Machine data | Software development

Predictive maintenance software

We develop predictive maintenance software solutions that turn machine data into recommendations for action - for less downtime, lower maintenance costs and maximum system availability.

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Predictive maintenance software from prodot
ALDI SOUTH: Customer of prodot Thyssenkrupp Elevator: Customer of prodot Rossmann: Customer of prodot Siemens Energy: Customer of prodot Bayer04 Leverkusen: Customer of prodot Borussia Mönchengladbach: Customer of prodot 3M: Customer of prodot thyssenkrupp: Customer of prodot Caparol: Customer of prodot HAVI: Customer of prodot

Predict failures before they occurwith predictive maintenance software

Unplanned machine downtime costs companies an average of€120,000 per hour. Despite this, many companies still rely on reactive maintenance strategies: you repair whensomething is broken. The result: production stops, spare parts shortages and exploding maintenance costs.

Predictive maintenance, , reverses this principle. By continuously recording sensor data, combined with machine learning algorithms and IoT technology, anomalies in the machine's condition can be detected at an early stage before they lead to a breakdown. The Remaining Useful Life (RUL) of components becomes predictable and maintenance is carried out when it is really necessary.

At prodot, we develop the predictive maintenance software infrastructure that makes exactly this possible: from connecting your machines to data analysis and a dashboard that provides your team with clear recommendations for action. Whether condition monitoring, anomaly-based alerting or complete predictive maintenance platforms: We deliver the right solution for your Industry 4.0 environment.

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This is what predictive maintenance software offers:

The future of machine data

Data-driven instead of gut feeling-based

We integrate IIoT sensors, machine control systems and existing ERP/MES systems into a continuous data stream: The basis for reliable forecasting models based on real production data.

AI that understands your machines

Our developers train machine learning models on your specific systems and failure patterns. No standard off-the-shelf solution, but algorithms that get better with your data.

Integration into existing systems

Predictive maintenance only works if it is integrated into everyday work. We develop seamless interfaces to SAP PM, CMMS and existing maintenance workflows so that your team receives recommendations for action directly where they work.

Added value of our predictive maintenance software

Up to 40 % less unplanned downtime

  • Anomalies are detected days or weeks before a critical failure
  • Maintenance windows can be specifically scheduled for low-production times
  • Emergency repairs and consequential damage to downstream components are drastically reduced

Reducemaintenance costs by an average of 30

  • Expensive flat-rate maintenance according to a schedule is no longer necessary - only what really needs attention is serviced
  • Spare parts inventory is demand-driven instead of kept in stock
  • The maintenance team's resources are planned and prioritized more efficiently

Full transparency about the status of your systems in real time

  • Live dashboards show machine status, anomaly score and predicted remaining runtime at a glance
  • Automatic alerts at defined thresholds via app, email or directly in the ticket system
  • Decision-making basis for investments in replacement or retrofit based on real data instead of estimates

From raw data to predictive maintenance - our scope of services

Predictive maintenance is not a product that you buy, it is a software capability that you build up. We accompany you all the way.
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IIoT connection & sensor integration

We connect your machines, controllers (PLC/SCADA) and sensors to a central data platform - OPC-UA, MQTT, REST or proprietary protocols: we speak the language of your system.

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Condition monitoring & real-time monitoring

Continuous monitoring of vibration, temperature, pressure, power consumption and other parameters with automatic detection of deviations from normal operation.

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Machine learning models & anomaly detection

Development and training of AI models that learn plant-specific failure patterns: supervised and unsupervised learning, ensemble models and deep learning approaches such as LSTM for time-based sensor data.

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Prognostics & RUL calculation

Calculation of the remaining useful life of individual components as a basis for predictable maintenance intervals and forward-looking spare parts logistics.

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Dashboard & reporting

User-friendly web and mobile interfaces that visualize the machine status for maintenance teams and production managers, including KPI tracking, alarm history and maintenance recommendations.

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System integration & rollout

Seamless integration into SAP PM, IBM Maximo, CMMS or proprietary ERP systems - plus change management and training to ensure your team uses the solution from day one.

Contact us now
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Your contact person

Daniel Ludewig
0203 3965080
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Questions & Answers

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Who we are

Digital Passion. Driving innovation. We inspire people with the right solutions for their business. As a pioneer and trailblazer into the digital future, we are committed to making our customers even more successful.

Passionate, interdisciplinary and agile. These are our ingredients for successful collaboration with our clients' teams. Together, we integrate innovations into the existing IT infrastructure. With a short time-to-market, seamlessly and efficiently, we help our customers to achieve their business goals in a more digital, secure and smarter way.

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