Statistical Process Control

Statistical process control, also called statistical quality control, is the application of statistical methods to monitor and control the quality of a production process, aiming to detect harmful variation before it produces defective output rather than catching defects afterward through inspection. The American physicist and engineer Walter A. Shewhart developed the technique at Bell Laboratories in the early 1920s, introducing the control chart in 1924 along with the underlying concept of statistical control, work he extended together with colleagues Harold Dodge and Harry Romig, who applied statistical principles to sampling inspection. The method distinguishes between common causes of variation, natural and expected in any stable process, and special causes, assignable disruptions that can be identified and removed, and its use expanded greatly during the Second World War when W. Edwards Deming trained American industry in these techniques before later introducing them to Japanese manufacturers, substantially shaping global manufacturing practice.