What other domains shared similarities with personnel parachutes?
Researching an Ambiguous Problem Space: T-11 Parachute Packing
The Aerial Delivery & Field Services Department (ADFSD) faced a pressing need to improve the T-11 personnel parachute packing process due to manpower shortages. Although automation seemed like a clear solution, we needed to explore whether it was the most effective approach. The challenge was to thoroughly understand the domain, uncover the root problems, and identify areas for improvement—without compromising the safety and expertise of the riggers.
As a UX researcher, I:
- Led in-depth ethnographic studies and contextual inquiries at Fort Gregg-Adams, observing and interviewing parachute packers and inspectors.
- Conducted and analyzed semi-structured interviews with 25+ riggers and inspectors to understand their needs, pain points, and workflows.
- Synthesized research findings using affinity diagramming to identify key insights and reframe the problem.
- Collaborated with the team to define a research plan, prioritize assumptions, and guide design solutions based on user feedback.
Capstone Group of 3 + myself
8 months
(2023-2024)
The research uncovered four key insights that reframed our understanding of the problem:
- The rigger-inspector ratio caused bottlenecks that slowed the workflow.
- The rigidity of the workspace contributed to physical strain and injuries among riggers.
- The repetitive, monotonous nature of the packing process led to disengagement and errors.
- Small inefficiencies, like outdated record-keeping, wasted time and manpower.
This deeper understanding led us to shift our focus from full automation to augmenting the riggers’ capabilities, ultimately providing the foundation for future design solutions.
Context
To design an effective solution, we first immersed ourselves in the complex, high-stakes environment of military personnel parachute packing
The T-11 personnel parachute is a crucial piece of equipment for the US Military, used in low altitude static line drops. The Aerial Delivery & Field Services Department (ADFSD) at Fort Gregg-Adams is responsible for ensuring that these parachutes are inspected, packed, and ready for deployment at a moment's notice.
The packing process, however, is manual, repetitive, and physically demanding, requiring meticulous attention to detail at every step. A single error could have catastrophic consequences, which is why safety protocols are strictly enforced, with riggers relying heavily on inspections.
Riggers, part of the 92R MOS (Military Occupational Specialty), undergo 14 weeks of training in airborne operations and parachute rigging. They spend their days folding, checking, and packing parachutes in a high-pressure environment.
Riggers thus live by the motto,
" I will be sure, always! „
A message so ingrained in ADFSD that it can be found everywhere in their facility, including painted on this C-130 training hull
The current system, while effective in ensuring safety, is outdated and presents several challenges—riggers often suffer from physical strain due to non-ergonomic tools, experience bottlenecks waiting for inspectors, and endure repetitive tasks that lead to disengagement.
ADFSD was considering automation as a solution to increase efficiency. However, before jumping into automation, our team needed to understand the core issues that riggers faced and determine whether automating the process was the right approach—or if augmenting the rigger's abilities would yield better results.
We embedded ourselves in this high-stakes environment, engaging with 25 riggers and inspectors to uncover pain points and identify opportunities for improvement, just a small subset of over
2000
Parachute Riggers
who support an average of
250000
Jumps Annually
Dual row static line jump from a USAF C-17 Globemaster
Research Approach
Recognizing the unfamiliarity of the parachute packing domain, we adopted a mixed-methods qualitative approach.
Analogous domain research
And what can we learn from them that can be applied to our domain? Take mask manufacturers, whose demand dramatically rose during the covid-19 pandemic. They accelerated quality checks by applying automated inspection algorithms to a machine vision system to detect surface or material defects. Could the ADFSD implement something similar on a larger scale to reduce inspection time and increase accuracy?
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Automatic optical system + anomaly detection model used to inspect and identify flaws in FFP2 masks.
(https://www.data-spree.com/blog/reliable-automation-of-ffp2-mask-production-with-ai-quality-inspection)
Contextual inquiry
We embedded ourselves within the dynamic pack floor environment at Fort Gregg-Adams, VA, observing riggers and inspectors in action.
Learning the realities of parachute packing from 92R Riggers.
Ethnography
It was difficult to imagine handling the massive 155 square-meter (1670 sf) canopy 17 kg (38 lbs) without one to fold and finesse. The ADFSD obliged our request and sent over a T-11 for us to practice with. Learning to fold this massive mess of fabric and lines helped me empathize with the parachute riggers, especially as I repeated the process over and over.
Practicing methods of folding a T-11 parachute on an impromptu rigger table.
Synthesizing insights from findings
Grouping findings via affinity diagramming.
Journey map categorizing various physical rigger stressors during the pack process.
Insights
Identifying the true problems in the parachute packing paradigm
We synthesized the following insights:
01
The rigger-inspector ratio creates a major bottleneck.
We observed frequent, lengthy waits for inspector checks, interrupting workflow. The rigger is often ready to move to the next step, but has to wait for inspector approval at least 8 times during each parachute pack. Riggers express frustration about losing momentum, feeling slowed down by the system. This dependence on inspectors, while crucially redundant for safety, limits overall efficiency.
Not relying completely on inspectors to move to the next step can increase efficiency.
02
The rigidity of the current packing system takes a toll on rigger physical health.
The rigid, one-size-fits-all approach to the packing process puts unnecessary strain on the riggers. Tables are fixed, tools are awkward, and the repetitive motions take a toll. Injuries like carpal tunnel and rotator cuff tears are a direct result of this mismatch between rigger needs and the workspace. Injuries result in a significant number of lost workdays per year, directly through absence and indirectly through reduced throughput performance.
Shifting towards a more adaptable process ensures a healthier and more productive work environment.
03
Rigger morale is undermined by monotony.
We asked many riggers what they were thinking about at various parts of the process, only to find the most common answer is “nothing.” Incidentally, the highest number of errors occur when the brain is not engaged in the task at hand, instead relying on imprecise motor memory.
In contrast with the creative aspects of aerial delivery, parachute packing currently offers limited variability in tasks and few opportunities for true collaboration.
Addressing the monotonous nature of parachute packing can increase rigger engagement and satisfaction.
04
Small inefficiencies waste manpower and time.
Observing pack floors in process, we found many suboptimal tasks that add up throughout the day. For instance, each rigger check involves 45+ seconds of waiting. When each parachute involves 8+ rigger checks, this adds up to over 90 minutes daily.
Riggers also complain about clunky record-keeping with the archaic DA-3912, and problematic tools that hamper the workflow.
Targeted optimization of the parachute packing process can free up manpower and improve efficiency.
Reframing
Is the T-11 parachute the true barrier to automation?
Our project began with a focus on optimizing the current T-11 parachute packing process. Our initial approach aimed to streamline operations through better workflow design, improved ergonomics, and potentially even automation assistance. As we explored the process through interviews and observations, and identified opportunities through analogous domain research, expert interviews, and data analysis, we synthesized a series of insights. Each insight reflects an area of opportunity, but collectively, they paint a clear picture: we’ve been focusing on optimizing a system that has inherent limitations. Addressing ergonomics, morale, and inefficiencies can provide temporary relief, but they won’t solve the core issue.
The true roadblock to achieving ADFSD's goals of efficiency, manpower optimization, and a future-proof packing solution lies not within the process itself, but within the T-11 parachute design, leading us to...
Insight 5:
05
The T-11 Parachute design inhibits true automation.
What we observed
The T-11’s canopy, deployment bag, drogue chute, and pack tray have complex folds that require dextrous human hands...
The T-11’s use of nylon and other pliable fabrics is well suited for human folding, but poses challenges for automated systems that need a greater degree of rigidity or structure for machine handling.
What we took from analogous domains
Automotive airbags are packed by robotic panels, and their folds are designed with that panel compatibility in mind.
Automated sleeping bag and large fabric packing utilizes rollers to facilitate machine folding and insertion into carrying cases. These techniques are difficult to translate to the complex line groups of the oddly-shaped T-11.
Experts validated our insight
We consulted robotics experts Howie Choset and Chris Harrison with our unique domain and proposed path forward. Choset highlighted the fundamental mismatch between smooth, nonlinear objects and the existing robotic grippers. Harrison emphasized that process improvements effectively puts a band aid on the larger problem, as the T-11 is a product of a time when human labor was the default
Impact & Reflection
Augmenting human expertise, not replacing it
We synthesized several critical insights that fundamentally changed our understanding of the problem. Instead of simply optimizing for speed or reducing manual labor through automtion, we discovered that the real opportunities lay in augmenting the riggers' capabilities and improving their work environment.
Our findings revealed inefficiencies related to the rigger-inspector workflow, physical strain caused by non-ergonomic tools, and low morale stemming from repetitive, monotonous tasks. These insights paved the way for more human-centered solutions that could address these issues without compromising safety. By reframing the problem from an automation-first approach to one that focuses on augmenting riggers’ expertise, we laid the groundwork for a more sustainable, scalable improvement plan.