Condition Monitoring

Condition Monitoring explained simply

Imagine your machine was a sensitive health tracker – it constantly measures symptoms such as temperature, vibrations or oil quality and tells you in good time: “Listen, something is coming up.” That is exactly what Condition Monitoring is: sensors continuously monitor the condition of your equipment and give early warning if something is wrong – before it comes to a standstill. This way you keep an overview and save yourself expensive surprises.

Background information

Condition Monitoring is the process of continuous or periodic collection and analysis of physical parameters – such as vibrations, temperatures, pressure or oil condition – to assess machine condition. The aim is to detect early signs of wear or faults in order to avoid unplanned failures and increase plant availability.

Typically, this involves three steps:

Condition acquisition – sensors measure the current actual condition.
Condition comparison – values are compared with target or limit values.
Diagnosis – in the case of deviations, causes are analysed and appropriate maintenance measures initiated.

Condition Monitoring is therefore an essential basis for Predictive Maintenance.

Technological methods in detail

Condition Monitoring draws on a wide range of methods – depending on the type of machine and relevant stress:

Vibration analysis (Vibration Monitoring): Indispensable especially for motors, pumps or gearboxes. Through frequency analyses (e.g. Fast Fourier Transformation, FFT), imbalances, bearing damage or gear problems can be identified at an early stage.
Thermography & temperature measurement: Infrared cameras or sensors reveal hotspots that indicate overload, friction or electrical defects.
Oil and lubricant analysis: Wear becomes visible through particle and chemical analysis of oils before it becomes mechanically critical. This makes it possible to plan filter or oil changes in a targeted manner.
Acoustic emission & ultrasound: Special microphones capture high-frequency sound waves that indicate cracks, friction or cavitation – often before they are audible to the naked ear.
Motor current signature analysis (MCSA): Electrical patterns in motor current show insulation problems, phase imbalances or winding faults.
Performance monitoring: Flow, pressure, speed or energy consumption are continuously compared with ideal values in order to detect gradual efficiency losses.

The more methods are combined, the more accurate the overall picture of the machine condition becomes – especially in complex industrial plants.

System architecture & integration

For Condition Monitoring to function reliably, a scalable system architecture and seamless integration into existing production and IT landscapes are required:

Sensors: At the beginning are robust sensors (e.g. vibration sensors, thermocouples, oil particle measuring devices) that continuously collect data.
Edge vs. Cloud Processing:
- Edge Computing processes data directly at the machine, ideal for real-time decisions or when low latency is required.
- Cloud Computing makes it possible to store large amounts of data, carry out historical comparisons and use AI algorithms across many plants.
Communication protocols: Industrial standards such as OPC UA, MQTT or Profinet ensure that data from heterogeneous machine environments can be brought together.
IIoT platforms: Higher-level platforms aggregate the data and visualise it in dashboards. There users can monitor conditions, configure alarms and analyse trends.
Integration into MES/ERP systems: Condition Monitoring delivers the greatest benefit when linked with production planning (MESManufacturing Execution System - software for real-time control and monitoring of entire production.) and resource management (ERP). This way maintenance orders are generated automatically and embedded into existing processes.

The combination of sensors, intelligent data processing and cross-system integration makes Condition Monitoring a key building block of the Smart Factory.

Condition Monitoring