Quality control analysis involves planning, acquiring data, and analyzing results to improve processes. It’s used in software development, service delivery, and manufacturing. Planning is crucial, including employee training and capturing data at key stages. Diagnostic techniques like flow charts and SPC are used to analyze data, and acceptance sampling is used for large batches.
Quality control analysis involves planning, checking for defects, acquiring data and analyzing the results to improve the process in the future. The analyst uses a variety of techniques to review defect data and to determine the causes of defects. Software packages are often used to facilitate the capture and analysis of quality control results.
Many organizations use quality control analysis. It is commonly used in software development, service delivery, and product manufacturing. While the high-level concepts are similar, the details and methods of quality control analysis can vary for each specific organization’s needs.
Successful quality control analysis requires significant planning. Before conducting the test, the analyst should consider what to test and how to test. Employee training needs and ways to identify, classify and document test results should also be included in the planning.
The analyst should plan to capture quality control data at key stages in the process. It is usually less expensive to find and fix defects early in the cycle, and your plan may take this into account. In the case of software development, this can mean efforts to reduce defects at the requirements stage. For a manufacturer, this may mean testing incoming subcomponents or raw materials for adherence to quality standards.
Other key parts of the process may occur between operations, especially before a more expensive operation. For example, a rubber molded parts manufacturer might mean sample batches of rubber compound after it’s been mixed but before it’s molded. If the batch of rubber compound is bad, it’s less expensive to get it at this point.
Employees will often need training to properly identify and categorize various defects. They may also need to log any flaws they find. Statistical quality control software can be used to capture and graph defect data.
Once the data is captured, a variety of diagnostic techniques can be used to analyze it. Some common techniques include flow charts, Pareto charts, and fishbone charts. Skillful use of these diagnostic techniques can identify factors that could cause defects.
One technique that can be used to verify that a process is running within quality standards is Statistical Process Control (SPC). This technique verifies that the process can meet the established quality objectives. It also takes into account random variations that cannot be controlled.
Another quality control method acceptance sampling. In this technique, a statistically significant sample is tested. It is often used when manufacturers receive a large quantity of sub-components and it is not convenient or reasonable to check the entire batch. A quality control analyst can determine how many samples need to be tested to verify that the entire lot meets quality standards.
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