Failure Code
How does a failure code differ from a failure mode?
A failure mode is the RCM language describing the physical event (e.g., 'bearing failed due to lack of lubrication'), whereas a failure code is the CMMS-specific alphanumeric shorthand (e.g., B-01-LUB) that concatenates component, problem, and cause for database sorting.
What is the standard structure for a failure hierarchy?
A common 4-level design at the asset level concatenates Component-Part, Component Problem, and Cause Code from validated fields into a single code on the work order.
Why is the PCA (Problem-Cause-Action) framework critical?
It acts as a decision tree where custom codes link specific failure modes to solutions, ensuring that every work order captures the full diagnostic logic required for pattern analysis.
How do failure codes enable 'Asset Offender' analysis?
Structured codes allow reliability teams to generate failure analytic reports that identify 'worst offenders' across multiple assets by aggregating identical cause codes, revealing systemic issues.
A failure code is a standardized alphanumeric or numeric identifier assigned to a corrective maintenance work order in a CMMS to classify the problem, cause, and action of an asset failure. It converts free-text descriptions into structured, queryable data for reliability analysis, enabling consistent documentation and data mining for failure trends.
In shop floor maintenance, technicians select predefined failure codes from a hierarchy (e.g., Problem-Cause-Action framework) when closing work orders, replacing narrative descriptions with consistent data points. These codes are stored in asset history within the CMMS, allowing reliability engineers to sort data for failure trends, identify common failure modes, and implement remedial actions. The system supports data mining to drive Reliability-Centered Maintenance (RCM) programs by refining failure event documentation based on logical groupings, enabling effective pattern analysis and systemic issue identification.
Inconsistent coding between technicians, such as selecting 'lubrication issue' versus 'over-lubrication', destroys data integrity and hides trends.
Recording only the problem (symptom) like 'high vibration' without the cause (e.g., 'bearing fatigue') prevents effective root cause analysis and recurrence prevention.
Over-reliance on free text instead of codes creates unsearchable data, making it impossible to aggregate failure patterns or benchmark reliability.