Abstract: A method of production quality monitoring and diagnosis based on the kernel principal component analysis was introduced in the hot rolled strip process.The squared prediction error(SPE) statistic was used in process monitoring.The diagnosis criterion could express the influential importance to SPE,which was computed by the data construction method and the optimal neighbor selection strategy.Finally,simulation data and actual production data were used for model validation.The result shows that the SPE statistic based on the kernel principal component analysis can detect the abnormality and track the causes of faults effectively for adjusting the production process to prevent from substandard products.