Standardized, open information models are essential for structuring large amounts of data and adding further descriptions to a variable. A new white paper describes their role within PI technologies and shows the way to implement Industry 4.0 applications.
The classic communication landscape consists of cyclic data exchange between controllers and field devices, as well as data exchange for parameterization, monitoring, and diagnostics of the field devices. Now, new information channels are being added. These include, for example, an additional communication path for data-driven advanced asset management and data analytics. However, this vertical communication requires additional channels to the devices and a machine-readable description of the data.
Information models make the data from the devices, machines and plants understandable for the IT applications. For this purpose, the data is supplemented by descriptions that contain the properties and the relationships between these data. The data thus becomes information that can be interpreted by machines. This provides very easy access to the data and saves a lot of time when integrating new components. Thanks to the uniform semantics, the quality of the data also increases. The information models also considerably simplify the coupling of IT applications to the plants.
OPC UA-based Information Models
Industrial communication, above all PROFINET and IO-Link, offers all the prerequisites for vertical communication. Therefore, it is obvious to integrate the necessary information models into the canon of PI technologies in such a way that a seamless implementation of the existing device technology is made possible. Importantly, vertical communication does not affect control tasks and it is equipped with the necessary IT security measures.
On the Way to Digital Transformation
PI launched various activities and collaborations with relevant organizations in the working groups to further develop its technologies in line with Industrie 4.0. For PROFINET and IO-Link, further mappings in OPC UA are currently being developed in order to use device and diagnostic data in IT applications without much effort. In particular, it is important to design the interaction between PROFINET and the OPC device integration models in such a way that it is easy for the user to get started. This makes it easier to implement data analytics and predictive maintenance scenarios or asset management in the plant, for example.
Machine-interpretable semantic descriptions can be generated for all data provided by existing devices and components using PI technologies. Finally, the more than 50 million devices in the field that have a PROFINET interface open up access to the valuable data. Standardized, open information models are already available for this data and its semantic descriptions. Further developments, especially of OPC UA Companion Specifications, complete the required scope of models. PROFIenergy can be considered as a successful example. Already today, the profile provides a means to collect energy measurement values in factories across manufacturers and thus to make them available to other applications, e.g., an energy management app, without much effort. Information models are an essential contribution to digital transformation and the implementation of smart manufacturing. How the implementation of information models works in practice, what role PI and complementary technologies play in this process, and what the future focus of the future focal points of the PI strategy have now been in a newly published white paper (free download at www.profibus.com).
Prof. Dr. Christian Diedrich,