RFID Data in the Cloud

The OPC Unified Architecture and industrial communication form the infrastructure of the digital factory.
By Markus Weinländer

In order to meet the objectives and requirements of the digital factory, however, an end-to-end network topology is not enough. Required is a communication protocol that is open and standardized, provides sufficient semantic information and translation options, is easy to expand and maintain, offers maximum security in various forms, and also has low memory and processing requirements to allow implementation on small devices.

The answer to these requirements is the OPC Unified Architecture (OPC UA). The most important thing about the OPC UA is that it is not only a protocol, but a complete architecture that, in addition to the transmission definition, also provides suitable software stacks for device and software makers, as well as engineering tools for system integrators. The OPC UA thus brings important advantages. To begin with, the information model ensures that all data is transmitted on a type-safe basis. Even complex data types (structures) are possible.

Figure 2: Different aggregation levels and a factory backbone in a ring structure form the industrial network topology (click on the above image to view a larger version)
Besides the pure data values, the OPC UA also transports semantic information between communication partners. Since the architecture works object-oriented, the semantics are always interwoven into an object context—it consists of more than just a "speaking" identifier and always refers to the entire object with its properties and methods. Function calls over the network allow a certain control of the communication partner. Events are supported as ad-hoc communication or as message brokers for the connection to the cloud. The security of the system is likewise guaranteed by suitable mechanisms.

For the specific use in different applications, various industrial associations work with the OPC Foundation on so-called "Companion Specifications," which supplement the basic specification of the OPC UA for a particular domain. One example is the AutoID Companion Specification, which was developed jointly by the RFID industrial association AIM and the OPC Foundation. This allows systems for the automatic identification, such as 2D code readers or RFID devices, to be embedded in modern communication architectures by means of the OPC UA. For users, the OPC UA makes it possible to employ devices from different manufacturers according to individual requirements.

Figure 3: RFID systems, such as Siemens' Simatic RF600, can be integrated into different target systems thanks to the OPC UA
In addition, different identification technologies can be integrated in the same way. The importance of the OPC UA, though, goes far beyond this, because now RFID systems can be integrated, as well as different controllers, field devices, IT systems and much more. Different target systems (automation systems for the control of the field level, big-data applications for the information analysis in the cloud), too, can be operated similarly (see Figure 3).

However, until the OPC UA can be widely used as an end-to-end communication architecture, further standardization work is necessary, as some areas of the industrial communication are not yet fully covered. For instance, at the sensor level, only a few device families or technologies have been specified for OPC UA—RFID and auto-ID systems are among the pioneers. But aside from these future tasks, the OPC UA already represents a communication architecture that is unique in its range of functions, and will be indispensable as the basis for the vertical and horizontal integration in the digital factory.

Markus Weinländer is the head of product management for SIMATIC Net at Siemens AG. He previously managed marketing for RFID across all parts of the company, and held various research and development positions. During his career, Markus acquired considerable experience in software engineering and the architecture of automation systems. He studied business economics in Hamburg and Wismar, received a Master of Science degree, and obtained his technical background as an associate engineer at Siemens Technik Akademie in Erlangen, in the special field of data and automation technology.

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