Plug & Play based on semantic Information Models with AML

Plug-and-play integration in industrial automation requires more than standardized communication interfaces. It also depends on machine-readable information models that describe the structure, capabilities, interfaces, parameters, and visual representation of equipment in a consistent and reusable form [1]. AutomationML provides a suitable foundation for such models by combining hierarchical plant structures, object-oriented libraries, semantic references, and standardized data exchange within a single engineering format.

This contribution presents a practical application of AutomationML in the engineering of Process Equipment Assemblies (PEA) [2] according to the Module Type Package (MTP) [3] concept. The underlying challenge is that the information required for an MTP is typically distributed across P&IDs, functional specifications, HMI configurations, spreadsheets, and automation projects. Without dedicated engineering support, this information must be transferred manually into complex AutomationML structures, which require detailed knowledge of both the standard and its underlying information model.

The presented approach uses a visual editor that allows engineers to describe a PEA through domain-specific concepts such as HMI elements, services, parameters, and alarms. These user interactions are continuously mapped to an MTP-compatible AutomationML model in the background. AutomationML therefore acts as the semantic backbone of the engineering process, while the complexity of the exchange format remains hidden from the user.

The resulting AutomationML model is not treated merely as a final export document. Instead, it serves as a consistent source of engineering information for subsequent activities. It can support the generation of MTP files, the derivation of automation structures and data points, the creation of manufacturer-specific engineering projects, and the generation of executable control code.

The contribution discusses how application-oriented editing, semantic libraries, model validation, and model transformations can make AutomationML usable beyond expert-driven data exchange. The case study demonstrates that AutomationML can connect process design, automation specification, HMI engineering, and implementation within one coherent information model and thereby provide a practical basis for scalable plug-and-play engineering.

Keywords: Modular Automation; Semantic Modeling; Module Type Package