Have you experienced purchasing a product then discovered that it is defective in some way or does not function the way it was designed to, or found that a piece of the product is missing or defective. As consumers, we expect the products we purchase to function as intended. However, producers of products know that it is not always possible to inspect every product and every aspect of the production process at all times. The challenge is to design ways to maximize the ability to monitor the quality of products being produced and eliminate defects. (TQM) addresses organizational quality from managerial viewpoints focusing on customer-driven quality standards, managerial leadership, continuous improvement, quality built into product and process design, quality identified problems at the source, and quality made everyone’s responsibility. However, talking about solving quality problems is not enough. We need specific tools that can help us make the right quality decisions. These tools come from the area of statistics and are used to help identify quality problems in the production process as well as in the product itself. Statistical Quality Control (SQC) is a set of statistical techniques intended to aid in the improvement of system quality.[i]
The Statistical Control of Quality is application of statistical principles and techniques in all stages of design, production, maintenance and service. The phrase “statistical quality control” (SQC) refers to the application of statistical methods to monitor and evaluate systems and to determine whether changing key input variable (KIV) settings is appropriate. Specifically, SQC is associated with Shewhart’s statistical process charting (SPC) methods. These SPC methods include several charting procedures for visually evaluating the consistency of key process outputs (KOVs) and identifying unusual circumstances that might merit attention.
In common usage, however, SQC refers to many problem-solving methods. Some of these methods do not relate to monitoring or controlling processes and do not involve complicated statistical theory. In many places, SQC has become associated with all of the statistics and optimization methods that professionals use in quality improvement projects and in their other job functions. This includes methods for design of experiments (DOE) and optimization. [ii]
Statistica1 quality control (SQC) is the term used to describe the set of statistical tools used by quality professionals. Statistical quality control can be divided into three broad categories: 1. Descriptive statistics are used to describe quality characteristics and relationships. Included are statistics such as the mean, standard deviation, the range, and a measure of the distribution of data. 2. Statistical process control (SPC) involves inspecting a random sample of the output from a process and deciding whether the process is producing products with characteristics that fall within a predetermined range. SPC answers the question of whether the process is functioning properly or not. 3. Acceptance sampling is the process of randomly inspecting a sample of goods and deciding whether to accept the entire lot based on the results. Acceptance sampling determines whether a batch of goods should be accepted or rejected.
Statistical quality control (SQC) originated in techniques of sampling inspection of lots (statistical lot inspection, SLI) and of manufacturing processes (statistical process inspection, SPI) developed since 1920’s. Nowadays, the area of SQC comprises all applications of statistical methodology for the purpose of assuring or improving the quality of products or services. Nevertheless, techniques of SLI and SPI still form the core of SQC. Both are applications of statistical hypothesis testing to the problem of deciding whether the quality of lots or processes is satisfactory or not. In recent years, the tendency has been growing to adopt...
References: Reid, R. D., & Sanders, N. R. (2005). Wiley. Retrieved December 12, 2008, from Wiley Website: http://www.wiley.com/college/sc/reid/chap6.pdf
Allen, T. T. (2006). Part I - Statistical Quality Control. In Springer, Introduction To Engineering Statistics And Six Sigma (p. 47). Ohio: Springer-Verlag London Limited.
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