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Viacparametrové SPC – Multivariačné SPC×Control chart×
OdborPlánovanie experimentovPlánovanie experimentov
RodinaProcess / pipelineProcess / pipeline
Rok vzniku1947 (Hotelling's T²); mature multivariate SPC framework 1980s–2000s1924 (first use); 1931 (seminal book)
TvorcaHarold Hotelling (T² statistic); extended by Alt, Lowry, Montgomery, Mason & YoungWalter A. Shewhart (Bell Labs)
TypMultivariate quality-monitoring procedureStatistical monitoring and control technique
Pôvodný zdrojLowry, C. A., & Montgomery, D. C. (1995). A review of multivariate control charts. IIE Transactions, 27(6), 800–810. DOI ↗Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. link ↗
Ďalšie názvyMultivariate SPC, MSPC, Multi-response SPC, Multivariate statistical process controlShewhart chart, process-behavior chart, SPC chart, quality control chart
Príbuzné66
ZhrnutieMulti-response statistical process control (multivariate SPC) extends classical univariate control charting to processes where two or more correlated quality characteristics must be monitored simultaneously. By treating all responses as a joint distribution, it detects shifts that would be invisible when each response is charted independently, reducing false alarms and improving the sensitivity of process monitoring in manufacturing and service contexts.A control chart is a time-series graph with statistically derived upper and lower control limits that separates the natural, random variation of a process (common cause) from unusual, assignable variation (special cause). Invented by Walter Shewhart at Bell Labs in 1924, control charts remain the foundational tool of Statistical Process Control and are used across manufacturing, healthcare, software, and service industries to monitor whether a process remains stable and predictable over time.
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ScholarGatePorovnať metódy: Multi-response statistical process control · Control chart. Získané 2026-06-15 z https://scholargate.app/sk/compare