Semantic models and knowledge graphs as manufacturing system reconfiguration enablers

Abstract

Reconfigurable Manufacturing System (RMS) provides a cost-effective approach for manufacturers to adapt to fluctuating market demands by reconfiguring assets through automated analysis of asset utilization and resource allocation. Achieving this automation necessitates a clear understanding, formalization, and documentation of asset capabilities and capacity utilization. This paper introduces a unified model employing semantic modeling to delineate the manufacturing sector’s capabilities, capacity, and reconfiguration potential. The model illustrates the integration of these three components to facilitate efficient system reconfiguration. Additionally, semantic modeling allows for the capture of historical experiences, thus enhancing long-term system reconfiguration through a knowledge graph. Two use cases are presented: capability matching and reconfiguration solution recommendation based on the proposed model. A thorough explication of the methodology and outcomes is provided, underscoring the advantages of this approach in terms of heightened efficiency, diminished costs, and augmented productivity.