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	Overall Equipment Effectiveness (OEE)	Ottimizzazione della Manutenzione	Six Sigma DMAIC
Campo	Gestione della qualità	Affidabilità	Gestione della qualità
Famiglia	Process / pipeline	Process / pipeline	Process / pipeline
Anno di origine	1988	2002	2014
Ideatore	Seiichi Nakajima	Hongzhou Wang	Motorola; Pyzdek & Keller
Tipo	Multiplicative KPI framework	decision optimization framework	Structured process improvement methodology
Fonte seminale	Nakajima, S. (1988). Introduction to TPM: Total Productive Maintenance. Productivity Press. ISBN: 978-0-915299-23-2	Wang, H. (2002). A survey of maintenance policies of deteriorating systems. European Journal of Operational Research, 139(3), 469–489.	Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9
Alias	OEE, Equipment Effectiveness Index, Machine Effectiveness Ratio, Toplam Ekipman Etkinliği	Optimal Maintenance Policy, Preventive Maintenance Scheduling, Predictive Maintenance Optimization, Bakım Optimizasyonu	DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC
Correlati	3	3	3
Sintesi	Overall Equipment Effectiveness (OEE) is a composite key performance indicator that quantifies how effectively a manufacturing operation uses its equipment relative to its full potential. Developed by Seiichi Nakajima in 1988 as a cornerstone metric of Total Productive Maintenance (TPM), OEE multiplies three loss factors—Availability, Performance, and Quality—to yield a single percentage that benchmarks actual productive output against ideal output.	Maintenance Optimization is a quantitative framework for determining the timing, type, and frequency of maintenance actions—preventive, predictive, or corrective—that minimize total cost or expected downtime over a system's operational life. Systematic formulations were consolidated by Hongzhou Wang (2002), whose survey unified age-replacement, block-replacement, and imperfect-repair policies under a common cost-rate structure applicable to deteriorating systems across engineering and operations management.	Six Sigma DMAIC is a data-driven, five-phase process improvement methodology — Define, Measure, Analyze, Improve, and Control — used to reduce defects and process variation to fewer than 3.4 defects per million opportunities. Originating at Motorola in the 1980s and systematized by practitioners including Pyzdek and Keller, it is widely adopted in manufacturing, healthcare, finance, and service industries seeking sustained quality gains.