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As I’ve previously written, armament testing can be very complex and difficult given all the different parameters and configurations. Today, the Air Force still employs Vietnam-era munitions off Vietnam-era aircraft, as well as modern munitions off of 5th generation aircraft. <Read More>Since electronics can fail after an initial use or after 10,000 uses, this adds an additional level of difficulty for managers who wish to better predict when faults will occur for each system. This results in armament technicians responding or reacting to failures which occur during flight vs. finding signs of systems degradation during scheduled maintenance cycles.

While many aircraft systems, such as engines, can be evaluated by advanced AI systems scouring years of maintenance data records to determine failures at a high level of certainty, the armament system is unique. As I discussed in my previous blog post, Future Solutions or Future Problems; Don’t Let the Solution Create Complications, because the armament system is highly configurable to meet mission needs, this makes the weapons stations quite complex, including many different types of signals, some of which are unique to a specific munition.

Another challenge when trying to properly analyze an armament system’s health is how to troubleshoot and fix a failure. When a failure occurs during a mission that was using munitions, three different maintenance sections are enacted to diagnose the problem. Normally, the first step is for the flightline armament technicians to isolate the munition from the aircraft station and hand it off to the munition’s technicians for further evaluation. Next, the flightline technician will most likely test the aircraft and if a failure is found, the rack or launcher is further isolated and sent to an armament back shop for additional testing. If the aircraft passes, then the fault is determined to be found and entered in the maintenance records as fixed.

All the while, the munitions and armament technicians are also testing the equipment which was returned to them. If additional faults are found, even if they had nothing to do with that mission, they are identified and fixed. Sometimes, these maintenance records are linked through the repair chain, but more often than not, the munitions repair records are de-linked from the aircraft records.

When analysis of this repair process is accomplished using maintenance records, the AI might capture all repairs noted as a root cause of the mission failure. As previously highlighted, some of these might have been faults which had nothing to do with the mission. Worse yet, if a clear path of corrective action doesn’t exist, the system isolation for troubleshooting might miss the actual root causes for the failure.

Predictive maintenance has been making major strides over the past decade within the DOD, working toward a clear site map for maintainers and mission planners. Unfortunately, not every system fits into a clean model, and some, like the armament system will still require the use of external test sets to gain clarity.  One could develop an equation to change parts within an open system like armament and possibly reduce many failures, but this will come with negative effect on the budget. Changing electrical components without knowing their current status is like shooting a bow and arrow blindfolded in a hurricane while standing on a moving vehicle.