Statistical control in industrial processes is a method of maintaining desired process performance through the use of statistical techniques. Statistical control processes are often used to reduce variation in production, improve quality and reduce costs. The objective of statistical control is to provide a measure of stability by detecting and correcting process variability before it adversely affects the production of the product.
Statistical control processes involve the collection and analysis of process data to determine whether the process is in statistical control. Statistical control techniques are used to reduce the variation in product output and to detect changes in the process. Common statistical control techniques include Shewhart control charts, process capability analysis and design of experiments.
Shewhart control charts are graphical devices used to detect special causes of variation and to monitor the process mean and variability over time. The control charts are based on statistical sampling techniques and are used to detect small changes in the process before they have an effect on the product. Process capability analysis is used to determine the ability of a process to meet design specifications. It involves comparing process performance to design specifications and identifying any areas that need improvement. Design of experiments is used to identify the optimal combination of process input variables and their effect on the process output.
Statistical control processes can help reduce process variation, improve quality and reduce costs. By using statistical control techniques, manufacturers can detect and correct process variation before it affects product quality. The use of statistical control processes can ultimately provide a more consistent product output and improved customer satisfaction.
References
Ebrahimpour, M., & Brown, D. R. (2012). A statistical control process for monitoring and improving production processes. International Journal of Production Research, 50(16), 4563-4576.
Juran, J. M., & Gryna, F. M. (2014). Quality planning and analysis. McGraw Hill Education.
Montgomery, D. C. (2013). Introduction to statistical quality control. John Wiley & Sons.