Abstract
The standard task within SPC is the detection of an unforeseen shift in the mean level of the sequence of typically normally distributed random variables. Only some papers deal with a not considerably less common pattern in industrial practice: gradual changes because of tool wear or similar causes. In the small list of the currently available papers both existing control charts for the mean under drift are studied and new ones are created. It is worth noting that except Gan (J Stat Comput Simul 38:181–200, 1991; Statistician 41:71–84, 1992) no convincing numerical algorithms are presented for calculating characteristics for control charts under and for drift. The good message is that mean level control charts are also suited for detecting drifts. This paper provides some more numerical results including a competing method to Gan’s algorithm and presents various schemes.
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© 2012 Springer-Verlag Berlin Heidelberg
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Knoth, S. (2012). More on Control Charting Under Drift. In: Lenz, HJ., Schmid, W., Wilrich, PT. (eds) Frontiers in Statistical Quality Control 10. Frontiers in Statistical Quality Control, vol 10. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2846-7_4
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DOI: https://doi.org/10.1007/978-3-7908-2846-7_4
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