Scalable Integration Concept for Data Aggregation, Analysis and Preparation of Big Data Volumes in Process Industry

Project Description

The Process Industry plays a significant role in the industrial and high-tech location Germany. For the production of pharmaceuticals and specialty chemicals, the process industry designs, operates and maintains highly automated plants worldwide, with a lifespan of more than 20 years. Field devices are used to control the processes, which have high safety and quality requirements. The devices from different suppliers, generate a flood of data in a heterogeneous IT landscape, e.g. usage, maintenance and quality data. Up to now, these data are collected in the companies in different IT systems and are considered exclusively as a local event (in one plant). Aggregated data from several plants are rarely used by the companies. The device manufacturer also collects data independently. The potential of an integrated analysis – preferably of all data – is rarely or not used.

The Goal of SIDAP is the development and evaluation of Big Data technologies for these innovative and competition-related usage scenarios. Cross-company, secure and scalable data integration architectures for supporting the decision making in plant operation will be designed. This is carried out in close cooperation with leading players from process industry, IT and MES suppliers and researcher in the field of integrated information systems for automation and for operational applications. For this, SIDAP develops a data driven and service-oriented integration architecture considering existing information about structure, data flows in engineering and process control systems and different semantics. This information is made available for interactive analysis in an abstract, integrated and access protected form for authorized users. Based on usage data of their equipment in production and maintenance, the device manufactures could analyze equipment errors, preventively identify failures and intervene in time, to give an optimal support to plant operators. For the operating company, the optimal use of equipment and consequently a failureminimized operation is guaranteed.


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