A new data processing architecture for multi-scenario applications in aviation manufacturing

Abstract

The development of industry 4.0 has spurred the transformation of traditional manufacturing into modern industrial Internet-of-Things. The most notable feature during this transition is the improvement of digitization and intelligence based on the massive data drives. In such a data-driven environment, the processing, storage, and utilization of the industry data get more and more important. Usually, the traditional data processing architecture runs as a one-way streamline, which cannot adapt to the different requirements of the multi-scenario application. This paper proposed a new industrial big data processing architecture called Phi architecture, which can realize many functions such as batch data processing and stream data processing, distributed storage and access, and real-time control. Compared with other data processing architecture, the Phi architecture combined with edge computing and feedback control has the ability to deal with the different demands in aviation manufacturing. Next, the new architecture is designed for microservices pattern, which improves the flexibility and stability of the architecture, and makes it independent operated in multi-scenarios, such as state monitoring of workshop, adaptive data acquisition, feedback control, and user-oriented information classification. As a proof of concept, the architecture has been tested in a simulation digital manufacturing workshop. The results verify the improved effectiveness of the Phi architecture on the data feedback control and real-time processing. And, the development of microservices architecture greatly improves the efficiency, adaptability, and extensibility of the manufacturing process.