Identifying the potential of edge computing in factories through mixed reality

Abstract The application of the edge computing paradigm in manufacturing unlocks novel data-driven improvements in factories while securing data ownership, reducing data transmission effort and storage costs. However, diversity and complexity of manufacturing systems hamper identification and exploitation of the full potential of data processing near machine level. Selection and development of edge applications require process knowledge and insight into available data. This paper proposes a methodology to systematically assist the discovery of data-driven solutions in manufacturing, specifically integrating the advantages that the paradigm shift towards edge provides. To increase the usability, it is implemented in a framework, a custom data model merging manufacturing layer and the ICT layer is developed, a fitting user interface is designed and selected, and all is implemented in an augmented reality application. A case study is conducted and first experiences are discussed and evaluated.