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Mitmevastusprotsessi võimekuse analüüs×Katseplaneerimine×
ValdkondKatsedisainKatsedisain
PerekondProcess / pipelineProcess / pipeline
Tekkeaasta1993–1994 (foundational multivariate indices)1935
LoojaTaam, Subbaiah & Liddy (multivariate capability); Hubele, Shahriari & Cheng (MCpm)Ronald A. Fisher
TüüpQuantitative quality / process assessment methodExperimental planning framework
AlgallikasTaam, W., Subbaiah, P., & Liddy, J. W. (1993). A note on multivariate capability indices. Journal of Applied Statistics, 20(3), 339–351. link ↗Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
RööpnimetusedMRPCA, multivariate process capability, multi-characteristic capability analysis, vector process capabilityDOE, experimental design, factorial experimentation, planned experimentation
Seotud63
KokkuvõteMulti-response process capability analysis extends classical single-response capability indices (Cp, Cpk) to situations where a process must simultaneously satisfy specification limits on two or more correlated quality characteristics. Rather than evaluating each response in isolation, it assesses the joint probability that all characteristics fall within their respective tolerance regions, yielding a more realistic picture of overall process performance in multi-characteristic manufacturing and engineering settings.Design of Experiments (DOE) is a systematic framework for planning, conducting, and analyzing controlled experiments to determine how multiple input factors simultaneously affect one or more responses. Introduced by Ronald A. Fisher in 1935, DOE allows researchers and engineers to identify causal relationships, quantify factor effects, and find optimal settings efficiently — using far fewer runs than one-factor-at-a-time approaches. It is foundational in engineering, manufacturing, agriculture, and applied sciences.
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ScholarGateVõrdle meetodeid: Multi-response Process Capability Analysis · Design of experiments. Loetud 2026-06-17 aadressilt https://scholargate.app/et/compare