IPM@GWC aims at apply innovative predictive maintenance and value stream mapping approaches, to prove and quantify the benefits on a production system´s flexibility, costs and performance.
Therefore, two synergising experiments are proposed: Within the 1stexperiment a predictive maintenance model, which gathers, analyses andutilities process and product data of a CPPS is implemented by appropriating the BEinCPPS Reference Architecture. The model consists of algorithms that derive predictions of future OEE and future set-up times, which leads to better decision making, as well as automatized planning of maintenance activities.
The influence of those predictive maintenance actions on the OEE and other KPIs are evaluated by value stream analysis in the 2nd experiment. The 2nd experiment combines the Fraunhofer VSM tool VASCO and the INEGI’ MSM methodology/SW module to generate static and dynamic value stream maps.
This experiment has been supported under the second open call of BEinCPPS project.