Digitalisierung

Markets will change dramatically due to the megatrend platforming [1]. For previously isolated markets, such as Smart Factory, Smart Logistics or Smart Grids, this offers the potential to create interconnected “smart Ecosystems”. Logistics platforms as an instrument of networking are a key driver of this platform economy. In the application for Supply Chain Visibility, logistics platforms promote the transparency and control of logistics chains and thus represent an essential first step towards smart Ecosystems.

The increasing complexity forces industrial companies to look for new strategies for a future-proof product development. One approach to this is agile approaches in product development in combination with additive manufacturing processes. Physical product increments can thus be produced during sprints and analyzed and improved directly with customers. This improves the product understanding of the development team and customers. The benefits are shorter development times, better customer orientation of the products and a lower project risk.

The age of globalisation is characterised by increased competition. An opportunity to succeed in the face of increasing competition lies in the digitisation of production companies. This article is dedicated to the design of a three-stage model platform of Industry 4.0, which focuses on the consistency of processes from the customer to the supplier at all company levels. The model platform is followed by an overview of the transformation steps for evaluating and shaping progress on the way to become a digitised production company.

The paper presents a method for the systematic selection of “Digital Twin” applications of products. Based on a product-independent search of implementations, potential use cases for the product’s ”Digital Twin” are specified and selected. This selection of applications forms the basis of the method, which allows a detailed modeling in two phases. The result of this modeling is an in-depth understanding of the use cases themselves and their requirements, especially information requirements, on the “Digital Twin” of the product. Furthermore, these findings enable an efficient conception and implementation of the virtual image of the product and can be the basis for optimizing the existing value chain.

In process engineering, one thinks of production operations that are controlled or regulated by sensors and actuators. And any realization of matter transformation is based on a physical substratum, which holds equally for living systems and their behaviour. The article distinguishes between three system levels: the functional level, the interface to the environment and the cognitive level of. Using these three levels, the learning cycle or the previous Cognitive Loop can be very well illustrated. If one compares with this way of distinction the Bio-Informatization of human intelligence with the technical development stages of mechanization, automation, regulation and deep learning, then the cybernetic-sociological term “operational closure” becomes understandable. It becomes obvious that in the context of a digitized culture of production and organization, we should be prepared for a new kind of cognitive loop based on silicon (SI), an intelligent system behavior via ...