Taking this into consideration, OCME uses the project lifetime to focus on the wear prediction of the plastic film cutting module, which forms part of its shrink-wrapping machine named VEGA. In particular, the objective of the model learning algorithms is the cutting blade which physically cuts the plastic film from the unwinder reels at the right length to be wrapped around the producing packs.
Although this is obviously not the only critical component of the machine, surveys conducted with final customers have revealed that it is considered a component perceived as a weak spot of the machine.
This is mainly due to the following reasons:
- The blade is, for safety reasons, situated in a mechanical cage which makes it invisible to exterior inspection
- Visual evaluation of the blade life time it is almost impossible and it is also difficult to estimate the cutting quality of the plastic film
- Placed under the main machine conveyor, the cutting unit is not easily accessible which affects not only the normal maintenance duties, but also the time required to replace the blade
Moreover, OCME aims to have a reliable indicator for machine wear which doesn’t rely on additional sensors to be placed in the unit which, from a mechanical point of view, is already quite complex in itself.