Shopfloor machinery requires periodic preventive maintenance to operate under the predefined industrial protocols and produce the parts within the expected limits. On the other hand, the continuous operation of the machines leads to a degradation of their internal tools. The main goal of the Z-BRE4K solution is to apply algorithms that will be able to predict the remaining useful lifetime of a certain tool between the intervals of scheduled maintenance. The other main motivation of the implementation of the Z-BRE4K solution is to simulate the processes over the complete production chain and monitor, based on sensorial data, the interaction between the tools and the machines in the assembly line and the product family.
Z-BRE4K combines all separate data and gathers it to the prediction of the remaining useful lifetime component where the component implements algorithms to compute the expected tool life and compare with the results given by the operators, based on their experience. The computed expected tool life is more accurate than the previous one and the prediction outcome is sent to the Decision Support System component which creates a suggestion for the production managers or the tool workshop operators. The suggestions are based on predefined rules by production managers and can create a new
Maintenance Plan, which will include new maintenance orders for the tool, based on the prediction of the expected tool life.
PdM helps this end-user to improve the uptime of their tools in the live production while reducing tooling costs, man-hours and unnecessary tooling parts stock.
| Country: | BE |
- Not specified
PHILIPS supports the idea of predictive maintenance, “listening to the machines” and understands that the key to success is close contact between technology providers and experts where data integration/architecture and machine learning are both very important projects.