Automated extraction of diagnostic knowledge

• Main Author: Zhai, Lianyin
• Other Authors: Khoo, Li Pheng
• Format: Theses and Dissertations
• Language: English
• Published: 2008
• Subjects: DRNTU::Engineering::Manufacturing::Production management; DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
• Online Access: http://hdl.handle.net/10356/13476
• Institution: Nanyang Technological University

With the advent in technology, manufacturing systems have become more complex. It may not be easy for an engineer to acquire sufficient knowledge in a short time in order to carry out manufacturing diagnosis efficiently. As a result, the ability to automatically extract diagnostic rules from the raw knowledge or data gleaned from a manufacturing system has become an important area in artificial intelligence research. In reality, the raw knowledge gleaned from a manufacturing system may contain uncertainty, that is, it may be imprecise or incomplete.