Analysis of False Alarms in Control Charts
DOI:
https://doi.org/10.5281/zenodo.20166125Keywords:
Statistical Process Control, Control Charts, False AlarmsAbstract
Control charts are statistical tools used in Statistical Process Control (SPC) to monitor the stability of production processes. During monitoring, signals—referred to as alarms—may occur, indicating potential problems in the process. An inherent aspect of control charts is the occurrence of false alarms, which are indications of problems when no actual abnormality exists. This study aims to evaluate the frequency of false alarms based on different types of point patterns on the chart. The analysis was conducted through simulation using the Python programming language, and the results indicate that the frequency of false alarms increases with the inclusion of additional alarm types. The average number of inspections until a false alarm tends to decrease, dropping by up to 80% when five types of alarms are used.
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