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
Link To Document :
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