Identifying repeating patterns in IEC 61499 systems using Feature-Based embeddings

Cyber-Physical Production Systems (CPPSs) are highly variable systems of systems comprised of software and hardware interacting with each other and the environment. The increasing integration of technologies and devices has brought an unprecedented level of automation and customization. At the same time, it has also increased the efforts to maintain highly complex and heterogeneous systems. Although engineering practices support the reuse of common components to ease the development and maintenance of the systems in different projects, the identification of common components is still manually performed, which is a time-consuming, error-prone task. In this paper, a novel approach identifying repeating patterns in CPPSs based on artificial intelligence techniques is presented. This approach allows finding exact and similar components to support the CPPS design. Furthermore, it enables the maintenance of common components by reusing predefined types thereby reducing development effort. We implemented and evaluated our approach in an industry case study on developing CPPS control software with IEC 61499.