Supply Chain System Analysis and Modeling Using Ontology Engineering

One of the primary objectives of supply chain (SC) system analysis and modeling is to develop conceptual design of organizational and process knowledge models, which facilitates optimal supply chain management. SC knowledge modeling consists of two components: 1) modeling SC workflows, and 2) capturing and organizing knowledge necessary for managing them. Workflow modeling deals with handling activities to generate and utilize knowledge, whereas Ontology Engineering formalizes knowledge content. This paper proposes a framework comprising both aspects of knowledge modeling. For knowledge representation, two standards are introduced: situation calculus, and supply chain markup language. The former is utilized for capturing process logic with mathematical expressions, and the latter for coding this logic with a computational language. An example of production scheduling for a steel supply chain is provided for illustration.