Abstract & Overview
Industry 4.0 opens up new potentials for the automation and improvement of production processes, but the associated digitization also increases the complexity of this development. Monitoring and maintenance activities in production processes still require high manual effort and are only partially automated due to immature data aggregation and analysis, resulting in expensive downtimes, inefficient use of machines, and too much production of waste. To maintain control over the growing complexity and to provide insight into the production, concepts such as Digital Twins, Digital Shadows, and model-based systems engineering for Industry 4.0 emerge. Digital Shadows consist of data traces of an observed Cyber-Physical Production System. Digital Twins operate on Digital Shadows to enable novel analysis, monitoring, and optimization. We present a general overview of the concepts of Digital Twins, Digital Shadows, their usage and realization in Data Lakes, their development based on engineering models, and corresponding engineering challenges. This provides a foundation for implementing Digital Twins, which constitute a main driver for future innovations in Industry 4.0 digitization.