Abstract
To cope with the issue of "brain drain" in today's competitive industrial environment, it is important to capture relevant experience and knowledge in order to sustain the continual growth of company business. In this respect, the study in the domain of knowledge learning is of paramount importance in terms of capturing and reuse of tacit and explicit knowledge. To support the process of knowledge learning, a methodology to establish an intelligent system, which consists of both On-Line Analytical Processing (OLAP) and fuzzy logic principles, is suggested. This paper attempts to propose this approach for integrating OLAP and fuzzy logic to form an intelligent system, capitalizing on the merits and at the same time offsetting the drawbacks of the involved technologies. In this system, the values and positions of related fuzzy sets are modified to suit the industrial environment, supporting smoother operation with less error. To validate the feasibility of the proposed system, a case study related to the monitoring of chemical concentration of PCB electroplating process is covered in the paper.
Original language | English |
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Pages (from-to) | 139-159 |
Number of pages | 21 |
Journal | Artificial Intelligence Review |
Volume | 21 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Apr 2004 |
Keywords
- Fuzzy logic
- Knowledge learning
- Machine learning
- On-line analytical processing (OLAP)
ASJC Scopus subject areas
- Language and Linguistics
- Linguistics and Language
- Artificial Intelligence