Open Knowledge Graph for Manufacturing Process Selection

Manufacturing process selection (MPS) is the process of identifying the most suitable manufacturing process based on various criteria such as production demands. Rapid selection is particularly crucial when sudden manufacturing chain disruptions occur, such as those caused by a disaster or a pandemic, where there is an urgent need to find new or alternative manufacturing processes. Challenges emerge due to the need for in-depth knowledge of manufacturing processes across various engineering domains, which is difficult to master, and the lack of easily accessible MPS knowledge. To address these challenges, we propose a process selection approach called the Open Manufacturing Process Knowledge Graph (OMPKG). The OMPKG is designed to comprehensively capture interdisciplinary engineering knowledge, while offering flexibility and scalability to handle complex and evolving MPS data and ensuring expression consistency for sharing. The OMPKG can be integrated with a general selection method, called screening and ranking, to determine the appropriate manufacturing process rapidly. In this paper, we describe the development rationale and logic of the OMPKG for specific manufacturing processes, such as casting, molding, and additive manufacturing, and demonstrate its use in a case study of producing respiratory mask facepieces.