Automatic Generation of Diagnostic Handling Code for Decentralized PLC-based Control Architectures

In this paper, an ontology-based approach to automatically generate control applications to handle diagnostic information of decentralized control devices is presented. Diagnostic possibilities of modern remote I/O devices are analyzed and software components in terms of function blocks to handle the specific diagnostic information are defined. After a detailed conceptual overview, the application of the proposed knowledge-based code generation approach to a PLC-based control architecture of a hot rolling mill is described. It is shown that the proposed approach significantly reduces engineering time and the error rate in the design processes of industrial control and diagnostic applications, since the application engineering is raised to an abstract level by utilizing pre-defined, tested, and reusable function blocks and a user-definable set of code generation rules to encode repetitive implementation tasks. The rules are defined in the query language SPARQL with additional ARQ functions to reduce the complexity.