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| Vankka prosessikyvykkyysanalyysi× | Robust Control Chart× | |
|---|---|---|
| Tieteenala | Koesuunnittelu | Koesuunnittelu |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 1990s–2000s | 1989–1997 (foundational period) |
| Kehittäjä≠ | Extended from classical PCA (Kane, 1986; Juran, 1974) via robust statistics (Huber, 1981); formalized for capability indices by Tong & Chen (1998) and Pearn & Kotz (1994) | David M. Rocke; L. G. Tatum (key contributors) |
| Tyyppi≠ | Quantitative quality engineering method | Statistical process monitoring technique |
| Alkuperäislähde≠ | Maravelakis, P. E., Bersimis, S., Panaretos, J., & Psarakis, S. (2004). Identifying the out of control variable in a multivariate control chart. Communications in Statistics - Theory and Methods, 33(10), 2499–2510. link ↗ | Tatum, L. G. (1997). Robust estimation of the process standard deviation for control charts. Technometrics, 39(2), 127–141. DOI ↗ |
| Rinnakkaisnimet | Robust PCA, Robust Capability Indices, Outlier-Resistant Capability Analysis, Robust Cpk Analysis | robust Shewhart chart, outlier-resistant control chart, robust SPC chart, distribution-free control chart |
| Liittyvät | 6 | 6 |
| Tiivistelmä≠ | Robust process capability analysis extends classical capability indices (Cp, Cpk, Ppk) by replacing the sample mean and standard deviation with robust location and scale estimators — such as the median, trimmed mean, MAD, or IQR-based spread — so that outliers and non-normal process distributions do not inflate or distort the capability estimate. The result is a more reliable assessment of whether a manufacturing or service process can consistently meet specification limits. | A robust control chart replaces the classical mean and standard deviation estimators in a Shewhart-style chart with resistant alternatives — such as the median and median absolute deviation (MAD) — so that a small fraction of outliers or non-normal process data cannot distort the control limits. The approach preserves the real-time monitoring logic of standard control charts while protecting against inflated or deflated limits caused by contaminated Phase I reference data. |
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