Human-centered knowledge graph-based design concept for collaborative manufacturing

With the increasing importance of highly connected and monitored processes supported by industrial information systems, such as knowledge graphs, the integration of the operator has become urgent due to its high cost and is also to be appreciated from a social point of view. The facilitation of collaboration between humans and machines is a fundamental target for Industrial Cyber-Physical Systems, as the workforce is the most agile and flexible manufacturing resource. Furthermore, the design of such a framework requires effective systems to utilise resources and information. This paper aims to provide recommendations of ontologies and standards that can support monitoring work conditions, scheduling, planning and supporting the operator and the possibilities to formalise the classic work instructions to analyse the unique activities. The main contributions of the work are that it proposes a design work-frame of a knowledge graph where the work performed by the operator is in the scope, including the evaluation of movements, collaboration with machines, work steps, ergonomics and other conditions. The paper highlights that activity recognition technologies can enhance the utilisable data in a knowledge graph for a smart factory. With this approach, the future goal may be to automate the entire data collection and knowledge exploration processes, which can facilitate the support of the human-digital twin and the implementation of augmented reality technologies in the Industry 5.0 concept.