Statistical Quality Control

Imagine a product that you use a lot, and then think about the most important feature that determines the quality of that product for you. For example, this could be the life of the battery for a mobile phone. What would you say if you were told that none of the original batteries placed in the same brand and model product are exactly the same, or even if you are unlucky, you will come across a battery with a short lifespan and therefore the battery will run out after 6-7 months of use?
The first explanation that manufacturers will make to unlucky customers is that this is usually due to incorrect or heavy use. But let us tell you a secret. There may also be serious differences between the lifetimes of batteries used in exactly the same conditions. Such differences appear in a wide variety of products such as white goods, electronic goods, automobiles, and in the various features of these products. The engine sound insulation of two cars of the same model is not at the same level, such as turning the knob of one of the two dishwashers of the same model is easy and the other is difficult. In addition, the same problems are valid for a company that purchases raw materials or semi-finished products from a supplier. These differences are due to the fact that the products cannot be produced exactly as they were designed. This leads to serious customer dissatisfaction and loss of customers. For this reason, systematic studies are carried out in all sectors to make production more suitable for design.
All studies conducted for this purpose fall within the field of statistical quality control. The main subjects of these studies are the measurement of product features, quality characteristics in technical terms, statistical modeling and analysis of measurements, and as a result, the discovery and elimination of the causes of non-compliance with the design. Today, we see that these studies are sometimes carried out in the form of total quality management, sometimes ISO 9000, and sometimes six sigma applications. After discussing these different quality management approaches in the book, the methods used for statistical quality control are explained with various industry applications.