Condition-based filter monitoring avoids unnecessary costs and downtime
Goal of the project
Filters have the important task of filtering out contaminants in different media and thereby protecting the plant. They are used in various areas within a production process and must be replaced regularly as they are wearing parts. If this does not happen, components will become faulty or, in the worst case, machine downtimes will occur – a nightmare for every manufacturer. However, maintenance always means machine downtime, too.
To plan the optimal use and replacement of the filters, it is possible to monitor the condition of each filter using a condition monitoring tool. This tool records current contamination using corresponding sensor data. Replacement of the filter can be planned at an early stage without having to rely on regular maintenance intervals. As a result, resources are used efficiently, downtimes are avoided and money is saved. In addition, maintenance can be optimally planned, which ensures a seamless process while taking maximum machine availability into account.
Business Case air filter
Avoidance of high
repair costs
Optimised filter replacement interval
Prevention of unplanned production downtime
On average, customers achieve:
€ 900
cost savings per year
thanks to targeted filter replacement
up to € 5000
damage prevented by
filters that were not changed
100 %
ROI from
1.8 years
Business Case water filter
Prevention of unplanned
production downtime
Optimised
filter replacement interval
Optimised
personnel deployment planning
On average, customers achieve:
75 %
Less frequent filter changes
€ 800
Savings in material and
maintenance costs per year
100 %
ROI from
2.5 years
Business Case oil filter
Avoidance of high
repair costs
Optimised
filter replacement interval
Prevention of unplanned
production loss
On average, customers achieve:
€ 300
cost savings per year
thanks to targeted filter replacement
up to € 5,500
damage prevented by
filters that were not changed
100 %
ROI from
2.5 years
Use filters optimally and consider real wear
Super simple – with the moneo software solution. The software monitors the filter and records the resulting data directly in the production process. Based on the recorded sensor data, the running time of a filter can be adjusted according to the degree of contamination, ensuring optimum filter utilisation. Permanent filter monitoring results in the optimisation of the entire process by avoiding unplanned downtimes – changing from time-based to condition-based maintenance. The responsible personnel receives the warnings and alerts directly via email or a ticket system, so that they can react quickly to changes.
Contamination and filter defects are detected promptly and expensive consequential costs for process and machine are therefore prevented. Timely detection of errors and alerting when filter replacement is necessary ensures machine availability and increases process quality. The environmental impact and the operating costs are sustainably reduced by the new maintenance strategy. moneo is also easy to use and can be adapted to customer-specific requirements without any difficulty.
Value proposition
✓ Machine availability
✓ Process quality
Condition-based instead of time-based maintenance
Filter monitoring plays an essential role in the smooth operation of production plants. Filters are an often overlooked component in production or building systems. They are usually replaced after a specific time interval, without considering the actual soiling of the filter. Machine downtime due to defective or clogged filters and unplanned production standstills due to maintenance work are the norm. This results in additional costs due to replacing the filter too early or too late.
To avoid additional costs, monitoring and visualisation of the filter taking the actual condition into account should be implemented. The aim is to replace the filter as needed to enable optimal use. moneo offers an ideal solution for optimal filter monitoring. The tool makes it possible to change from time-based to condition-based maintenance.
moneo simulation video
Cost-optimised maintenance of various filter systems
- ➔ Air filters
- ➔ Water filters
- ➔ Oil filters
Operating principle of
Air filters
Air quality in the workplace and at the respective machines is crucial. For this reason, air filters are used in extraction systems in production facilities. The resulting vapours should be extracted from the machines to prevent quality defects caused by dust and vapours. Air in the factory must also be constantly cleaned to prevent damaging employees’ health due to contaminated air. Legal regulations on air quality (in Germany: Technical Instructions on Air Quality Control) must also be adhered to. To record the air quality or soiling of the filters, pressure sensors are installed before and after the filter to ensure continuous monitoring. The corresponding tool evaluates the data and indicates necessary filter maintenance at an early stage.
Water filters
Microfilters are installed in cooling circuits to ensure that systems with heat exchangers run smoothly. These water filters take on the important task of filtering out impurities in the cooling water, thereby protecting the heat exchangers in the connected machines. With water filters, the cooling capacity of a machine is also important. If the filters are dirty, the machine or parts of the machine are no longer cooled properly, resulting in defects in the machine and the manufactured component.
Oil filters
Condition monitoring not only of air and water filters, but also of oil filters is of great importance. Oil filters are an important component in hydraulic and lubrication units. Undetected soiling leads to damage with possibly high follow-up costs. If a filter becomes clogged sooner than expected, there is likely to be an issue with the lubrication of the bearings or gears, and failure of these components is inevitable. In hydraulics, the oil must have a certain level of purity. This can only be achieved using filters installed in the return line. Appropriate filter monitoring is therefore absolutely necessary to ensure the process and operation of the plant.
With ideal use of filter monitoring, numerous factors are taken into account to prevent unplanned failures, reduce costs and use resources optimally. At the same time, machine availability is increased.
Automated maintenance interfaces
The comprehensive solution from ifm sensors in conjunction with the moneo software opens up a wide range of options and offers numerous interfaces. Data processed in moneo can be exported using different protocols.
It is possible to use data via MQTT or OPC UA in a third-party system or to transmit data directly to AWS, Azure or SAP via a specific connector.
- ✓ moneo
MQTT or OPC UA → AWS, Azure, SAP - ✓ SAP Integration
SFI (shop floor integration) → SAP PM - ✓ Alert
email notification (threshold) - ✓ Spare parts
automatic ordering through SAP - ✓ Cloud
filter monitoring possible in the cloud
By integrating ifm’s own SFI (shop floor integration) interface, a direct connection to SAP PM is possible. The on-premises solution serves as an interface between production and business levels and offers the possibility of automatically triggering further follow-up processes when limits are exceeded. The maintenance engineer receives an email notification when the specified threshold values are exceeded and warnings and alerts are sent out. This makes it possible for them to plan a suitable replacement or cleaning at an early stage and to order spare parts. Depending on customer requirements, alarms can also trigger ordering directly through SAP.
Filter monitoring is also possible in conjunction with the cloud. ifm provides the necessary interfaces to store your data in the cloud and, if necessary, use it for further analysis.
Implement filter monitoring to reduce costs
For filter monitoring, the moneo condition monitoring tool is installed centrally on a server. An IO-Link master is connected to the server via an internally secured network (VLAN). Two sensors each are installed on the water or oil filter. One sensor detects the pressure before the filter and the second sensor detects the pressure after the filter. Using these two pressure values it is possible to determine a pressure difference that describes the filter condition.
A differential pressure sensor is connected to the air filter. The most accurate pressure measurement possible is required for this. All pressure sensors feature IO-Link interfaces, which allow data transfer to an IO-Link master. With differential pressure sensors on air filters, the signal is similarly converted to IO-Link. The IO-Link master then transmits the sensor values to moneo.
moneo is responsible for pre-processing the data. This includes calculating the pressure difference, saving historical data, visualising the data and monitoring the threshold values. To monitor the filters, the respective threshold values are defined for the warning and alarm thresholds. Threshold violations are transmitted to the SAP system via the SFI interface.
System structures
- IO-Link master (VLAN)
- pressure sensor (before filter)
- IO-Link pressure sensor (after filter)
- IO-Link pressure difference sensor
- ✓ Pressure difference
- ✓ Historical data
- ✓ Visualisation
- ✓ Monitoring
- ✓ Alarm function
- ✓ Threshold violations via SFI to SAP
- ✓ Pressure difference
- ✓ Historical data
- ✓ Visualisation
- ✓ Monitoring
- ✓ Alarm function
- ✓ Threshold violations via SFI to SAP
- ✓ Pressure difference
- ✓ Historical data
- ✓ Visualisation
- ✓ Monitoring
- ✓ Alarm function
- ✓ Threshold violations via SFI to SAP
Initial success will be noticeable within just a few weeks. The sensors record the actual use and therefore soiling of the respective filters. Based on this database, it can be seen whether the filter is clogged according to the measurement results or whether the filter’s life can even be significantly extended.
✓ Downtimes are avoided and maintenance periods for filter replacement can be planned optimally.
Text taken from the original – ifm
