Digital Transformation of Products and Processes
Digital transformation is understood as a permanent process of change for all areas of life based on digital technologies.
Digital transformation goes hand in hand with a continuous networking of the real and virtual world throughout the product life cycle via the development of cyber-physical systems (CPS) and taking into account the entire value chain.
This involves the creation of virtual real-time images of products and production systems (digital shadows), the use of standardised communication platforms and the development and provision of software services, the creation and use of digital twins of products and production processes, and the use of methods for handling and using large amounts of data (big data). The latter range from procedures for data analysis and forecasting to artificial intelligence algorithms and machine learning.
Another field of action is the design of predictive, intelligent, learning and self-organising production, logistics, quality assurance and maintenance processes as well as customer-integrated production process design and handling.
For automation and plant and factory operation, the further development of autonomous control, regulation, monitoring and optimisation mechanisms for networked systems represents another field of action. In this context, human-machine collaboration, assistance systems and learning processes also play a special role.
To create the methodological foundations, both complex modelling and simulation procedures, multi-level models, transdisciplinary models and multi-scale simulations, as well as methods for collecting and processing large amounts of data (big data) from heterogeneous data sources and analysing them (data analytics), as well as data-driven modelling, are further significant fields of action.
To create the methodological foundations, both complex modeling and simulation procedures, multi-level models, transdisciplinary models and multi-scale simulations, as well as methods for collecting and processing large amounts of data (Big Data) from heterogeneous data sources and analyzing them (Data Analytics), and data-driven modeling are further significant fields of action.