摘要：Statistical process control (SPC) techniques are widely used in industry for process monitoring and quality improvement. Various statistical control charts have been developed to monitor the process mean and variance. Traditional SPC methodology is based on a fundamental assumption that process data are statistically independent. Process data, however, are not always statistically independent from each other. Under such conditions, traditional SPC procedures are not effective and appropriate for monitoring, controlling, and improving process quality. In this presentation, I will review the research results on process control charts either for monitoring the process mean or the process variance when the process is autocorrelated.