Abstract
Abstract Statistical process monitoring and control are now widely accepted in various industries. In recent years, statistical techniques are expected to solve quality-related problems. The issue of how to improve product quality and yield in a brief period of time becomes more critical in many industries where the product life cycle becomes shorter. Examples include steel processes and semiconductor processes. These processes are totally different in appearance, but the problems to solve are highly similar: how to build a reliable model from a limited data, how to analyze the model and optimize operating condition, and how to realize an on-line monitoring and control system and maintain it. In this paper, the problems and solutions are described with our application results in steel facilities.
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