to monitor the condition of machines in real time and detect anomalies at an early stage.
Which role do the application areas of Condition Monitoring & Predictive Maintenance play?
Condition Monitoring and Predictive Maintenance play a central role in improving plant reliability. While Condition Monitoring monitors the current status of machines, Predictive Maintenance goes one step further: With AI-based analysis, it predicts errors before they occur. Predictive Maintenance software thus reduces unplanned downtimes, extends the life of systems and lowers maintenance costs. Together, they enable more efficient planning and ensure smooth operation.
AI Predictive Maintenance: Where is AI used in our software?
Artificial intelligence is used in several places in our software:

1. Machine understanding:
AI helps to understand and meaningfully analyze the structure and functioning of systems.

‍ 2. Calculation of the health score:
Instead of just using fixed thresholds, AI takes adaptive thresholds into account. This means that it recognizes changes in investments over time, learns from them and adjusts the assessments accordingly.
How can our Predictive Maintenance software help to reduce costs?
Predictive Maintenance software reduces costs by predicting failures, avoiding unplanned downtimes and extending the life of machines through targeted maintenance. In addition, maintenance cycles are optimized and the availability of machines is increased, which leads to better production performance.
What are the challenges of implementing Predictive Maintenance?
Challenges include the integration of various data sources, the selection and, if necessary, retrofitting of suitable sensors, the need for qualified personnel for data analysis, and the initial investment costs. The team of aiomatic experts will support you every step of the way.
How do I start implementing Predictive Maintenance in my company?
The implementation of a Predictive Maintenance project starts with an as-is analysis: Identify relevant machines and available sensor data. Then you choose a suitable software solution and run a Proof of Concept (PoC) to check the feasibility and benefits. The solution is then integrated into your processes, accompanied by training for your team.
Foto von Mitarbeiter bei aiomatic

Any further questions?

Our expert Kim Barthel is happy to advise you!
Get in touch now
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