Prevent machine failures with explitia.PDM
Machine learning predictive maintenance that protects your production
Every unexpected machine failure creates pressure. Production stops. Orders are delayed. Costs increase. Maintenance teams must react immediately, but there’s not enough time or data to understand the root cause.
Explitia.PDM – Predictive Maintenance is machine learning predictive maintenance software built for those who want to prevent failures before they need to react to them.
The system analyzes real-time machine data, detects early warning signals, and helps you plan maintenance before breakdowns occur, which means fewer surprises, more predictable production, and better cost control.
Connect machine condition data with production analysis!
Contact us and see how explitia.PDM helps reduce failures, interpret performance drops, and connect machine condition with production availability, efficiency, quality, and costs.
What does Predictive Maintenance deliver from the user’s perspective?
If your goal is stable production and more predictable machine operation, explitia.PDM gives you the data needed to assess machine condition faster, detect early warning signals, and reduce the risk of unplanned downtime before failures affect your production.
The system supports you by enabling:
Continuous real-time machine condition monitoring
Detection of anomalies before they become failures
Identification of components that are wearing out
Prediction of the right moment for service or replacement
Analysis of trends and remaining useful life of key parts
Integration of machine condition data with production context
Predictive maintenance extends production data with technical context, helping teams make faster decisions, reduce risk, and act with greater confidence in daily operations.
What is machine learning predictive maintenance?
Machine learning predictive maintenance uses operational data and intelligent algorithms to assess the actual technical condition of machines.
Instead of servicing equipment according to a fixed schedule, maintenance decisions are based on real machine behavior.
With explitia.PDM predictive maintenance software, you can:
- detect anomalies before they become failures,
- identify components that are wearing out,
- estimate the remaining useful life of key parts,
- receive early alerts for planned intervention.
It helps you reduce risk and boosts your team confidence in daily operations.
Predictive Maintenance and production efficiency analysis
Efficiency indicators show where production is losing performance, while Predictive Maintenance helps explain why.
Combining production analysis with predictive maintenance makes it possible to:
- identify the technical causes of downtime and availability losses,
- analyze how machine condition affects efficiency, output, and quality,
- stabilize production line availability through earlier intervention planning,
- plan maintenance activities better in the context of production schedules and costs.
Thanks to this, predictive maintenance supports production management in real time instead of operating as a separate technical tool.
How explitia.PDM – predictive maintenance software works?
Real-time machine data collection
The system connects to PLC controllers, IoT sensors, SCADA systems, MES platforms and sensors measuring vibration, temperature, pressure, and energy use.
It continuously gathers operational data from machines and production lines without interrupting work.
Machine learning analysis
Collected data is processed with advanced machine learning models designed for industrial environments.
The system learns what your typical machine behavior looks like, detects deviations from standard operating conditions, identifies patterns that historically precede failures and improves prediction accuracy over time.
You can shift from reactive maintenance to predictive maintenance based on facts.
Early alerts and maintenance planning
When abnormal behavior appears, the system generates clear alerts with practical information:
- Which machine is at risk
- What type of anomaly has been detected
- How urgent the situation is
Maintenance managers can plan service during scheduled downtime instead of dealing with emergency breakdowns.
The result is better coordination between production and maintenance teams.
Reports and predictive maintenance analytics
Reports include:
- alarm history,
- analysis of equipment life and remaining useful life,
- wear and anomaly trends,
- aggregated reports for managers.
This makes it possible to analyze technical data in the context of production performance, quality, and costs.
The result is a shift from reactive maintenance to predictive maintenance based on facts, with better coordination between production and maintenance teams.
Take control of machine reliability!
Predictive maintenance helps you plan service with greater confidence, based on real machine behavior instead of relying only on fixed schedules. Contact us and test the solution in your manufacturing plant.
The most common problems solved by predictive maintenance
- lack of visibility into the actual technical condition of machines,
- unplanned production downtime,
- maintenance decisions based only on fixed schedules or experience,
- difficulty linking technical issues with production losses, quality issues, and OEE drops,
- limited ability to plan interventions before breakdowns occur.
Predictive Maintenance helps connect technical data with production analysis and identify the sources of losses faster.
Why manufacturers choose explitia.PDM – Predictive Maintenance
The key benefits include:
| Fewer unexpected breakdowns | Early detection reduces unplanned downtime and protects production continuity |
| Lower maintenance costs | Components are replaced when their condition requires it; you don’t have to rely only on scheduled maintenance. As a result, spare part waste and emergency repair expenses decrease |
| Higher equipment reliability | Continuous monitoring increases transparency of machine health and aids you in preventing hidden technical issues |
| Better production planning | With predictable maintenance windows, production managers can plan orders with greater confidence and less risk |
What does the predictive maintenance implementation process look like?
The implementation of machine learning predictive maintenance with explitia.PDM includes:
Discovery and machine park analysis
Assessment of available operational and sensor data
Pilot deployment on selected machines
Model calibration and alert configuration
Scaling across the facility and user training
Our approach allows you to validate predictive maintenance software in your production environment, achieve measurable results quickly, and reduce project risk.
The implementation can start with a pilot on selected machines. After verifying results, the system can be expanded to additional lines, departments, or entire facilities.
The web-based architecture allows easy access without installing local applications.
Designed for manufacturing environments
explitia.PDM predictive maintenance software can operate as a standalone system or as part of a broader Production Portal environment, integrated with:
Production efficiency analysis and OEE monitoring
The combination of Predictive Maintenance with production efficiency analysis and OEE monitoring makes it possible to better interpret drops in availability and performance in the context of the actual technical condition of machines.
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CMMS systems
Automatic transfer of information about deteriorating equipment condition to service activities and better planning of maintenance interventions.
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Traceability
Connecting Predictive Maintenance with traceability makes it possible to analyze how machine condition affects product quality and costs, and to link technical events with specific batches, products, and process stages.
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This integration connects machine condition data with production context. You can analyze how technical issues affect output, quality, and costs.
Take control of machine reliability
If your company is looking for machine learning predictive maintenance that delivers measurable results, explitia provides predictive maintenance software built specifically for industrial production.