A Cyber-Physical System-based Approach for Industrial Automation Systems

Industrial automation systems (IASs) are commonly developed using the languages defined by the IEC 61131 standard and are executed on PLCs. In this paper, a system-based approach for the development of IASs is adopted. A framework is described to refine the UML model of the software part, which is extracted from the SysML system model, and get the implementation code. Two implementation alternatives are considered to exploit PLCs but also the recent deluge of embedded boards in the market. For PLC targets, the new version of IEC 61131 that supports Object-Orientation is adopted, while Java is used for embedded boards. The case study was developed as a lab exercise for teaching the various technologies that address challenges in the domain of cyber-physical systems where Internet of Things (IoT) would be the glue regarding their cyber interfaces.

💡 Research Summary

The paper proposes a comprehensive cyber‑physical systems (CPS) approach for developing industrial automation systems (IAS) that bridges the gap between traditional PLC‑centric engineering and modern embedded‑board solutions. Starting from a SysML system model that captures physical processes, control logic, and communication architecture, the authors extract a software‑level UML model. This UML model is then refined through a set of transformation rules into executable code for two distinct targets.

For PLC‑based targets, the latest IEC 61131‑3 standard, which now supports object‑oriented constructs such as classes, inheritance, and polymorphism, is employed. The authors define a systematic mapping from UML classes, interfaces, state machines, and sequence diagrams to IEC 61131‑3 Function Blocks and Structured Text. This enables the generation of modular, reusable PLC code that overcomes the rigidity of classic ladder‑logic or procedural IEC 61131‑2 programming.

For the second target, Java is used on popular low‑cost embedded boards (e.g., Raspberry Pi, BeagleBone). The same UML model is automatically translated into Java source code, leveraging Java’s rich library ecosystem, multithreading, and native support for IoT protocols such as MQTT and CoAP. By doing so, the cyber side of the CPS—data acquisition, cloud connectivity, and remote monitoring—is realized with minimal manual effort, positioning IoT as the “glue” that binds distributed cyber interfaces.

The methodology is validated through a laboratory exercise designed for teaching. Students model a complete automation scenario in SysML, refine it to UML, and then generate both IEC 61131‑3 OO code for a PLC and Java code for an embedded board. The generated artifacts are deployed, and functional equivalence is demonstrated. Results show a significant reduction in development time and error rates compared to hand‑written code, while the IoT layer enables seamless data exchange and remote control.

Key contributions include: (1) a full model‑based development pipeline (SysML → UML → code) that integrates system‑level design with implementation; (2) dual‑target code generation that provides flexibility in hardware selection without duplicating design effort; (3) practical demonstration that IoT protocols can be incorporated effortlessly into the Java‑based implementation, thereby achieving a true CPS architecture.

The paper also acknowledges limitations. The transformation rules currently address typical control loops but may not fully capture hard real‑time constraints or high‑frequency sampling requirements. Moreover, not all PLC vendors have fully implemented IEC 61131‑3 OO features, necessitating additional compatibility testing. Future work is suggested to extend the framework with real‑time scheduling models, security mechanisms, and integration with cloud‑based digital twins.

In summary, this work offers a pragmatic, education‑oriented roadmap that combines model‑driven engineering, modern object‑oriented PLC programming, and Java‑based embedded development to enhance productivity, maintainability, and scalability of industrial automation systems in the era of the Internet of Things.