Development of nuclear power plant online monitoring system using statistical quality control

Abstract

Statistical Quality Control techniques have been applied to many aspects of industrial engineering. An application to nuclear power plant maintenance and control is also presented that can greatly improve plant safety. As a demonstration of such an approach, a specific system is analyzed: the reactor coolant pumps (RCP) and the fouling resistance of heat exchanger. This research uses Shewart X-bar, R charts, Cumulative Sum charts (CUSUM), and Sequential Probability Ratio Test (SPRT) to analyze the process for the state of statistical control. And we made Control Chart Analyzer (CCA) to support these analyses that can make a decision of error in process. The analysis shows that statistical process control methods can be applied as an early warning system capable of identifying significant equipment problems well in advance of traditional control room alarm indicators. Such a system would provide operators with enough time to respond to possible emergency situations and thus improve plant safety and reliability.