HOLISTIC - SIMPLICITY - USABILITY
Holistic solutions for modern plant maintenance
GIB combines the world of automation and mixed reality to provide consistent communication from the sensor to the SAP system
In a world in which almost everything can be measured and evaluated, it is important to make the right information available at the right time, in the right place, suitable for the respective user. The integrated solutions from GIB make this possible and open up new ways for optimized plant maintenance in the most modern way.
Well-functioning plant maintenance relies on ensuring that employees are always provided with the relevant data and information at the right time and in the right place, depending on their respective roles in the company. Only in this way can they react in the best possible way to incidents in the plants. To meet this requirement, a solution is needed where all business processes are networked. The IoT tool, “Shop Floor Integration” (SFI) from GIB, closes the important gap between “Operational Technology” (OT) and “Information Technology” (IT). By means of intelligent systems such as the KPI-Tower and the GIB Dispo-Cockpit Planning, it is also possible to monitor the processes based on key performance indicators and optimize the production planning. Plant maintenance thus becomes integrative and company-wide, quickly and effectively from the production manager to the maintenance worker.
KPIs at a glance
This can be illustrated by the following scenario: The KPI tower enables the production manager to always keep an eye on the key performance indicators. Thus, thanks to the established Early Warning System that monitors the technical assets continuously, he can detect an impending standstill caused by a bottleneck machine in time and initiate specific countermeasures without which a major order could not be completed on time. Based on this real-time information, a plant maintenance process is triggered automatically and can be processed efficiently. The intelligent use of sensors which are connected to downstream systems can effectively monitor the condition of the system and automatically initiate follow-up processes in the SAP ERP system. This process information from the SAP ERP system together with the sensor data from the Early Warning System provide a comprehensive view of the pending plant maintenance task.
Optimal machine utilization
The maintenance employee receives the problem message with high priority on his tablet. With just a few clicks in the GIB “Mobile Maintenance App,” he will gain all relevant context information on the affected machine. For example, he receives an overview of the previously reported problem cases and orders for the machine on a timeline. He can thus deduce the possible cause of the deviating sensor data from this and check the availability of any required spare parts. Using GIB’s comprehensive solutions, he can see when the spare part is available and schedule the repair so that it does not affect the production process. This ensures optimal utilization of the machine.
Arriving at the machine, he picks up his tablet again. The mixed reality function and the use of the tablet camera enable him to call up more information about the machine. He is also able to view the machine in more detail on his tablet via 3D display. For example, he can rotate it and display areas that are difficult to access and that are not easily visible with the naked eye. The plant maintenance technician has access to a detailed repair manual via the app and can execute the repair step by step. Thus, the onset of wear on the bottleneck machine is quickly resolved and impending failure averted. The plant maintenance technician documents the repair in the system. The information message is automatically transmitted by the SFI to all relevant areas of the SAP system for further processing, e.g., in updated KPIs that clearly show the production managers that their production is still going forward as planned. The standstill has been averted, the production of the important major order is ensured.