Continuous Integration of Field Level Production Data into Top-Level Information Systems Using the OPC Interface Standard

On the way to the fourth industrial revolution, one major requirement lies in reaching interoperability between hardware and software systems. Especially real-time propagation of shop floor information in top-level production planning and control systems as well as the consolidation of distributed information into a consistent data basis for comprehensive data analysis are still missing in most production environments. Existing approaches to serve interoperability through standardized interfaces are limited by proprietary data exchange protocols and information models. Within industrial manufacturing and automation, standardization attempts between these systems are primarily focused on industrial interfaces like OPC/OPC-UA. However, the aggregation of data created by devices like sensors or machinery control units into useful information has not been satisfactorily solved yet as their underlying models are carried out using different modeling paradigms and programming languages, thus inter-communication is difficult to implement and to maintain. In this work, an integration chain for data from field level to top-level information systems is presented. As Manufacturing Execution Systems or Enterprise Resource Planning tools are implemented in higher programming languages, the modeling of field level information has to be adapted in terms of a semantic interpretation. The approach provides integration capabilities for OPC-conform data generated on the field level. The information is extracted from low level information systems, transformed according to object-oriented programming paradigms and object-relational standards and finally integrated into databases that allow full semantic annotation and interpretation compatible to a common information model. Hence, users on management levels of the enterprise are able to perform holistic data treatment and data exploration along with personalized information views based on this central data storage by means of a reliable and comfortable data acquisition. This increases the quality of data and of the decision support itself, as more time remains for the actual task of data evaluation.