• Title of article

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

  • Author/Authors

    Wang، نويسنده , , Xiaohuan and Wong، نويسنده , , T.N. and Fan، نويسنده , , Zhi-Ping، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    15
  • From page
    7519
  • To page
    7533
  • Abstract
    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. s 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.
  • Keywords
    Ontology , Knowledge Management , Decision support , global supply chain , Rule-Based Reasoning
  • Journal title
    Expert Systems with Applications
  • Serial Year
    2013
  • Journal title
    Expert Systems with Applications
  • Record number

    2354137