EXHIBITIONS
Tube 2016: FA 03: Industry 4.0 – automation technology of the future
T
he term Industry 4.0 has been a frequently buzzword for several years now. It is generally used as a synonym for the fourth industrial revolution where the real and virtual worlds are growing together into an “internet of things”. It should largely be seen against the background of changes in industrial production, with an increasing individualisation of products and highly flexible manufacturing processes. Moreover, according to the German Federal Ministry of Education and Research, there has been a “far-reaching integration of customers and business partners into value-added and business processes, while the link between production and high-quality services has led to so-called hybrid products.”
The term Industry 4.0 has manifested itself especially clearly
in the increased automation of the various processes within an industrial enterprise. It only works under the development of intelligent, autonomous monitoring and decision-making processes, so that the relevant routines can be controlled and optimised in real time. Two concepts that are closely connected with Industry 4.0 are the terms smart factory and smart production. The focus of a smart factory is on developing intelligent production systems and processes and on realising distributed and networked production sites – or, to use IT jargon: on the integration of adaptive cyber-physical systems in production. Smart production includes, among other things, cross-company production logistics and man-machine interaction. In order to implement Industry 4.0 in practice, large volumes of data (“big data”) are required. Although they are available in many
companies, they still tend to be rather isolated and disconnected. To set up genuinely efficient routines within a business, it is important to analyse, process and intelligently connect all data. Prof. Katharina Morik from the Department of Artificial Intelligence at TU Dortmund University, says: “Unless large collections of data are analysed, they can degenerate into data cemeteries. This is done with the tools of Artificial Intelligence (AI) which allows machine learning, i.e. the automatic acquisition of rules based on data. To “dig” for knowledge among the available data – a process known as “data mining” – the company RapidMiner has developed a tool of the same name which is now extremely widespread and requires no programming.
Big data and cyber-physical systems are areas which are studied by SFB 876, a unit within
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the IT Department of TU Dortmund University. One of their projects is the development of data stream algorithms which allow an analysis of incoming data streams in real time. The special research unit has developed a tool called Streams for the convenient configuration, parallel arrangement and distributed execution of online processes. The theoretical foundation that was created by SFB 876 has been implemented in practice together with SMS Siemag AG and a working group of Dillinger Hütte under a real-time forecasting project at a steel mill. This innovative system is adaptive, i.e. it is able to learn and therefore to fine-tune a production process based on the data which it receives from the manufacturing process, so that it can then improve the industrial process.
Dillinger Hüttenwerke, according to Dr. Dominik Schöne, is “Europe’s
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photo by Messe Duesseldorf
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