NTSB CAROL · Event
Event BFO93IA070
Registry · N867US
FAA Aircraft Registry record.
Make / Model
DJI MAVIC 2 PRO
ADS-B equipped
Yes — Mode-S ABEAAB
Registrant of record
SAMARITANS PURSE
Source: FAA Aircraft Registry (releasable master file).
Aircraft involved
Probable cause & findings
THE IMPROPER INSTALLATION OF THE SPACERS BY THE MECHANIC AND THE UNCLEAR INFORMATION SUPPLIED FROM THE MANUFACTURER AND OPERATOR REGARDING THE INSTALLATION OF THE SPACERS.
Factual narrative
SHORTLY AFTER TOUCHDOWN AT MEMPHIS, TN, A SEVERE VIBRATION WAS FELT BY THE FLIGHTCREW IN THE COCKPIT. THE FLIGHTCREW THOUGHT THE VIBRATION WAS GENERATED BY THE RIGHT MAIN GEAR SO THEY HAD MAINTENANCE PERSONNEL CHECK THE RIGHT MAIN GEAR. NO ANOMALIES WERE NOTED. THE FLIGHT CONTINUED TO PITTSBURGH, PA, AND SHORTLY AFTER TOUCHDOWN, THE LEFT MAIN GEAR COLLAPSED. POST INCIDENT EXAMINATION OF THE LEFT MAIN GEAR REVEALED THAT TWO SPACERS IN THE TORQUE LINK ASSEMBLY WERE FOUND TO HAVE BEEN IMPROPERLY INSTALLED. THE INVESTIGATION ALSO REVEALED THAT DURING RE INSTALLATION OF THE TORQUE LINKS AND SHIMMY DAMPER AT THE LAST MAINTENANCE CHECK, THE TWO SPACERS WERE INSTALLED IN REVERSE OF THEIR NORMAL POSITIONS. ACCORDING TO FOKKER, REVERSAL OF THE TWO SPACERS WOULD RESULT IN AN UNDAMPED FREE PLAY BETWEEN THE UPPER AND LOWER TORQUE LINK RESULTING IN OSCILLATIONS IN THE LATERAL MODE OF THE LANDING GEAR. REVIEW OF USAIR'S AIRCRAFT MAINTENANCE MANUAL, SUPPLIED BY FOKKER, REVEALED THAT THE TWO SPACERS THAT WERE INCORRECTLY INSTALLED ON THE INCIDENT AIRPLANE WERE NOT DESCRIBED BY DIMENSIONS OR VERBIAGE. Source: NTSB Aviation Accident Database (Pre-2008 Archive) Retrieved: 2026-02-12
Verbatim from NTSB's published report. Source file
NTSB_1993_BFO93IA070.txt.
Findings + structured fields enriched from FAA avall.mdb.
Full investigation docket on
data.ntsb.gov ↗.
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Related research
What the literature says.
Academic papers and agency reports matching this event's aircraft type or causal vocabulary (stall, maintenance). Sourced from NASA NTRS, NTSB Safety Studies, FAA CAMI, AOPA Air Safety Institute, Embry-Riddle Scholarly Commons, arXiv, and the Semantic Scholar academic graph.
- Embry-Riddle Scholarly Commons 2023 · Conference paper
The Value of Strong Partnerships to Build a Successful Aviation Maintenance Career Pathway Program for Transitioning Military Service Members
The aerospace industry is competing with other industries for a qualified workforce, and many of those competing industries are investing heavily in creating workforce development pipelines.
- Embry-Riddle Scholarly Commons 2026 · Journal article (IJAAA)
From Reactive to Predictive: A hybrid Trust-Mediated Adoption Framework for Data-Driven Maintenance in Distributed-Authority Aviation Environments
Modern aviation maintenance operates within increasingly data-intensive technological environments, yet the operational integration of predictive maintenance into routine decision-making remains incon…
- NASA NTRS 2026 · Conference Paper
Computational Analysis of Steady State Aerodynamics of Transonic Truss-Braced Wing Configuration in Deep Stall
This study presents a computational investigation of steady state aerodynamics of the Subsonic Ultra-Green Aircraft Research (SUGAR) Transonic Truss-Braced Wing (TTBW) configuration over a wide range …
- Semantic Scholar 2025 · Article (Applied Sciences)
Decision-Making Framework for Aviation Safety in Predictive Maintenance Strategies
The implementation of predictive maintenance (PM) in aviation presents unique challenges due to strict safety requirements, complex operational environments, and regulatory constraints.
- Embry-Riddle Scholarly Commons 2024 · Journal article (JAAER)
Low-Resource Automatic Speech Recognition Domain Adaptation – A Case-Study in Aviation Maintenance
With timeliness and efficiency being critical in the aviation maintenance industry, the need has been growing for smart technological solutions that optimize and streamline the different underlying ta…
- Embry-Riddle Scholarly Commons 2024 · Journal article (JAAER)
A New Trajectory in UAV Safety: Leveraging Reinforcement Learning for Distance Maintenance Under Wind Variations
In the field of aviation, safety is a critical cornerstone, and the operation of Unmanned Aerial Vehicle (UAV) systems is deeply connected with this principle.
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