By Paul Salmon FCILT, FSCM
Introduction: The Hidden Weakness in Defence Logistics
In Defence supply chains, spares forecasting has always been a high-stakes challenge. Every component moved through the system carries a cost in procurement, storage, transport, and maintenance. Demand forecasting seeks to strike a balance between availability and affordability, ensuring that equipment is ready when needed without burdening the system with excess stock.
But what if a significant proportion of that demand isn’t real at all?
Enter the persistent problem of No Fault Found (NFF). Across aviation, naval, land and medical platforms, items are frequently removed at the front line as “faulty,” only to be tested later and found to be fully serviceable. These NFF returns create false demand signals that inflate consumption, distort data, drive unnecessary procurement, and slow the repair pipeline.
The solution may be deceptively simple: insert a dedicated NFF bench into the supply chain to triage and filter these items before they flood deeper into the system. It is a concept with precedents in civil aviation and automotive sectors — and one that Defence could embrace to save cost, sharpen forecasting, and improve availability.
The Cost of No Fault Found in Defence
No Fault Found is not a minor nuisance; it is a systemic issue. Studies in aviation and defence have shown that 20–30% of electronic line-replaceable units (LRUs) returned from aircraft are recorded as NFF. In some fleets, the percentage is even higher for certain avionics modules.
Why does it happen?
Limited frontline diagnostics: In the field, technicians have minimal time and limited tools. If an item appears suspect, it is swapped out to restore availability quickly. Intermittent faults: Some problems only appear under certain stresses (heat, vibration, humidity). By the time the unit reaches the repair facility, the fault has disappeared. Environmental stressors: Harsh operating conditions can create false positives — a system glitch mistaken for component failure. Human caution: No technician wants to risk leaving a genuine fault in place. Erring on the side of caution leads to more removals than strictly necessary.
The consequences cascade:
False demand: Perfectly good spares are removed, leading to inflated usage rates. Repair congestion: Items enter the maintenance pipeline unnecessarily, creating bottlenecks. Procurement waste: Replacement parts are ordered, draining budgets. Forecasting distortion: Data on failure rates is skewed, leading planners to believe components are less reliable than they are.
In an age where every pound in Defence must be justified, NFF represents a hidden but significant cost.
Distorted Demand Signals
One of the most damaging effects of NFF is the way it corrupts the demand signal. Forecasting models are built on historical usage data: how often items fail, how many are consumed per year, how long repairs take. When 20–30% of that demand is false, models inevitably over-predict future needs.
This is a vicious cycle:
False removals inflate historical demand data. Forecasting tools interpret this as higher expected failure rates. Stock levels are set too high. More procurement is authorised. Budget is wasted, storage is filled, and more items eventually expire unused.
At the same time, unnecessary removals slow the return of genuinely faulty items through the repair chain. Operational availability suffers, costs rise, and trust in the forecasting system is undermined.
Case Study: RAF Avionics and the NFF Challenge
The Royal Air Force has long grappled with NFF in avionics. Complex systems like radar modules, mission computers, and electronic warfare equipment are prone to intermittent behaviour under operational stress. Frontline technicians, under pressure to keep aircraft mission-ready, often remove suspect LRUs rather than risk recurrence in flight.
Yet when those LRUs reached the repair depots, large numbers tested within specification. This created a drag on the supply chain: valuable workshop capacity was tied up verifying healthy items, while false demand distorted planning.
In response, some RAF units experimented with dedicated NFF benches equipped with advanced diagnostics to stress-test avionics in conditions closer to operational reality. These benches filtered out false returns more quickly, returning serviceable items to stock within days instead of months. The result: leaner pipelines, reduced procurement demand, and improved confidence in availability data.
Lessons from Civil Aviation
Commercial airlines face the same challenge. Avionics “black boxes” are notoriously prone to NFF removals. The financial consequences for airlines — unnecessary component swaps, inflated repair contracts, and distorted reliability metrics — were severe.
The industry responded by introducing centralised NFF diagnostic benches as a standard part of the supply chain. Before items enter expensive repair or procurement cycles, they are screened with advanced diagnostic tools, sometimes replicating environmental stresses that frontline checks cannot simulate.
The results speak for themselves:
Faster turnaround: Serviceable items returned to the line quickly. Reduced costs: Fewer unnecessary repairs and purchases. Improved reliability data: Better distinction between genuine failures and false alarms.
For Defence, adopting similar practices could yield comparable savings — with the added bonus of reducing the operational footprint in contested logistics environments.
Automotive Diagnostics: Another Parallel
The automotive sector provides another useful analogy. Modern vehicles are packed with electronics, and “phantom faults” are common. Drivers may see warning lights triggered by sensor glitches, leading to unnecessary part replacements if handled simplistically.
Automotive supply chains counter this with dedicated diagnostic benches in dealerships and service centres. Suspect components are tested under simulated driving conditions, with software interrogation to distinguish genuine from false faults. This practice keeps costs down, prevents waste, and builds customer trust.
Defence can take note: investing in diagnostic capacity at the right point in the chain prevents false demand from propagating through the system.
The Value of an NFF Bench in Defence
A dedicated NFF bench functions as a filter in the supply chain, intercepting suspect components before they flood deeper pipelines. Its benefits are manifold:
Reduced false demand: Serviceable items are quickly identified and returned to stock. Faster turnaround: Items can be cleared in days rather than months in repair queues. Lower procurement costs: Defence avoids buying replacements for items that never truly failed. Improved data quality: Forecasting models reflect true failure rates, not distorted signals. Reliability insights: Patterns of NFF can inform design improvements or diagnostic tool upgrades.
The wider systemic gains are equally important: higher platform availability, smaller logistics footprints, and greater confidence in forecasting accuracy.
Challenges and Considerations
Of course, an NFF bench is not a silver bullet. There are real considerations to address:
Upfront investment: Diagnostic benches require advanced equipment and skilled technicians. Throughput balance: If poorly designed, the NFF bench could itself become a bottleneck. Intermittent fault capture: Not all faults will reveal themselves even under stress testing — some NFF rates will persist. Cultural trust: Operators must trust that an item declared “serviceable” after NFF inspection is genuinely safe to reinstall.
But these challenges are manageable. Civil aviation and automotive sectors have proven that the cost of investment is outweighed by the savings and reliability gains.
Towards Digital NFF
The future may take the concept further. Emerging technologies offer new possibilities:
AI-driven diagnostics: Machine learning can spot patterns across thousands of NFF cases, predicting which removals are likely to be false. Digital twins: Virtual models of components can replicate stresses, revealing hidden failure modes. Condition-based maintenance: Combining real-time sensor data with NFF analysis could eliminate many false removals at source.
In this vision, the NFF bench becomes not just a triage point, but a hub of diagnostic intelligence feeding back into design, training, and forecasting systems.
Conclusion: Filtering the Signal
Defence supply chains face enormous pressure: contested logistics, fragile global supply bases, and shrinking budgets. In this environment, every wasted removal and every false demand signal is a luxury Defence cannot afford.
A dedicated No Fault Found bench offers a practical, proven way to cut through the noise. By filtering the signal — separating true demand from false — Defence can reduce costs, increase availability, and improve the accuracy of its forecasting models.
The RAF’s avionics experience, civil aviation’s standard practices, and automotive’s diagnostic culture all point to the same conclusion: the benefits are real, the savings are tangible, and the resilience gains are significant.
The question is not whether Defence can afford to add NFF benches. The question is whether, in an era of contested supply chains, Defence can afford not to.
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