Περίληψη : | Statistical Quality Control is an important tool for improving the quality of a process. That is why it is more and more applied to industry. It uses statistical techniques for checking, analyzing and improving the quality of a process and of the final product by reducing their variability. Statistical Quality Control charts are effective and easily applicable tools to perform that task. However, a basic assumption for applying them is that observations from the process are independent and identically distributed and follow the normal distribution while this assumption is often violated in industry process.The purpose of this essay is to investigate the application of statistical process control in auto-correlated data and find out:(a). Which type of quality control charts could be applied to correlatedobservations in a production process?(b). What are the consequences of ignoring correlation in the data by applying traditional quality control charts which assume uncorrelated measurements?Applications on simulated data will be provided to illustrate the results in questions 1 and 2.
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