Characteristic Rule Induction Algorithm for Data Mining
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
Implementing a data mining solution for enhancing carpet manufacturing productivity
Knowledge-Based Systems
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The production process in manufacturing has recently become highly complex. Therefore, it is difficult to solve problems in a process, by only using techniques that depend on the knowledge and knowhow of engineers. Knowledge discovery in databases (KDD) techniques are supposed to assist engineers in extracting the non-trivial characteristics of a production process that are beyond their knowledge and knowhow. However, the KDD process is basically a user-driven task and such a user-driven manner is not efficient enough for use in a manufacturing application. We developed an automated data-mining system designed for quality control in manufacturing. It has three features; periodical-analysis, storing the result, and extracting temporal-variances of the result. We applied it to liquid crystal display fabrication and found that the data-mining system is useful for the rapid recovery from problems of the production process.