Discrete Proportional-Integral Adjustment and Statistical Process Control

Abstract

This paper explains the nature and importance of proportional-integral control and shows how it may be adapted to statistical process control. The relation of this type of control to exponential smoothing, minimum mean squared error control, and optimal constrained schemes is discussed. Robustness properties which simplify considerably the practical application of this type of control are demonstrated.

• Engineering Process Control
• Feedback Control
• Minimum Mean Square Error Controller
• Process Control

Additional information

Notes on contributors

George Box

Dr. Box is Professor Emeritus and Director of Research in the Center for Quality and Productivity Improvement. He is an Honorary Member and Shewhart and Deming medalist of the ASQC.

Alberto Luceño

Dr. Luceño is a Professor in the Department of Statistics.