This paper was produced for the 2019 NAFEMS World Congress in Quebec Canada
It is said that heaven and the hell come together with digitalization. The rationale behind this claim is that digitalization is enabling much of scientific and engineering content in application-specific implementations, but the implementations themselves are complex and difficult to manage. Poor digital capabilities cause scattered and unstructured domain data with unknown reliability. Anyhow, from scientific and engineering perspectives, the scattered, unstructured and fragmented domain data is also the main enabler for scientific research. The general objective of a truly digitalized engineering world in Industry 5.0 can be reached by activating the scientific research and the industry to organize this data into a controllable & structured format. Consequently, benefits, competitive advantages and business potential will be realized by using a combination of different technologies. New business models are shaping the landscape for new technologies. Service-based logic and changing modes of resource ownership are transforming the way data can be utilized and shared among actors. Ownership of data is becoming increasingly important for many companies. Hybrid models are the practical ultimatums of data capitalization, since they are connecting engineering knowledge to business knowledge via enabling technologies such as IT, IoT, 5G, data analytics, Big Data, AI, etc. By integrating a physics-based model and data-driven model based on measured data, weaknesses of these individual approaches can be avoided, benefits of both approaches can be utilized and finally, more information and knowledge through integration processes can be created. In this article, we will give an engineering-based overview of a hybrid modelling approach to reach some of the end goals of Industry 5.0. The hybrid model approach will be clarified with specific benefits, competitive advantages and business potential.