Predictive Maintenance Makes Maintenance In The Rubber Industry More Efficient

Rubber compounds are manufactured in the rolling mills of Gummiwerke Kraiburg GmbH & Co. KG, among others. There, hydraulic Hägglunds radial piston motors from Bosch Rexroth move the rolling mills, which homogenize and roll out the rubber compounds. When Kraiburg wanted to introduce a new rolling mill into the machine park, the focus was on a future-oriented maintenance concept and high energy efficiency.

"Since our rolling mills run almost entirely in three shifts, machine availability plays an extremely important role," explains Günther Beisser, who works in Kraiburg's system planning. "After all, failures in a single machine delay the entire production process and ultimately result in extremely high costs." To prevent this, machines are usually serviced after a certain number of operating hours. The company wanted to find out how that can be done differently in the new rolling mill and therefore took a step towards the future in terms of maintenance.

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Act with foresight

With offers for condition monitoring and predictive maintenance, Bosch Rexroth wants to offer a wide range of options that can be designed individually. The possibilities range from equipping the systems with intelligent sensors and components to implementing condition monitoring at the customer and analyzing the data with Bosch Rexroth.

Kraiburg relies on Odin (Online Diagnostics Network) from Rexroth for its new system. The core idea of ​​this service package is to carry out maintenance work through the interaction of sensors, cloud-based applications and machine learning methods - before a standstill occurs. At Kraiburg, sensors record data on the oil tank, pumps, motors and electrical drive in the system. Among other things, temperatures, oil levels, volume flows and pressures are measured. The data is sent to Bosch Rexroth and analyzed there.

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Sophisticated monitoring

After the installation of the new rolling mill, Odin collected data on all monitored components in a training phase. On the basis of this data, an algorithm determined a “health status” for the rolling mill. After the learning phase, Odin continuously monitors this rolling mill health index. If only a single measured value breaks out of the tolerance band, this does not necessarily lead to a warning, since wear can rarely be detected with a single signal. However, if the health index deteriorates because the data of several sensors change, the system warns - even if the individual changes are within the defined limits.

The Health Index not only shows the condition of the monitored unit, but also gradual changes in the upstream and downstream components. If movements take longer over time or require more force, this is an indication of wear in the mechanics or hydraulics. Odin provides relevant information and helps to create concrete recommendations for action. (br)

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