Intelligent condition monitoring for driven tools in operating condition

Steckbrief

Eckdaten

Duration:
01.11.2017 to 30.10.2020
Organizational Unit:
Chair of Machine Tools, Machine Technology
Funding:
German Federation of Industrial Research Associations AiF
Status:
Running

Research partner

  • WTO

Contact

Telephone

work Phone
+49 241 80 27442

E-Mail

 

The central element of driven tools is a rotating spindle which is mounted opposite the housing. This coupling point between a static housing and a rotating shaft is realized by high-precision bearings. Such elements are subject to considerable loads as they absorb both axial and radial process forces. The service life of this bearing arrangement fluctuates between a few months and a few years, depending on the load. It can be seen that the main cause of failure is bearing damage resulting from wear.

This wear, which occurs in the course of everyday use, leads to increased bearing clearance in the course of the product life cycle, which is negatively reflected in the machining result. Although a given tool wear can often be detected acoustically, it cannot be quantified clearly and reproducibly due to the surrounding background noise. Even if all surrounding disturbance factors are omitted, no acoustic threshold value can be determined which is assessed solely by the operator. Therefore, in the final analysis, only the machining result can be used as an indication of wear, which, due to the time delay between cause and effect, can lead to considerable rejects and also to a production standstill.

The solution to the problem is permanent monitoring of the condition. Instead of the real wear condition, preventive maintenance is often used in industrial environments. In this context, the user uses table-based documentation, whereby a less meaningful forecast of the actual tool condition is derived from the recorded operating hours. The aim of this project is to assess the wear condition during the entire life cycle of the tool. This is to be recorded and evaluated via an intelligent condition monitoring system, which is being developed together with the company WTP, in order to replace the AGW in the correct condition and thus avoid longer downtimes and scrap production.