AiVibeQuality, Reliability & Maintenance
Failure Mode, Effects and Criticality Analysis (FMECA)
FMECA extends failure mode and effects analysis by ranking each failure mode by its criticality, a combination of the severity of its effects and its probability or frequency of occurrence, to prioritise design and maintenance actions.
An FMECA first performs a failure mode and effects analysis, identifying for each item its failure modes, causes and local and system-level effects. The criticality analysis then rates each failure mode. Quantitative approaches, as described in the former United States military standard MIL-STD-1629A, compute a criticality number from the part failure rate, the failure mode ratio, the probability that the failure causes the stated effect and the operating time. Qualitative approaches rank failure modes on a criticality matrix that plots severity against probability of occurrence.
FMECA is used in aerospace, defence, nuclear, rail, oil and gas and other high-consequence industries, both during design and to build maintenance programmes. In reliability-centred maintenance, criticality rankings help decide which failure modes need proactive tasks. Results also guide redundancy, spare parts holdings and inspection priorities.
Like FMEA, FMECA depends on accurate failure data, knowledgeable participants and consistent rating scales, and it analyses single failure modes rather than combinations, for which fault tree analysis is better suited. MIL-STD-1629A has been cancelled but is still widely referenced, and IEC 60812 describes procedures for both FMEA and FMECA.
Key points
- Adds criticality ranking to failure mode and effects analysis.
- Criticality combines severity with probability or frequency of occurrence.
- Quantitative methods derive from MIL-STD-1629A; qualitative ones use a criticality matrix.
- IEC 60812 describes FMEA and FMECA procedures.
Where AiVibe comes in
AiAmbA AI Factory use cases include predictive maintenance and visual inspection on textile, automotive and electronics lines. AiAmbA IoT normalises industrial signals from protocols such as OPC UA and MQTT, with driver availability confirmed per installation.
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