What is PdM?

A chart shows maintenance progression from reactive to proactive: Responsive maintenance, Preventive maintenance, Condition-based maintenance, Predictive maintenance (Uses AI/big data for fault forecasts), and Reliability-centered maintenance

Predictive maintenance (PdM) is a planned strategy that reduces downtime, predicts failures, and extends equipment life based on time and usage.

System architecture

Powered by data, using algorithms and fused with AI, expert systems and failure cases are combined to build models that accurately predict faults across industries and equipment.

Digital manufacturing data flow: Production data, Data historian, Process flows, ERP, Quality, and MES inputs feed the Data store. AI predictive analytics processes data for fault prediction, generating Dashboards and Alerts.

Key technologies

Sensor

Accurate sensors capture real-time equipment data for PdM.

IoT

Collects and transmits sensor data to enable timely analysis.

Big data analysis

Analyzes operational data to reveal patterns and predict faults.

AI & ML

Detect anomalies and recommend optimal maintenance actions.

Main advantages

Reduce 25% to 30% of maintenance costs
Increase 20% to 25% of productivity
Reduce 35% to 45% of equipment/process downtime
Reduce 20% of material costs
Reduce 20% of Reduce maintenance frequency
Data source

MIR Industry

Markets

Power and energy

Petrochemicals

Manufacturing

Medical devices

Power and energy

Petrochemicals

Manufacturing

Medical devices

Key components and manufacturers

Advantech Ethernet & Communication Modules 
Banner Engineering Vibration Sensors 
Phoenix Contact Controllers 
Schneider Electric Motors & Drives 
Siemens HMI Displays & Panel PCs 
TDK-Lambda Power Supplies - DIN Rail Mount 
Advantech
Banner Engineering
Phoenix Contact
SchneiderElectric
Siemens
TDK-Lambda