ScholarGate
Assistent

Methoden vergleichen

Prüfen Sie die ausgewählten Methoden nebeneinander; abweichende Zeilen sind hervorgehoben.

Multi-response Root Cause Analysis×Multi-response Design of Experiments×
FachgebietVersuchsplanungVersuchsplanung
FamilieProcess / pipelineProcess / pipeline
Entstehungsjahr1990s–2000s (multi-response extension of classical RCA)1980 (desirability function formalization); DoE roots from Fisher, 1920s–1930s
UrheberRoot Cause Analysis tradition (Kepner-Tregoe, Ishikawa, Deming); multi-response extension in Six Sigma and quality engineering practiceDerringer & Suich (desirability function); Montgomery (systematic DoE integration)
TypSystematic problem-solving methodExperimental optimization methodology
Wegweisende QuelleAndersen, B., & Fagerhaug, T. (2006). Root Cause Analysis: Simplified Tools and Techniques (2nd ed.). ASQ Quality Press. ISBN: 978-0873896924Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219. DOI ↗
AliasnamenMulti-KPI RCA, Multi-output RCA, Multi-response RCA, MRCAMulti-response DoE, Multiple-response optimization, Multi-objective DoE, MRDoE
Verwandt64
ZusammenfassungMulti-response Root Cause Analysis (MRCA) is a structured problem-solving method that identifies the underlying causes of failures or deviations across multiple simultaneous response variables (KPIs, quality characteristics, or process outputs). It extends classical RCA to settings where a single root cause can propagate into several observed defects or performance degradations at once, which is common in manufacturing, engineering, and service-quality contexts.Multi-response Design of Experiments (MRDoE) extends classical DoE to situations where several response variables must be optimized simultaneously. Rather than tuning factors for a single output, the experimenter fits separate regression or response-surface models for each response, then combines them — most often via Derringer and Suich's desirability function — into a single composite score that guides the search for factor settings satisfying all response targets at once.
ScholarGateDatensatz
  1. v1
  2. 2 Quellen
  3. PUBLISHED
  1. v1
  2. 2 Quellen
  3. PUBLISHED

Zur Suche Folien herunterladen

ScholarGateMethoden vergleichen: Multi-response Root Cause Analysis · Multi-response Design of Experiments. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare