Journal of Quality in Maintenance Engineering· 2026Q2
From internal audit to maintenance learning: feedback mechanisms in safety-critical asset management systems
- 0citations
- Q2SCImago
- 2026year
Short summary
Six links (diagnosis, corrective action, effectiveness verification, escalation, requirement revision, recurrence monitoring) distinguish learning-oriented closure from administrative closure of maintenance findings in safety-critical systems.
AI-generated from the title and abstract; the full text is not read.
Key points
- Six links (diagnosis, corrective action, effectiveness verification, escalation, requirement revision, recurrence monitoring) distinguish learning-oriented from administrative closure of maintenance findings.
- Public sources more consistently document deficiencies and recommendations than their implementation and effectiveness verification.
- Recurring coded patterns include procedure and monitoring weaknesses, prior warnings, weak requirements, maintenance-data problems, and long feedback latency.
- The study assesses public-source traceability, not internal organizational learning or corrective-action effectiveness.
AI-generated from the title and abstract; the full text is not read.
Abstract
Purpose 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.
The authors' abstract, as published at the source. Journal of Quality in Maintenance Engineering, 2026 · DOI ↗
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Field: Radiological and Ultrasound Technology
Radiological and Ultrasound TechnologyHealth Professions