As factories become mobile, machines will physically move inside a factory or to another site. Current network infrastructure does not match the associated requirements because wired connections and fix subnets as well as fix routes cause high effort for each adaptation. Using NFV technology and the 5GTANGO platform, the factory network will be raised to a new level of flexibility.

The smart manufacturing pilot focuses on three use cases for modern factories: create an innovative, flexible factory network and analyze the operational data, machine data, and process data (O/M/P data) gathered from the machines; detecting and containing threats; and enable augmented reality (AR-)based support for machine maintenance and repairs.

The following use cases were defined during a face-2-face meeting at Weidmüller premises in Detmold. The participants gained many insights of a manufacturing process by visiting one of Weidmüller’s factories and created a time schedule for the development of needed components. Many aspects of the use cases will be tested and evaluated in demonstration setups during the final year of 5GTANGO.

Use Case 1: Machine setup

Figure 1 Use Case 1: Machine interconnection


A company decides to build and install a new site and/or machine park. Once the construction work is done and physical machine park is built, a 5GTANGO PoP is installed in a small, co-located data center, e.g., consisting of a couple of COTS servers. When these servers and the 5GTANGO installation are ready, an edge analytics network service is deployed which aggregates operational data, machine data, and process data (O/M/P data) generated by that machine park and pushes it to the cloud backends of the company. The NFV-based machine interconnection is shown in Figure 1. It is assumed that all machines that should be integrated are IP protocol compatible; other machine interfaces are beyond the scope of the project but can be connected using the appropriate bridging technologies to translate between protocol stacks.
The main aim of all improvement in manufacturing is to increase the efficiency of production. Therefore, all available machine data will be collected and analyzed. This includes information of the production process delivered by the machine itself as well as sensor data, coming from Industrial Internet of Things (IIoT) sensors. IIoT enables this usage for older machines as well retrofitting. As a first step in the analysis process data should be processed locally, close to the machines (edge computing). The aim is to find issues as fast as possible to avoid larger damage to a machine. In this case a low latency is required. Long-term analysis is taking place in a cloud environment.


Use Case 2: Threat defense – containing a threat

Figure 2 Use Case 2: Threat defense

Industry networks must deal with a lot of threats, e.g., industrial spying. To protect operation-critical infrastructure from those threats, (security) network functions, such as intrusion detection systems (IDS) and firewalls (FW), are used and deployed in different locations of the network. If such a security function detects malicious activities, it should not only raise alerts, but also trigger active counter measures. One example for this is to isolate the machine under attack from the rest of the factory network to further investigate it. This is shown in Figure 2. All data transmissions of this machine must stop immediately, the information might be corrupted and is unusable for any analysis. Here 5GTANGO can help by automatically reconfiguring the network service(s) that interconnect the machine with the factory network and thus put the machine to quarantine.

Such re-configuration tasks are complicated in existing factory networks and cannot be automated. The use case shows how 5GTANGO, with its advanced programmability features, e.g., FSMs and SSMs, can help and implement fully automated counter-measures triggered, e.g., by an IDS alarm.


Use Case 3: AR-based maintenance

Figure 3 Use Case 3: AR-based maintenance

Even though 5GTANGO allows to virtualize many parts of a factory network, the production machine, remain physical entities which require regular maintenance, encounter malfunctions and might even fail completely. If this happens, engineers are required, who need a deep understanding of the machine, to repair the machine and bring it back to production. A recent trend to simplify such maintenance tasks is using augmented reality (AR) systems, such as smart glasses, to directly provide the engineers with additional information. This information can contain technical details about the machine to be fixed, e.g., technical documentation but even dynamic data, such as real-time machine data, helping an engineer to find the cause of the problem. Those advanced supporting technologies introduce special requirements to a factories network. They might, e.g., require high bandwidths that exceed the normal bandwidths available in a machine park's network or have additional isolation requirements, e.g., if the maintenance tasks are delegated to third party companies that should not be directly connected to the production network. The steps for AR-based maintenance/repairs are shown in Figure 3.

5GTANGO can help here with different aspects. First, it enables the dynamic, on-demand deployment of the network functionalities required by the mentioned supporting mechanisms, e.g., the network to connect the smart glasses and serve them with real-time machine data. Second, proper isolation of those on-demand services from the regular production services becomes possible. Both capabilities can be achieved by using network slicing. One Slice will deal with regular machine operations, while the other can be created on-demand anytime a AR-based maintenance is required.


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