Quality, Reliability & Maintenance
Reliability-Centred Maintenance (RCM)
Reliability-centred maintenance is a structured process for determining the maintenance requirements of physical assets by analysing their functions, failure modes and failure consequences, and selecting tasks that are technically feasible and worth doing.
RCM originated in civil aviation. A 1978 report by F. Stanley Nowlan and Howard Heap of United Airlines, prepared for the United States Department of Defense, showed that many failures are not age-related and that scheduled overhaul often does little to improve reliability. An RCM analysis asks a set of questions about each asset: its functions and performance standards, how it can fail to fulfil them, what causes each failure, what happens when it fails, why each failure matters, what can be done to predict or prevent it, and what should be done if no suitable proactive task exists.
RCM is used in aviation, defence, power generation, oil and gas, rail and manufacturing to build maintenance programmes for critical assets. Failure consequences are classified, for example as hidden, safety and environmental, operational or non-operational, and the outcome is a mix of condition-based tasks, scheduled restoration or discard, failure-finding tasks for hidden failures, redesign and deliberate run-to-failure.
Full RCM analysis is resource-intensive, so organisations often apply it to the most critical assets and use streamlined methods elsewhere, although SAE JA1011 sets out the criteria a process must meet to be called RCM. Its quality depends on knowledgeable participants and good failure data, and the resulting programme should be reviewed as operating experience accumulates.
Key points
- Selects maintenance tasks from functions, failure modes and consequences.
- Originated in civil aviation with the Nowlan and Heap report.
- Answers seven questions, from functions to default actions.
- SAE JA1011 sets out criteria for a process to be called RCM.
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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