From internal audit to maintenance learning: feedback mechanisms in safety-critical asset management systems
Karim HardyPurpose
This article examines how maintenance-related findings documented in audits, inspections, regulatory reviews and investigations may function as traceable feedback signals in safety-critical asset management systems.
Design/methodology/approach
A qualitative comparative design uses public official sources covering 30 asset-intensive cases and 120 standardized coded observations. Each case contributes maintenance-related, corrective-action, verification or oversight, and learning-related evidence.
Findings
Within the coded sample, public sources document deficiencies and recommendations more consistently than implementation and effectiveness verification. The operational synthesis identifies six links – diagnosis, corrective action, effectiveness verification, escalation, requirement revision and recurrence monitoring – that may distinguish learning-oriented closure from administrative closure. Recurring coded patterns include procedure and monitoring weaknesses, prior warnings, weak requirements, maintenance-data problems and long feedback latency.
Research limitations/implications
The study assesses public-source traceability rather than internal organizational learning or corrective-action effectiveness. It supports analytical generalization across common mechanisms, not statistical prevalence estimates or direct industry comparisons.
Practical implications
The diagnostic model may help maintenance, audit, asset and quality managers connect significant findings to barriers, degradation mechanisms, verification evidence, recurrence indicators and management review.
Originality/value
The article offers an operational integration of maintenance engineering, quality auditing, corrective-action systems, asset management and organizational learning by treating maintenance-related findings as engineering feedback signals.