Abstract
Already Yashchin (IBM J Res Dev 29(4):377–391, 1985), and of course Lucas (J Qual Technol 14(2):51–59, 1982) 3 years earlier, studied CUSUM chart supplemented by Shewhart limits. Interestingly, Yashchin proposed to calibrate the detecting scheme via P ∞ (RL > K) ≥ 1 − α for the run length (stopping time) RL in the in-control case. Calculating the RL distribution or related quantities such as the ARL (Average Run Length) are slightly complicated numerical tasks. Similarly to Capizzi and Masarotto (Stat Comput 20(1):23–33, 2010) who utilized Clenshaw-Curtis quadrature to tackle the ARL integral equation, we deploy less common numerical techniques such as collocation to determine the ARL. Note that the two-sided CUSUM chart consisting of two one-sided charts leads to a more demanding numerical problem than the single two-sided EWMA chart.
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Appendices
Appendix 1: Collocation Design for More Than r = 2 Intervals
Here we provide the generalization from r = 2, dealt with in Sect. 2, to general r ∈{2, 3, …}. To start with the first interval, 0 ≤ s ≤ h − ε, we simply state that the shape of the collocation design does not change for greater r. For the succeeding intervals, h − (r − m + 1)ε < s ≤ h − (r − m)ε with m = 2, …, r − 1, the following structure is utilized.
Note that these equations are not present for r = 2. However, the last interval, h − ε < s ≤ h, is considered for all r ≥ 2. The general structure of the corresponding collocation equation is similar to the above one (now with m = r) except for the upper limit of the last integral where ε + s has to be replaced by h.
Appendix 2: Two-Sided CUSUM Chart
Starting with case (i), s + + s −≤ 2k, and re-writing the corresponding integral equation results in:
Setting s + or s − to zero in (6) yields:
Using this, the first line of the integral equation’s right-hand side changes to
Substituting x = z + k − s in (2) while replacing the upper limit by h results in
so that the line under analysis simplifies heavily to
In a similar way we treat the second line ending in
For the second line we made use of φ(−x) = φ(x) in the in-control case (δ = 0), while for δ≠0 we have to change the sign of δ, hence φ δ (−x) = φ −δ(x). All together resembles (the “1” consumes the disturbing parts of the above two ratios)
Turning to case (ii), 2k < s + + s −≤ h + 2k, we recall the shape of the related integral equation:
First we plug (6) into and transform the second line
with the last integral subsequently reduced to Φ(s −− k) − Φ(k − s +). We rewrite the first line as for case (i) and merge, borrowing \(\mathcal {L}^-(0) / \big (\mathcal {L}^+(0) + \mathcal {L}^-(0)\big )\),
to get
by applying again (7). Exploiting Φ(s −− k) = 1 − Φ(k − s −) we proceed in a similar way with the third line by collecting after transforming both integrals as in the first case
which results in
The two “borrowed” terms
are compensated with the 1 on the right-hand side of the original equation. The last remaining term forms together with the two others
This completes the proof.
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Knoth, S. (2018). New Results for Two-Sided CUSUM-Shewhart Control Charts. In: Knoth, S., Schmid, W. (eds) Frontiers in Statistical Quality Control 12. Frontiers in Statistical Quality Control. Springer, Cham. https://doi.org/10.1007/978-3-319-75295-2_3
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