Automatic Generation of Conceptual Enterprise Models
The world organizations operate in is becoming increasingly complex and uncertain, due to technical disruptions, changes in operational environments and social structures, global markets, or, as recently seen, through global diseases. Those changes require the development of smart technological and human systems, based on Conceptual Enterprise Models. Through the increasing complexity, modeling is difficult for human actors and therefore requiring machine support, for example through Artificial Intelligence approaches, leading to Hybrid Intelligence systems and automated generation of Conceptual Models. While various approaches for the automated generation of Conceptual Enterprise Models exist, for example in requirements engineering, process mining or in the context of Digital Twins, the approaches mostly support only parts of the modeling process. Additionaly, the approaches lack a common base, such as standardized frameworks. Therefore, my further research aims at showing how conceptual modeling can be automated, developing a modeling standard for Digital Twins in enterprise context, showing its technical feasibility and evaluating the implementation in real world use cases. The research is performed through design science research, systematic literature research, argumentative deductive reasoning, prototyping and use cases. At this stage, a first literature review is completed, and the next research steps are in preparation.
2020 IEEE 24th International Enterprise Distributed Object Computing Workshop (EDOCW)