Abstract
This article presents an alternative approach, based on time series analysis of all the real-time process data. The time series approach is employed because the sequence of process observations may not be statistically independent. The autocorrelative structure in the data may be captured using an ARIMA model, and the residuals from this model are shown to be an effective input signal for a variety of statistical process control procedures.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 309-317 |
| Number of pages | 9 |
| Journal | Quality and Reliability Engineering International |
| Volume | 5 |
| Issue number | 4 |
| State | Published - Oct 1989 |
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ASJC Scopus subject areas
- Management Science and Operations Research
- Engineering (miscellaneous)
Cite this
Time-series approach to discrete real-time process quality control. / Yourstone, Steven A.; Montgomery, Douglas.
In: Quality and Reliability Engineering International, Vol. 5, No. 4, 10.1989, p. 309-317.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Time-series approach to discrete real-time process quality control
AU - Yourstone, Steven A.
AU - Montgomery, Douglas
PY - 1989/10
Y1 - 1989/10
N2 - This article presents an alternative approach, based on time series analysis of all the real-time process data. The time series approach is employed because the sequence of process observations may not be statistically independent. The autocorrelative structure in the data may be captured using an ARIMA model, and the residuals from this model are shown to be an effective input signal for a variety of statistical process control procedures.
AB - This article presents an alternative approach, based on time series analysis of all the real-time process data. The time series approach is employed because the sequence of process observations may not be statistically independent. The autocorrelative structure in the data may be captured using an ARIMA model, and the residuals from this model are shown to be an effective input signal for a variety of statistical process control procedures.
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UR - http://www.scopus.com/inward/citedby.url?scp=0024754256&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:0024754256
VL - 5
SP - 309
EP - 317
JO - Quality and Reliability Engineering International
JF - Quality and Reliability Engineering International
SN - 0748-8017
IS - 4
ER -