A Software Solution For Filters

The use of predictive maintenance is well established in a wide variety of mobile equipment as a way of eliminating downtime and, ultimately, can lead to a reduction in the total cost of ownership. Now a German company is looking to monitor machine filter status. By Ian Cameron

Mann+Hummel, whose product portfolio includes, amongst others, air cleaners, liquid and cabin air cleaners, said it is working on a software solution including sensor technology to monitor the filter status in construction and agricultural machines as well as heavy commercial vehicles.

The software means Mann+Hummel, headquartered in Ludwigsburg near Stuttgart, will offer networked filtration as an integrated component of comprehensive telematics systems used in fleet management. This fully integrated solution is expected to go into series production between the fourth quarter of quarter of 2020 and 2022.

Various sensors monitor the load status of air and cabin air filters, oil, German Furthermore, the status of the engine oil, hydraulic oil and fuel can be observed.

The measured data is then transferred from the respective vehicle to the OEM cloud where it is then passed on to the Mann+Hummel cloud. Algorithms analyze the data of the individual sensors and determine precise key figures for the predictive maintenance.

This information is prepared and returned digitally to the OEM which makes the information available to end customers, fleet operators and users in the telematics system or via an app.

Mann+Hummel said that the advantage for the operator is that it can view the status of the vehicle fleet at all times. Numerous key figures provide the operator with information on the exact condition of the fleet vehicles and indicate upcoming maintenance and repair work for individual components.

Werner Scharpf, director Product Management Original Equipment, Mann+Hummel, said, “previously fleet operators had to determine the filter status by time-consuming visual inspection which could lead to an incorrect assessment or, alternatively, fixed servicing periods maintained.

“The use of the software solution ensures that the filter is always changed at the right time. The filter service life can be efficiently exploited under consideration of changing operating conditions.

“Monitoring in real time protects against incorrect servicing for example due to a filter change made based on intuition or habit. Apart from that, the risk of exceeding the service life can be eliminated. Therefore, unplanned downtimes and failure in the field can be prevented. That saves time, reduces costs and ensures the longest possible service life for the filter.

“Information on the status of their vehicles is a valuable asset for the fleet operators of agricultural machines, construction machines and heavy-duty commercial vehicles. The smooth operation of their vehicles is only possible if the vehicles are properly maintained.”

But when is the right moment to carry out a service?

Scharpf added, “instead of relying on experience, intuition or fixed intervals, the method of predictive maintenance is increasingly establishing itself. There are many advantages to proactive measures compared to reactive measures. Maintenance times can be arranged precisely to fit in with the machine schedule and therefore it is possible to reduce or even eliminate unplanned downtimes.

“This has a positive effect on the efficiency of the vehicles and in turn reduces the total cost of ownership,” he said