Run-to-failure (RTF) maintenance is a deliberate maintenance strategy in which equipment is operated until it fails, with no preventive or predictive interventions performed beforehand. Unlike unplanned breakdowns caused by neglected maintenance, RTF is a calculated decision based on cost-benefit analysis, asset criticality, and operational impact. Though often misunderstood as a passive or reactive approach, RTF can be a highly efficient method when applied correctly to the right class of assets—typically those that are non-critical, inexpensive to replace, or have a random failure pattern that cannot be reliably predicted.
In industrial environments, maintenance strategies must align with both production goals and financial constraints. While preventive and predictive maintenance dominate discussions around reliability, RTF remains a practical choice for certain components. For example, replacing a standard fluorescent tube only after it burns out—rather than on a fixed schedule—is a common and sensible RTF application. Similarly, low-cost sensors, non-essential fans, or auxiliary conveyors with built-in redundancy may be better managed through RTF than through time-based servicing that adds labor and parts cost without meaningful reliability gain.
Technical Foundations of Run-to-Failure: Understanding Failure Patterns and Asset Criticality
To implement RTF effectively, maintenance professionals must first understand the underlying failure behavior of assets. The classic study by Nowlan and Heap for the U.S. Department of Defense introduced the concept of six failure patterns, showing that only a small percentage of industrial equipment follows a traditional “wear-out” curve (Pattern A), where age-related preventive replacement makes sense. Many components—especially electronics, seals, or bearings under stable loads—exhibit random failures (Patterns D, E, or F), meaning their likelihood of failure does not increase significantly with age. For these, preventive replacement offers little benefit and may even increase costs due to unnecessary labor and premature part disposal.
Asset criticality assessment is the second pillar of RTF strategy. Criticality is typically evaluated across three dimensions: safety, operational impact, and financial consequence. A failed safety valve on a pressure vessel is high-critical due to potential hazards; its RTF use would be unacceptable. In contrast, a failed indicator light on a control panel may cause zero downtime and pose no safety risk—making RTF a logical choice. Maintenance teams should use formal criticality matrices to categorize assets systematically. Only those falling into low-risk categories should be considered for RTF.
RTF is most effective when the mean time to repair (MTTR) is short and spare parts are readily available. If replacing a failed item takes hours due to special ordering or complex disassembly, the downtime cost may outweigh any savings from skipping preventive actions. Therefore, RTF suitability also depends on logistical readiness—inventory levels, technician skill, and access to documentation.
Common Misapplications and Risks of Poor RTF Implementation
One major pitfall in maintenance programs is the accidental or default use of RTF on critical assets due to resource constraints or lack of planning. This is not true strategic RTF—it is unplanned reactive maintenance, which leads to higher costs, extended downtime, and potential safety incidents. For instance, running a primary hydraulic pump to failure on a stamping press without a backup may halt an entire production line for days, costing tens of thousands in lost output.
Another risk arises when asset roles change over time. A motor that once powered a non-essential cooling fan might later become part of a critical refrigeration loop due to process modifications. If its maintenance strategy isn’t reevaluated, it remains on RTF by inertia, creating a hidden vulnerability. Regular asset strategy reviews—at least annually or after major process changes—are essential to ensure alignment between function and maintenance approach.
Furthermore, RTF should never be confused with “no maintenance.” Even RTF assets may require basic condition monitoring or cleaning to ensure safe failure modes. For example, a dust-clogged exhaust fan allowed to run to failure could overheat and pose a fire hazard. Thus, RTF does not eliminate all maintenance—it simply removes scheduled component replacement or inspection where those actions don’t improve outcomes.
Integrating Run-to-Failure into a Balanced Maintenance Program
A mature maintenance strategy rarely relies on a single approach. Instead, it uses a mix: predictive maintenance for high-value rotating equipment, preventive for time-dependent wear items, and RTF for low-impact components. The goal is to allocate resources where they deliver the highest return in reliability and cost savings.
To operationalize this, organizations should document their maintenance strategy for each asset in a master equipment list. This includes the chosen approach (e.g., RTF, PM, PdM), justification based on failure data and criticality, required spare parts, and response procedures upon failure. Digital tools like CMMS platforms are essential for maintaining this strategy at scale.
How TeroTAM Enables Intelligent and Controlled Run-to-Failure Execution
TeroTAM supports strategic RTF implementation through structured asset management and real-time performance tracking. Within the system, each asset can be assigned a maintenance strategy flag—such as “Run-to-Failure”—along with supporting metadata like criticality score, failure history, and spare parts inventory status. This prevents confusion between intentional RTF and neglected maintenance.
When an RTF asset fails, TeroTAM streamlines the response. Technicians can quickly access prior work orders, standard repair procedures, and real-time parts availability. Managers can analyze whether the actual failure frequency and cost align with initial assumptions. If a supposedly low-risk pump fails three times in two months, TeroTAM’s analytics highlight the anomaly, prompting a strategy review.
Key technical capabilities that support RTF in TeroTAM include:
- Asset strategy tagging: Clearly label assets under RTF to avoid misclassification
- Automated work order triggers: Generate repair requests instantly upon failure report
- Cost-per-failure tracking: Compare actual repair and downtime costs against preventive alternatives
- Criticality-based filtering: View all RTF assets by risk level to audit appropriateness
- Spare parts linkage: Ensure quick replacement by linking RTF assets to min/max inventory levels
- Failure mode logging: Record root causes to detect hidden patterns (e.g., voltage spikes affecting multiple RTF sensors)
- KPI dashboards: Monitor MTTR, cost variance, and frequency for RTF assets versus others
By centralizing this data, TeroTAM transforms RTF from a cost-cutting shortcut into a disciplined, data-backed strategy.
Summing it up
Run-to-failure maintenance is not a sign of poor maintenance—it is a legitimate engineering decision when grounded in failure physics, asset criticality, and economic analysis. In modern industrial facilities, where maintenance budgets must be optimized without compromising safety or output, RTF plays a vital role in eliminating wasteful tasks and focusing effort where it matters most.
However, its success depends on rigorous asset classification, continuous monitoring, and a willingness to adjust strategies as conditions change. With a platform like TeroTAM, maintenance leaders can implement RTF deliberately, track its performance objectively, and ensure it remains a tool for efficiency—not a source of avoidable risk.
For maintenance managers, supervisors, and reliability engineers seeking to refine their maintenance mix, understanding and applying RTF correctly can unlock meaningful savings while preserving system integrity. To explore how TeroTAM can support a smarter, segmented maintenance strategy—including controlled run-to-failure—contact us at contact@terotam.com.
