What is Statistical Process Control?
Statistical Process Control (SPC) is a standardized method in industry used to effectively measure and control quality during production and manufacturing processes. This methodology was designed by industrial engineer William Shewart prior to World War II after he considered the notion that a production process could be in statistical control.
SPC was created partially in response to weapons facilities seeking an efficient way to monitor the quality of products. Due to its increased popularity and wide-spread usage in Japanese manufacturing companies following the war, SPC was adopted by American industry where it quickly gained acceptance as one of the most important tools of quality in many industries.
Quality data is collected in the form of readings from numerous machines or product and process measurements by hand or calibrated instruments. Upon successful collection of data, the results are used to monitor a process while evaluating and controlling the quality of products. This is done on a control chart with pre-determined control limits determined by process capability and specification limits determined by the needs of the customer.
Data that remains inside the control limits indicates that everything is operating according to quality standards. There are two types of variation in the data. One is common-cause variation which is normal in manufacturing processes and is expected as a natural part of the process.
The other is special-cause variation and this indicates that product variation is most likely due to an assignable cause such as a shift in the process, tool adjustments, machine damage or a change in the measurement system. If any special causes are identified, appropriate action is taken to return the process to a state of statistical process control.