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- FIR e. V. an der RWTH Aachen (3) (remove)
Especially in SMEs of the manufacturing industry, data is not sufficiently used to optimize processes. Some companies have implemented lighthouse “Industrie 4.0 projects”, but struggle with a broader approach. We present the results of a survey we performed that underlines that statement. There are approaches in the literature that propose generic architecture frameworks tackling the mentioned challenge. Still, most of them do not include the existing IT architecture of a company and fail to propose a comprehensive solution delivering a real benefit to companies. Therefore, companies cannot easily use them. For that reason, we developed and tested an Industrie 4.0 software platform architecture companies can use as a blueprint for their own implementation. This architecture is presented in this paper as well as the structured VDI 2221 approach we used to develop it.
In this paper, an approach towards energy management 4.0 will be presented. Energy management 4.0 is understood as an encompassing energy data based concept for manufacturing companies acting in an flexible energy grid of the future with the final goal of autonomous self-optimization Controlling, supervising and scheduling production and logistic steps based on a reliable communication infrastructure and real time data in accordance to achieve a maximum of profitability with regard to human factor is executed.
Guided by a four maturity levels of the "acatech Industrie 4.0 Maturity Index" developed by the German National Academy of Science and Engineering (acatech) different use cases are presented according to the steps of visibility, transparency, prognostic capacity and self-optimization. The basic idea of energy management 4.0 is described and an outlook of further steps that are needed to be evaluated for an implementation are presented.
The work at hand offers a comprehensive guide to practitioners to develop IoT solutions based on the circumstances and the specific environmental factors encountered in individual cases throughout industries. The fundamental technologies, software basics, and organizational principles are explained and specified. The hardware in use are different sensors and localization technologies. These technologies enable the data acquisition on the shop floor. They are the link between the physical world and the software portion of the solution. To augment the information value of the data acquired while monitoring the processes on the shop floor, information from the existing IT-infrastructure is extracted. Additionally, the presented concept enables the insertion of information acquired by the sensors into the existing IT-infrastructure. The open architecture of the IoT solution supports a seamless integration of the system into the existing IT landscape.