Connecting technology know-how and process knowledge

The starting point is the networking of equipment and software systems, smart control and sensor systems permitting the acquisition and subsequent provision of all technology and process-related information. Either alone or with our cooperation partners, who are usually from the Fraunhofer network and from the RWTH Aachen University, we develop the IT infrastructures such as industrial cloud concepts for smart services, which are required in order to evaluate such large volumes of data and utilize them effectively.

Smart glasses in production

Whereas smart devices such as tablets and smartphones have long become established parts of our everyday lives, these technologies are much less in evidence in the industrial environment despite the fact that they have enormous potential in terms of process quality, productivity and transparency. They could connect employees very much more efficiently than is currently the case with production planning and quality systems, thereby supporting them in their activities. The vision of fault-free production thus moves another step closer.

Data consistency in the CAx process chain

Computer-assisted process chain planning and design via software systems are more important than ever in the age of Industry 4.0. In recent years, there has been a shift in computer-assisted planning of process chains (CAx) from fixed to flexible manufacturing process chains. In accordance with the principle of “mass-customization”, manufacturing process chains must adapt dynamically to inputs and disturbances in order to achieve the expected outcome. The fundamental requirement for continuous, flexible CAx process chains is data consistency.

Machine-to-machine communication

Industrial manufacturing still requires an enormous amount of manual support: this begins with the development of machine programs and extends through parameterization and organizing processes and cycles to manual quality control. This prolongs set up and rigging times and requires experienced machine operators, who intuitively pass on information between process stages and refer it to planning systems such as MES.

Big Data: Processing large volumes of data efficiently

As a result of the burgeoning use of sensors along with networked equipment with complex software systems, the data flow into manufacturing is increasing rapidly. Just recording and filing such large volumes of data in a structured manner takes a considerable amount of time and effort. Initially, instead of bringing about the intended transparency, this can lead to somewhat chaotic conditions. Only when suitable data processing systems are in place and when the truly relevant information can be extracted from such expansive volumes of data, knowledge can be acquired. The Fraunhofer IPT is therefore developing effi cient concepts for rapid data processing and evaluation and is transforming these into applications with real-time capability.

© Fraunhofer IPT

Next-generation technologies for Industry 4.0

Systematic collection and analysis of relevant information precedes all strategic planning. This applies particularly to the introduction of appropriate technologies for manufacturing or networking, for example. However the ability to spot and trace the right information at the right time usually requires a trained eye and considerable practical knowledge. Networked, community-based approaches can be extremely useful in such cases by involving network partners and experts outside the organization in the search for the appropriate technology and the best way to manage it.