Statistical Process Control (SPC)

The term Statistical Process Control (SPC) is typically used in context of manufacturing processes (although it can also pertain to services and other activities), and it denotes statistical methods used to monitor and improve the quality of the respective operations. By gathering information about the various stages of the process and performing statistical analysis on that information, the SPC engineer is able to take necessary action (often preventive) to ensure that the overall process stays in-control and to allow the product to meet all desired specifications. SPC involves monitoring processes, identifying problem areas, recommending methods to reduce variation and verifying that they work, optimizing the process, assessing the reliability of parts, and other analytic operations. SPC uses such basic statistical quality control methods as quality control charts (Shewhart, Pareto, and others), capability analysis, gage repeatability/reproducibility analysis, and reliability analysis. However, specialized experimental methods (DOE) and other advanced statistical techniques are often part of global SPC systems also. Important components of effective, modern SPC systems are real-time access to data and facilities to document and respond to incoming QC data on-line, efficient central QC data warehousing, and groupware facilities allowing QC engineers to share data and reports (see also Enterprise SPC).

See also, Quality Control and Process Analysis.

For more information on process control systems, see the ASQC/AIAG’s Fundamental Statistical Process Control Reference manual (1991).