Title :
A Framework for Managing Enterprise Knowledge for Collaborative Decision Support
Author :
Zhang, N. ; Lu, W.F.
Author_Institution :
Singapore Inst. of Manuf. Technol., Singapore
Abstract :
This paper presents a new knowledge management paradigm in order to assist knowledge workers to make decision effectively and efficiently in the new economy age. The paradigm is called knowledge infused decision support (KIDS) framework for managing knowledge required for complex decisions in manufacturing processes. KIDS framework tackles two kinds of knowledge: quantitative knowledge and qualitative knowledge. Quantitative knowledge is discovered from enterprise´s business databases through data mining, and qualitative knowledge like experience and judgment captured from human in the collaborative decision making process. The infusion of quantitative and qualitative knowledge provides better understanding of business processes and the decision contexts for decision makers to make decisions quickly under the pressures of time-and knowledge-based competition. The knowledge is then codified into enterprise´s knowledge repository. A knowledge mapping mechanism is also provided in the framework for not only delivering the relevant knowledge to the knowledge workers, but also enabling them to access knowledge from knowledge repository efficiently and effectively at anytime and anywhere. It finally discusses several applications in manufacturing industry in order to speed up design decision making using quantitative and qualitative knowledge.
Keywords :
data mining; decision making; decision support systems; groupware; knowledge based systems; knowledge management; manufacturing processes; KIDS; collaborative decision making process; data mining; enterprise business database; enterprise knowledge management paradigm; knowledge infused decision support framework; knowledge mapping mechanism; manufacturing process; qualitative knowledge; quantitative knowledge; Collaboration; Collaborative work; Context modeling; Data mining; Databases; Decision making; Decision support systems; Humans; Knowledge management; Manufacturing processes;
Conference_Titel :
Industrial Informatics, 2007 5th IEEE International Conference on
Conference_Location :
Vienna
Print_ISBN :
978-1-4244-0851-1
Electronic_ISBN :
1935-4576
DOI :
10.1109/INDIN.2007.4384811