Statistical Quality Control Definition

Statistical quality control ensures manufacturing processes remain consistent.
Statistical quality control ensures manufacturing processes remain consistent. (Image: Kim Steele/Photodisc/Getty Images)

Statistical quality control, also called statistical process control, uses statistics to determine when processes or product quality deviate from specifications. The primary goal of statistical quality control is to maintain and improve processes through techniques such as sampling and process improvement projects, which reduce variations in product. Statistical process control uses control charts to monitor changes in processes, machinery, labor or the environment. Inspections and sampling determine when a process is outside of the control parameters, which can result in a reduction in quality.

Quality Consistency

Statistical quality control helps to maintain the consistency of a process, which will result in a consistency in the quality as well. Process controls will not correct defects in the design of a product or in the process itself, but they do ensure each product is manufactured to the process parameters. Sampling and inspections used to collect data for statistical quality control can identify defective processes and flaws in product design.


The control chart is the tool most often used in statistical process control. The graphic provides a visual representation of data collected through inspections and quality sampling. The control chart compares the statistical data taken from quality inspections and sampling to the control data, which is inspection data when the process is within control parameters. When a manufacturing process is outside of the parameters, variations in inspection and sampling data will occur.


Statistical quality control or statistical process control provides instant feedback when a process goes outside of the process parameters. This allows production to stop and correct the problem before creating a great deal of defective product. The process also reduces the need for 100 percent inspections. Production workers can monitor the process through sampling and random inspections to determine when a process has deviated from specifications.


Training is required to implement statistical quality control in a production environment. The company must train production workers to use control charts and the tools for sampling, random inspecting and measuring the product to ensure the process does not deviate from the control.

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