Overview
Read this article from a comprehensive knowledge base, updated and supplemented with articles reviewed by scientific committees.
Read the articleAUTHORS
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Pascal VEDEL: Consulting and training in management and organization of industrial companies
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Jean-Michel POU: Chairman and founder of Delta Mu
INTRODUCTION
You implement a manufacturing process to produce a product whose measured characteristics vary randomly as a result of random variations in process parameters. Statistical Process Control, SPC, enables early detection of process deviations before they have a chance to affect product quality.
The benefits of the MSP method are :
help to differentiate between "normal" random process variations and those due to an assignable cause (e.g. an adjustment to one of the operating parameters). This allows corrections to be applied only when necessary, helping to stabilize the process and reduce product variability;
to allow correction of operating parameters before product quality is affected and thus reduce non-quality costs;
enable operators to better "visualize" product quality and know when to act. In this way, operator responsibility and autonomy can be enhanced, while product quality is better stabilized.
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Bibliography
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Websites
fr.wikipedia.org Wikipedia article on normal distribution, with links to numerical tests to check whether a population follows a normal distribution.
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