Bandingkan kaedah

	Analisis Mod Kegagalan dan Kesan Berbantukan Pengoptimuman	Kawalan Proses Statistik
Bidang	Reka Bentuk Eksperimen	Reka Bentuk Eksperimen
Keluarga	Process / pipeline	Process / pipeline
Tahun asal	1949 (FMEA origin); optimization-assisted variants: 1990s–2000s	1924–1931
Pengasas	Extension of FMEA (U.S. Military, MIL-STD-1629, 1949); optimization integration developed in reliability and quality engineering literature from the 1990s onward	Walter A. Shewhart
Jenis	Reliability and risk analysis technique with embedded optimization	Process monitoring and quality control method
Sumber perintis	Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762
Alias	Optimization-assisted FMEA, FMEA with optimization, OA-FMEA, Optimized risk priority ranking	SPC, statistical quality control, process control charting, Shewhart control
Berkaitan	6	6
Ringkasan	Optimization-assisted FMEA extends classical Failure Mode and Effects Analysis by embedding mathematical optimization algorithms — such as linear programming, multi-objective optimization, or metaheuristics — into the risk prioritization step. Rather than relying solely on the Risk Priority Number (RPN = Severity × Occurrence × Detectability), the approach frames corrective-action selection and resource allocation as an optimization problem, enabling more defensible, constraint-aware ranking and mitigation of failure modes.	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.