What Is Statistical Quality Control?

Statistical quality control, referred to as SQC, is based on the quality control chart, using mathematical statistics to make the quality control quantitative and scientific, and effectively prevent and control process quality. Its main goal is to ensure that the characteristic values of product quality produced by all processes are as long as possible or close to the expected value, and to improve the process capability of the production process. Therefore, it is also commonly known as statistical process control (SPC). Its main feature is to fully reflect The principle of process prevention in modern control theory is introduced.

Statistical quality control refers to the use of statistical techniques for quality control. These techniques include

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Statistical quality management was born in the 1920s, a pioneering work was proposed by WA Shewhart and HF Dodge working in Bell Telephone Labs in 1925, respectively

The purpose of all business statistics is to provide statistical information for business decision-making and management. Under the conditions of the new economy, there are high risks in business decision-making, and high risks arise from uncertainty. Uncertainty is directly related to the accuracy and timeliness of information. The more accurate and effective the information, the lower the uncertainty. And so on. Accuracy and timeliness are two basic requirements for statistical data. Among them, accuracy is the first and is the basis of statistical work. It determines the quality of statistical data and is the fundamental indicator of the quality of statistical data. Accurate statistical data is convenient for decision-makers and managers to correctly grasp the situation and objectively analyze the problems so as to make scientific decisions. Conversely, moisture and unrealistic statistical data and contradictory statistical data will give policymakers the opposite signal, which will mislead decision-making and regulation, and will cause fatal losses to the development of enterprises. Therefore, the statistician must be highly responsible for his job, take the statistical data as the object, and eliminate the error of the statistical data as the goal. It must have accurate statistical data to achieve the purpose of strengthening the quality control of statistical data.