Abstract
We study the effect of the Phase I estimation error on the cumulative sum (CUSUM) chart. Impractically large amounts of Phase I data are needed to sufficiently reduce the variation in the in-control average run lengths (ARL) between practitioners. To reduce the effect of estimation error on the chart's performance we design the CUSUM chart such that the in-control ARL exceeds a desired value with a specified probability. This is achieved by adjusting the control limits using a bootstrap-based design technique. Such approach does affect the out-of-control performance of the chart; however, we find that this effect is relatively small.
| Original language | English |
|---|---|
| Pages (from-to) | 402-415 |
| Journal | Quality Engineering |
| Volume | 28 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Oct 2016 |
| Externally published | Yes |
Funding
The work of William H. Woodall was supported by National Science Foundation Grant CMMI-1436365.
Research Keywords
- average of ARL (AARL)
- bootstrap
- effect of estimation error
- standard deviation of average run length (SDARL)
- statistical process control (SPC)
- statistical process monitoring (SPM)
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