In the last few years, the potential impact of big data on the manufactur- ing industry has received enormous attention. This chapter details two large-scale trials that have been implemented in the context of the lighthouse project Boost 4.0. The chapter introduces the Boost 4.0 Reference Model, which adapts the more generic BDVA big data reference architectures to the needs of Industry 4.0. The Boost 4.0 reference model includes a reference architecture for the design and implementation of advanced big data pipelines and the digital factory service development reference architecture. The engineering and management of business network track and trace processes in high-end textile supply are explored with a focus on the assurance of Preferential Certification of Origin (PCO). Finally, the main findings from these two large-scale piloting activities in the area of service engineering are discussed.
Keywords: Reference architecture · ISO 20547 · ISO/IEC/IEEE 42010 · DIN 27070 · Sovereignty · Data spaces · Track & Trace · Blockchain · FIWARE · Virtual commissioning · Testbed · Trial · Business networks 4.0 · SUMA 4.0 · Intralogistics
Excerpt from: Lázaro O, et al. (2021) Big Data-Driven Industry 4.0 Service Engineering Large-Scale Trials: The Boost 4.0 Experience. In: Curry E., Auer S., Berre A. J., Metzger A., Perez M. S., Zillner S. (eds) Technologies and Applications for Big Data Value. Springer, Cham.