What is Statistical Analysis in Quality Control?
Statistical analysis in quality control is where statistical methods are used to measure, monitor and maintain the overall quality of products. Over time, the results help processes, such as manufacturing, ensure that the procedures will produce more specification-conforming products, therefore creating less waste. At BDK, we use both AQL and Cpk techniques in order to preserve our reputation for outstanding quality.
AQL, Acceptance Quality Limit, refers to the maximum number or percentage of defective products beyond which a batch is rejected. For example, if you set your AQL as 2% this means that if there are more than 2% defective items in a batch, then all products in this batch will be rejected. The production process will then be reviewed to work out the areas that are causing the defects.
Usually, different AQLs are set for different levels of defect e.g. critical, major and minor; the lower the AQL, the less risk there is of encountering a defect. This statistical tool is used either during production or during the final outgoing inspections.
Cp and Cpk techniques are another type of statistical method we undertake here at BDK, which is often referred to as Process Capability. These techniques measure our levels of consistency compared to our average performance; this means that we can predict and verify if our longstanding processes will meet customer specifications and requirements for the future.
The Cp and the Cpk present different capabilities of the chosen process. Cpk accounts for the natural variability of the process by showing the number of standard deviations the specification limits are from the centre of the process. Cp is the capability that the process could achieve if it was centred directly between the specification limits. If the Cpk is negative, the average of the process is outside the specification limits leading to more defects.
Why is Statistical Analysis important?
The importance and the benefits of these statistical methods is that they allow us to detect any problems early enough to prevent them from happening in the future. As well as reducing waste, they also reduce the time required to produce our products, meaning we can produce a larger number of items with consistent high quality results.
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