Knowledge-based Support of the Production System Design by Semantic Technologies Using the Example of the Electric Motor Production

Abstract

The interest in artificial intelligence (AI) and its use in industrial production is growing steadily. The increasingly known machine learning, however, is only one of several AI technologies emerging from basic research. Another subarea of AI represent the so-called semantic technologies, which play a decisive role especially in knowledge management. They allow knowledge to be structured and processed in such a way that it can be used for targeted support in complex, knowledge-intensive tasks. Especially during the design of production systems, such technologies have the potential to reduce planning efforts by providing existing expert knowledge. For electric motor manufactures, designing a proper production system remains a challenge due to low standards and numerous alternative manufacturing processes. Accordingly, this paper provides an overview of semantic technologies and outlines their fundamental potential in the conceptual design of production systems. Finally, a pragmatic approach is presented to improve the future knowledge work at electric motor manufacturers.