Ontology-based supply chain decision support for steel manufacturers in China

• The method is presented to combine multi-source decision knowledge.
• Rule-based ontology reasoning is presented to support decision-makings.
• The semantic interoperable decision environment is enabled.
• The decision knowledge is evolved and updated as time goes by.
• Practices of China’s iron and steel industry can be improved based on this study.

It is now very popular for companies to collaborate as a global supply chain (GSC) for their business benefits. Many companies are inclined to outsource manufacturing, logistics and business activities globally. The senior managers of companies are faced with more complicated and dynamic situations to make decisions than ever before. They not only have to consider the internal factors including production, inventory, and financial status, but also have to take into account the external factors such as policies, market forces, competitive behaviors, etc. To survive in today’s fierce market environment, it has become increasingly important for companies to find ways to combine the multi-source decision knowledge, and utilize it to make sound decisions across the organizational boundaries.In this paper, a rule-based ontology reasoning method is proposed to support decision makings and improve industrial practices for companies in the dynamic and heterogeneous GSC context. A shared GSC ontology is developed to describe the heterogeneous internal and external decision knowledge of the GSC companies and the dynamic market environments. It is contributed in enabling a semantic interoperable decision-making environment, along with the decision knowledge being evolved timely. In addition, semantic rules serving as decision requirements are developed to reason the shared GSC ontology to support the complicated and sound decision-makings, and also to provide suggestions on improving their industrial practices. A case study in China’s iron and steel industry is introduced to justify the feasibility and effectiveness of the proposed ontology-based approaches.