Simple application of data-driven services for SMEs
Machines are constantly generating data, for example by measuring temperatures and speeds. Collecting, processing and using this data is becoming increasingly important for companies. By analyzing data, companies can identify errors, improve production processes, increase the transparency and efficiency of supply chains and offer consumers additional services. The problem is that small and medium-sized companies in particular often lack the technical expertise and suitable IT platforms that need to be specially tailored to the individual machines or components. The use of these so-called data-driven services is therefore associated with a lot of effort and costs that are often disproportionate to the expected benefits. This is precisely where the it’s OWL project ‘Industry 4.0 ecosystem for the automated use of data-driven services (I4.0AutoServ)’ comes in: The aim of the project is an Industry 4.0 ecosystem for the automated use of data-driven services, in which companies can implement product-service systems faster and more cost-effectively.
The target Industry 4.0 ecosystem consists of assets, such as machines and systems in the production environment (store floor), and their interoperable digital twins. If the data-driven services are also equipped with a digital twin and their requirements are described there, capabilities and requirements can be matched automatically. In addition, services can be distributed, used and maintained across these levels in an automated deployment by automatically matching their requirements and the capabilities of the individual IT levels (device, edge, cloud). This matching is based purely on the digital twins of the assets in the ecosystem and massively facilitates the use of data-driven services or, in some cases, makes them possible in the first place.
The fact that this approach not only works in theory was demonstrated in practice at the Hannover Messe from April 22 to 26, 2024. An intralogistics scenario from project partner Remmert was demonstrated here, in which driverless transport vehicles (AGVs) move goods from one station to the next in a production or warehouse environment. As the real AGVs and warehouse facilities are too large for the trade fair presentation, they were represented by AMiRo robots from Bielefeld University, which traveled on a parkour between two warehouse areas (see image above).
Intuitive user interface for efficient matching
All store floor assets (SFAs), i.e. the AGVs and warehouse systems, can be displayed in a graphical user interface (GUI) (see image above). When an SFA is selected (e.g. an AMiRo), the matching process is triggered, which provides a list of matching data-driven services. Services that are not suitable for the SFA are grayed out. It should be emphasized here that no information about the SFA or services needs to be stored in the GUI in advance. This comes from the respective digital twins in the form of the Industry 4.0 Asset Administration Shell (AAS). In the next step, a service (e.g. anomaly detection) can be selected, whereupon the matching process determines the appropriate computing resources. This is followed by training (if required) and the provision and execution of the selected service. As soon as a service is applied, a data pipeline is automatically established from the SFA (AMiRo) to the computing resource (edge component) on which the service (anomaly detection) is executed. The results are then immediately displayed in the GUI. The data was recorded on a straight test section of the parkour so that a reference movement was available for anomaly detection. The anomalies were caused live at the exhibition stand by project staff or visitors, for example by using adhesive tape on the wheels of the AMiRo to create an imbalance in the drive. If an anomaly is detected, the AMiRo can then drive itself into maintenance and a new AMiRo is provided.
Live demonstration at the Hannover Messe
The demonstration at the OWL joint stand at the Hannover Messe represented a milestone in the project, with all the developed parts interlocking and providing proof of the feasibility of the approach as an overall system. The trade fair appearance made it possible to gather direct feedback on the implementation to date and suggestions for further development, with visitors pointing out various usage perspectives. As the project progresses, the final details of the implementation will have to be worked out. For example, the capabilities and requirements of the services and the SFA for scaling should be described as comprehensively as possible, but at the same time they must be specific enough to carry out the matching.
How companies from OWL benefit from the project
On completion of the project, the results will be made available to small and medium-sized companies in OstWestfalenLippe. For example, as an open source solution that can be adapted to the needs of companies at a low threshold. This would allow production managers to click to see which services can be applied to which SFA in their production environment, e.g. anomaly detection or determining the remaining service life of components. The desired services are then executed with a click and the results are displayed. In addition to Bielefeld University (Cognitronics & Sensor Technology Group), Paderborn University (Chair of Dynamics and Mechatronics) and the Fraunhofer IOSB-INA Institute for Industrial Automation in Lemgo, three companies are involved in the I4.0AutoServ project: the drive and automation supplier Lenze, the specialist for industrial connection technology, automation and digitalization Weidmüller and Remmert – a specialist for fully automated warehouse technology, intelligent logistics software and economical automation solutions for long goods and sheet metal.
