Statistical process control (SPC) is the general methodology based on statistical methods that can be used in monitoring and control of product and/or process quality. We often expect the processes and products to exhibit variability. The inherent variability in a process is defined as the variability that occurs by chance. If a process exhibits such variation, it is said to be in a state of statistical control. However when there is an unusual and/or unexpected occurrence of excess variability due to an assignable cause, the process is said to be out of statistical control. This could for example be due to wear and tear, defective/impure raw material, errors in data collection schemes, etc. Statistical process control aims to identify these assignable causes generating the excessive variation and help to bring the process back in statistical control.
SPC has a wide variety of application areas in manufacturing and chemical processes as well as in daily applications in service sector. Our current research areas include:
- Multivariate SPC where more than a single quality characteristic is being monitored
- SPC with serially dependent data collected in time
- SPC applications in health care
Examples of application: Improving industrial processes