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Σχεδιασμός Πλήρους Παραγοντικού Πειράματος σε Βιομηχανικές Εφαρμογές×Στατιστικός Έλεγχος Διεργασιών×
ΠεδίοΠειραματικός ΣχεδιασμόςΠειραματικός Σχεδιασμός
ΟικογένειαProcess / pipelineProcess / pipeline
Έτος προέλευσης1926 (foundational); industrially systematized by Box, Hunter & Hunter ~1950s–19781924–1931
ΔημιουργόςRonald A. FisherWalter A. Shewhart
ΤύποςExperimental design / factorial experimentProcess monitoring and quality control method
Θεμελιώδης πηγήMontgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762
Εναλλακτικές ονομασίεςindustrial FFD, full factorial experiment, complete factorial design, 2^k factorial designSPC, statistical quality control, process control charting, Shewhart control
Συναφείς36
ΣύνοψηFull factorial design (FFD) applied in industrial settings is a structured experimental methodology in which every combination of factor levels is tested, enabling engineers to quantify main effects and all interaction effects among process or product variables. Widely used in manufacturing, chemical processing, materials science, and quality engineering, it provides a complete picture of how input factors jointly influence a response variable such as yield, strength, or defect rate.Statistical 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.
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ScholarGateΣύγκριση μεθόδων: Industrial applications full factorial design · Statistical Process Control. Ανακτήθηκε στις 2026-06-18 από https://scholargate.app/el/compare