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benefits of overcoming, reliability problems. During system acceptance testing in 1995, three Hunter
aircraft were lost within a 3 week period, contributing to a decision to terminate full rate production.
UAS ROADMAP 2005
APPENDIX H – RELIABILITY
Page H-8
Wanting to benefit as much as possible from its substantial investment in the Hunter, its Program
Management Office and the prime contractor (TRW) performed an end-to-end Failure Mode Effect and
Criticality Analysis (FMECA) and a Fishbone Analysis on each of the critical subsystems. An
interconnected network of failure analysis and corrective action boards was implemented with the
authority to direct design changes to Hunter. Failures of its servo actuators, the leading culprit for the
series of crashes, were identified, and their MTBF increased from 7800 hours to 57,300 hours, a
sevenfold improvement. Other key components received focused attention including the data link and
engine.
Hunter returned to flight status three months after its last crash. Over the next two years, the system’s
MTBF doubled from four to eight hours and today stands at over 21 hours. The aircraft itself achieved its
required MTBF of ten hours in 1998, and today that figure stands close to 26 hours. Prior to the 1995
stand down and failure analysis, Hunters were experiencing a mishap rate of 255 per 100,000 hours;
afterwards (1996-2005) the rate was 24 per 100,000 hours. Initially canceled because of its reliability
problems, Hunter has become the standard to which other UA are compared in reliability.
In addition to the reliability data shown in Table H-1, an in-house reliability assessment performed by the
prime contractor for the period of 1995 through 2005 found an availability of 0.991. The calculated
reliability per mission was 97 percent.
The failure modes analysis in Table H-2 is built on data from December 20, 1995 to June 15, 2005. This
data shows that Hunter’s non-weather related failures were led by power and propulsion issues (38
percent). This concentration is a shift from the more evenly distributed failure mode breakout shown
during a 2003 reliability assessment (2003 OSD UAV Reliability Study). This follows in the trend of the
Predator and Pioneer systems, which also suffer failures due primarily to power and propulsion. The 19
percent of failures attributed to “Miscellaneous” includes malfunctions with the flight termination system
and parachute aircraft recovery system.
The high mishap rate of the early Hunters is comparable to that of the early Pioneers and, based on that
similarity can be largely attributed to poor Israeli design practices for their UA in the 1980s. The
significant improvement in Hunter’s mishap rate achieved since the mid-1990s is reflective of (1) joint
government/contractor-focused oversight, (2) a rigorous review and analysis process being put in place,
and (3) qualitative improvements in a number of failure-critical components (servo-actuators, flight
control software).
TECHNOLOGY ENHANCING SOLUTIONS
To address the reliability shortcomings identified above, examples of current and developmental
technologies are presented in Table H-3. These technologies – provided in detail in the full Reliability
Study – are provided as examples of solutions which have the potential to significantly enhance UA
reliability. Technology areas for each of the major failure modes are presented at three levels of
cost/complexity.
TABLE H-3. TECHNOLOGY TO ENHANCE UA RELIABILITY.
Low Level COTS High Level COTS Next Generation
Power and
Propulsion
Lighter (Boralyn
Molded) Engine Block Heavy Fuel Engine Fuel Cell Technology
Flight Control Higher Frequency Flight
Control System
Advanced Digital
Avionics System
Self-Repairing
“Smart”Flight Control
System
Communications Better Environmental
Control
Electronically Steered
Arrays
Film and Spray-On
Antennas
Human/Ground Enhanced Pilot Training Auto Take-Off and
Recovery
Enhanced Synthetic
Vision
UAS ROADMAP 2005
APPENDIX H – RELIABILITY
Page H-9
RECOMMENDATIONS
Based on the preceding reliability data and trends analysis, it is possible to distill a focused set of
recommendations which will have a measurable impact on UA reliability growth.
Introduce joint standardization of reliability data tracking for operational UA systems.
Data collection for this study provided insight into an inconsistent (and at times inaccurate and
incomplete) reporting framework for tracking the reliability growth of various UA fleets. This makes
it particularly difficult to gauge not only the reliability of one system, but also any trends across
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