Operational reliability assessment of radiotherapy equipment failures through integrated Pareto and FMECA analysis

Unplanned equipment and infrastructure interruptions are a persistent source of radiotherapy service loss, yet prioritization is often based on either downtime burden or risk criticality alone. This study analyzed five years of interruption logs to integrate a standardized failure taxonomy with downtime-based Pareto analysis and FMECA criticality scoring.

A harmonized event log captured asset class, subsystem, cause category, operational severity, downtime, and maintainability indicators, including response and repair times. Event burden and downtime distributions were quantified, Pareto rankings were performed at asset, subsystem, and cause levels, and FMECA Risk Priority Numbers were analyzed. Agreement between Pareto and FMECA priorities was assessed using Top-k overlap and Spearman rank correlation.

A total of 4200 events produced 16,006.4 h of service loss. Downtime per event was right-skewed, with a median of 0.93 h and an interquartile range of 0.43-2.50 h. Minor events comprised 42.95% of events but accounted for only 4.39% of downtime, whereas critical events represented 6.60% of events but generated 50.93% of downtime. Major events contributed 31.79% of downtime from 19.43% of events. Unit-level burden ranged from 755 to 1707 events and from 2990.9 to 6077.8 h of downtime. Downtime was dominated by LINAC failures, accounting for 60.5%, followed by HDR after loader faults at 15.0%, OIS/network interruptions at 8.6%, CT-sim faults at 6.9%, TPS-related events at 6.0%, and auxiliary infrastructure at 3.0%. The leading subsystem contributors were imaging systems at 1324.7 h, MLC components at 1178.7 h, and software/controls at 1152.5 h. The leading cause categories were hardware wear/aging at 4532.6 h, power instability at 2340.2 h, and vendor part delay at 2212.6 h. Median response times clustered between 0.60 and 0.61 h, while median repair times ranged from 0.62 to 0.86 h. Pareto and FMECA alignment was limited, with a Top-10 overlap of 3/10, a Top-5 overlap of 0/5, and a Spearman correlation of approximately 0.09.

Service loss was concentrated in a minority of major and critical episodes. Combining Pareto analysis, which prioritizes lost hours, with FMECA, which identifies rare but high-criticality modes, supports balanced and actionable prioritization for maintenance planning, spare-parts and logistics strategy, power conditioning, and digital infrastructure resilience.

Radiotherapy services can be disrupted when equipment fails, which may delay treatment for patients. This study reviewed five years of equipment failure records to understand which problems caused the most service interruptions and how best to prioritize them. This study found that a small number of serious issues caused most delays, and using more than one method helped identify priorities more clearly. This matters because better planning can reduce delays and support safer, more reliable treatment.