Industry 4.0 Living Lab #2

The second Industry 4.0 Living lab will validate the IoT-NGIN federation framework in real-life applications implemented ABB facilities (Trial#5) in Pitäjänmäki, Helsinki.

In Pitäjänmäki (Helsinki), ABB manufactures electrical accessories and electrical equipment. As there are thousands of product variations, manufacturing is highly automated utilizing robotics and assembly automation. Private 5G network in high-power AC-laboratory is used to connect powertrains signals with high bandwidth and low latency and to connect sensors to edge servers enabling digital twins. This technological testbed enables advanced proactive diagnostics and optimisation of energy efficiency and productivity and will be used for customer use case demonstrations.

Use case Applications

  • Human-centred safety in a self-aware indoor factory environment. IoT-NGIN will provide a high-precision IoT localization layer merging real-time localizations obtained from Ultra-Wide Band (UWB) sensors and a solution providing Visible Light Positioning (VLP). In addition, safety cameras will be deployed to monitor areas with reduced visibility. A high-speed and ultra-low latency wireless access network, which supports quick notifications and massive data uploads, will be also deployed based on a combination of 5GNR technology, using private spectrum at 3.5 GHz, and high-speed Wi-Fi using unlicensed spectrum at 5 GHz. The data from the sensors provide a full description of the environment and how it is changing. It allows to model moving objects and skeletonize human bodies to detect the position of each body part and build a “safety shell” around it to ensure human-centred safety.
    In ABB facilities, the data will be used to monitor sub-assembly location and movement, and to optimize production workflow.
  • Human-centred Augmented Reality assisted build-to-order assembly. Based on contextual-IoT intelligence, high-precision IoT localization, RFID sensors and camera analysis, IoT-NGIN will be able to recognize the components and the stage of the assembly process using local ML trained models and provide assistance and guided instructions, displaying the procedure and next stage of the customizable manufacturing, either using AR classes, mobile devices or small industrial screens. In ABB facilities, the system will be used for employee training.

IoT-NGIN as Differentiator

  • Combine edge (remote) and semi-autonomous (local) federated ML decision on constrained resources, enabling safe operation and build-to-order assembly even in case of network error, loss of connectivity or weak coverage
  • Monitoring employees’ body positions and stress levels to ensure workplace safety through federated ML
  • High-Accuracy Indoor Positioning (HAIP) deployment enables production optimization
  • Digital powertrain optimization (production, process, asset and energy) in brown field factories