Development of an intelligent data-mining system for a dispersed manufacturing network

Recent advances related to on-line analytical processing (OLAP) have result ed in a significant improvement in data analysis efficiency by virtue of it s multidimensional database structure and pre-computing operations of measu ring data. However, the research related to the design and implementation o f OLAP, particularly in the support of dispersed manufacturing networks in terms of 'intelligent decision making', has yet to be considered as remarka ble. Research studies indicate that the level of intelligence of decision s upport systems can be enhanced with the incorporation of computational inte lligence techniques such as case-based reasoning or rule-based reasoning. T his paper describes the development of an intelligent data-mining system us ing a rule-based OLAP approach which can be adopted to support dispersed ma nufacturing networks in terms of performance enhancement. In this paper, th e techniques, methods and infrastructure for the development of such a data -mining system, which possesses certain intelligent features, are presented . To validate the feasibility of this approach, a case example related to t he testing of the approach in an emulated industrial environment is covered .