2013Skola biznisaOpen access

The application of mean control chart in managing industrial processes

Nataša Papić-Blagojević, Zbigniew Paszek

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Abstract

Along with the advent of mass production comes the problem of monitoring and maintaining the quality of the product, which stressed the need for the application of selected statistical and mathematical methods in the control process. The main objective of applying the methods of statistical control is continuous quality improvement through permanent monitoring of the process in order to discover the causes of errors. Shewart charts are the most popular method of statistical process control, which performs separation of controlled and uncontrolled variations along with detection of increased variations. This paper presents the example of Shewart mean control chart with application in managing industrial process.

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Along with the advent of mass production comes the problem of monitoring and maintaining the quality of the product, which stressed the need for the application of selected statistical and mathematical methods in the control process. The main objective of applying the methods of statistical control is continuous quality improvement through permanent monitoring of the process in order to discover the causes of errors. Shewart charts are the most popular method of statistical process control, which performs separation of controlled and uncontrolled variations along with detection of increased variations. This paper presents the example of Shewart mean control chart with application in managing industrial process.

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Available abstract

Along with the advent of mass production comes the problem of monitoring and maintaining the quality of the product, which stressed the need for the application of selected statistical and mathematical methods in the control process. The main objective of applying the methods of statistical control is continuous quality improvement through permanent monitoring of the process in order to discover the causes of errors. Shewart charts are the most popular method of statistical process control, which performs separation of controlled and uncontrolled variations along with detection of increased variations. This paper presents the example of Shewart mean control chart with application in managing industrial process.

Key concepts: Control chart, Statistical process control, Computer science, Process (computing), Chart, Control limits, Product (mathematics), Quality (philosophy)

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