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Статистичне керування процесами×Планування експериментів×
ГалузьПланування експериментуПланування експерименту
РодинаProcess / pipelineProcess / pipeline
Рік появи1924–19311935
Автор методуWalter A. ShewhartRonald A. Fisher
ТипProcess monitoring and quality control methodExperimental planning framework
Основоположне джерелоShewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
Інші назвиSPC, statistical quality control, process control charting, Shewhart controlDOE, experimental design, factorial experimentation, planned experimentation
Пов'язані63
ПідсумокStatistical Process Control (SPC) is a data-driven quality method that uses statistical techniques — primarily control charts — to monitor a manufacturing or service process over time. By distinguishing natural process variation (common cause) from unusual, actionable variation (special cause), SPC enables practitioners to maintain processes in a stable, predictable state and to detect problems early, before defective output reaches customers.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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ScholarGateПорівняння методів: Statistical Process Control · Design of experiments. Отримано 2026-06-17 з https://scholargate.app/uk/compare