Z-BRE4K: Aftermath of first year as project enters in its strategic phase


    Z-BRE4K, the EC-funded project that aims at reaching zero downtimes caused by unexpected breakdowns in manufacturing plants, is facing its strategic phase after the completion of year one activities.

    Starting from fall 2017, the project partners of Z-BRE4K have on the one hand worked on the specifics of the three use cases and came up with a list of user requirements that the several Z-Strategies will cover. On the other hand, project’s technical partners have both dealt with the definition of the Z-BRE4K architecture and have further developed the different components: data acquisition and condition monitoring solutions, machine learning simulators for predictive maintenance, IDS and FIWARE connectors together with semantic modelling, visualization framework and decision support system.

    These activities have had a twofold objective: predispose the correct operation of each component within the different use-cases and simultaneously permit their further integration in Z-BRE4K’s architecture. In this regard, year 2 of Z-BRE4K project constitutes the cornerstone of the project as the software integration is taking place in the following months.

    Concerning the three Demo cases, relevant operations have already taken place in the packaging sector (SACMI & CDS), automotive sector (GESTAMP) and home appliances (PHILIPS) use cases.

    SACMI and CDS have already analysed the FMECA related to their use case, together with the definition of the sensing technologies and alarms involved for each failure mode. Moreover, Holonix has installed the data acquisition Gateway in five compression moulding machines and successfully connected to FIWARE so that online stream is already available for data analysis.

    PHILIPS use case, after the definition of the failure modes and tooling depreciation aspects, has concentrated the effort in developing an IDS connector, building several predictive maintenance algorithms and setting the rules of the DSS implemented. The next step is the initial evaluation of the solution provided by Philips.

    GESTAMP use case has worked on the evolution of chassis products manufacturing equipment such as stamping press, welding power sources and metrology quality inspection inline equipment. The main aim of all these equipment modifications is to gather more machines information to be used for predictive maintenance strategies development. In this regard, new strain gages have been installed in the stamping press and a broker and an Ad-Hoc solution have been implemented to gather real time welding signals of the power sources. On the other hand, a new IR sensor is being developed to achieve online quality inspections that might be related to system mal functions and therefore, maintenance strategies. Finally, the laser quality inspection system has also been instrumented in order to develop maintenance strategies.

    In short, Z-BRE4K will face a critical stage during 2019, as the machine-learning related activities will be performed at full throttle with continuous data stream, while the different components of the Z-BRE4K platform get integrated and tested prior its full deployment on the shopfloor.

    INOVA+ is a partner of the project. For more information check the official website of the Z-BRE4K project.