KARMEN: Redefining collaboration and expertise sharing through an innovative knowledge graph framework: a case study in additive manufacturing

In the context of Industry 4.0, the manufacturing sector is experiencing increasing complexity and has become a focal point of digital transformation. Knowledge-based engineering (KBE) 4.0 emerges as a crucial solution for agile design processes. In this environment, having comprehensive knowledge about product design, data management, and manufacturing processes is vital for industry success.

Manufacturing industries encounter challenges associated with a deficit of skilled workers and high turnover rates among consultants at service firms, leading to a loss of expertise. This raises a critical question: How can knowledge be effectively transferred from experienced professionals to new designers? Addressing this issue necessitates implementing knowledge-based engineering solutions. KBE 4.0 can serve as a repository for capturing knowledge and streamlining the onboarding process for new team members.

The proposed KBE framework, exemplified by KARMEN (Knowledge Access Request for Manufacturing and Engineering by Network graph), stands as a beacon of innovation for the manufacturing industry by using knowledge graphs. The KARMEN knowledge graph is based on PPR-FBS-8 M data model that standardizes information related to Product, Process, Resource-Function, Behavior, and Structure-8 M. KARMEN, through its knowledge graph, becomes a dynamic tool for design support, facilitating intuitive navigation within a complex network of information. The experimental protocol and case study centered on additive manufacturing serve as a testament to the tangible impact and effectiveness of KARMEN. The integration of KARMEN and its knowledge graph significantly improves the agility and adaptability of the manufacturing industry. As a result, the industry is better positioned to thrive in the rapidly evolving landscape of digital transformations.