Discovery
Research into the Problem Space
We started with background research, but parachute packing is very complicated and involves many variables, from the users, to interpersonal interactions and culture, to the packing environment itself. Reading about the packing process and users was not enough. We needed to go to the site and observe firsthand how parachute packers did their jobs. We performed a contextual inquiry at Fort Gregg-Adams, which helped us empathize with our users and reveal key pain points. Based on our findings, we could create insights and actionable areas of opportunity to guide our designs.
Insight 01
&
Insight 02
Riggers
Their job is to pack 15 parachutes a day. There are 4 riggers per 1 inspector. They often have to wait around for inspectors to perform a review.
Inspectors
They are experienced packers that patrol pack floors and inspect rigger packs during rigger checks. They have many inspections to perform.
On average, every day there are
performed by an inspector
Statistics calculated based on data from Fort Gregg Adams
The process has many small steps and rigger checks
Injury is inevitable
Riggers reported that injury was not an "if", but a "when". Carpal tunnel, back, shoulder and neck strain, or more serious problems came with the job. Everyone had a health-related story to tell.
Individuals face different physical impacts
Riggers come in different shapes and sizes, but the tables they pack on and the process itself remains the same. Tall riggers have to hunch over the packing tables, while short riggers have to strain themselves to reach across the tables.
Packing culture is important
Riggers would "trash talk" and compete with one another to make time pass faster and bond. They would also play music to break up monotony and energize each other. Collaboration was not allowed, however.
Riggers can't quantify the important work they are doing
They pack 15 parachutes a day, every day, which adds up over time. But only daily packs are tracked, so their long term progress is lost.
Synthesis
Finding areas of opportunity
Now that we have identified insights, we can turn them into areas of opportunity. We also wanted to balance our client's needs of a scalable system that can be automated in the future. We created guiding principles that combined user needs with client goals.
Streamlining the inspection process will increase rigger efficiency
A shift towards a more adaptable process can foster a healthier work environment and boost productivity
We can increase rigger engagement and satisfaction by addressing the monotonous nature of parachute packing
By optimizing parts of the parachute packing process, we can free up manpower and improve efficiency
Our guiding principles
Eliminating bottlenecks & improving efficiency
Adapting the process to the individual rigger to improve health
Fostering healthy competition & improving morale
Establishing data collection to optimize packing techniques & create a feedback loop
Final Solution
Smart Table & Hub System
We have designed multiple solutions that work together as a system to streamline the packing process, collect packing data, and improve ergonomics and morale. At the center of our system is the packing table, where riggers pack parachutes.
3D renders were created in Blender by me
The brain
Feature
We designed a dashboard that can be used by both riggers and inspectors. It is linked to 4 pack tables, the rigger simply chooses which table they prefer. Inspectors can watch the hub to identify incoming rigger checks more clearly.
Feature
Riggers can check their metrics, such as average time per pack, or total lifetime packs, whenever they prefer. They can also compare each other's stats, fostering healthy competition.
Key Improvements
Data Collection
Rigger data, such as pack time or total packs, can be collected. Displaying these stats helps quantify data in ways that are tangible and digestible to riggers
Alleviating Small Tasks
Tasks like filling out the small form on each parachute, or keeping track of tools throughout the day, are eliminated through the use of the hub
Competition & Morale
Healthy competition, banter, and camaraderie are important to riggers, so seeing one another's stats will help support this culture
The core
Feature
The Smart Table will communicate with the Hub and automatically adjust the height to the rigger's preset position, accommodating different rigger needs.
Feature
The rigger can call for an inspection by double-tapping a conductive strip underneath the table. The light will turn on and the Hub will display the rigger's order in line. This streamlines the rigger check process by making it easier to tell which rigger called for an inspection.
Key Improvements
Health & Safety
The table height will be adjusted for each rigger's preferred height to reduce strain. With less riggers harmed when working, more personnel are available to pack
Efficiency
By optimizing working conditions and reducing latency caused by rigger checks, packing efficiency will improve
Data Collection
Time between rigger checks can be tracked, as well as the inspector's performance
A closer look
The Design Process
When we started our research, we knew very little about parachute packing. ADFSD, the US Army, parachutes, parachute packing itself, and the many subdomains within these categories were all topics we had to research in-depth. Once we had more general knowledge on our problem space, we decided that analogous domain research would be helpful.
Traditional Fabric Folding
Large swathes of parachute fabric are folded, so we studied origami and sail making
Inventory Management
We studied Amazon warehouses and IKEA for how they manage large inventories
Compact Packing
The large parachute must be compacted into the small deployment bag. We researched airbags and deployable objects
Automated Fabric Folding
Automated manufacturing for tents and sleeping bags was researched
Next, we drove down to Fort Gregg-Adams to perform a contextual inquiry. This is a great way to empathize with the user you are designing for—by going into their environment and watching them in action. We used the AEIOU method, looking at Activities, Environment, Interactions, Objects, and the User. This process can involve asking questions, taking notes, and silently observing how the user does their task and how they interact with their environment.
We took all of our findings and sorted them into groups based on similarities. From there, we could find common patterns and extract insights.
Some key findings were that there was a high incentive for efficiency—riggers can go home once they successfully complete 15 parachute packs. As a result, balancing efficiency with quality, especially during times of high stress like "push weeks", was very hard.
Affinity mapping helped us extract insights. These took a few rounds of iteration before we solidified them. We had to summarize key findings, while also telling the client something they didn’t already know. In short, “...So What?”
From there, we could rework our insights into actionable questions that acted as a base for the ideation process.
While creating our insights, we also wanted to make a user journeymap. However, I thought it would be beneficial to map the pain points to each step of the packing process. Different physical stressors and injuries are accrued at different stages, so visualizing them all would help us target pain points better for solutioning.
Since we had principles to guide us, we could begin to think of potential solutions. We started with a modified version of “Crazy 8s” where we gave everyone 15 minutes per principle, and they could generate as many as they wanted. We generated 200 ideas, give or take a few.
After sorting them, four main categories developed: ergonomics & physical assistance, workflow automation & tooling, in-process monitoring & data collection, and organizational changes. Now, we could sort the ideas based on how much they satisfied insights and see which categories offered the biggest gains.
Left with 4 solution categories, we wanted to visualize them in a way that could start a dialogue with the client. We opted for a kind of "abridged storyboard"—basically, concept sketches with added backstory. If we were to show them highly-polished, refined solutions, they naturally would be less inclined to comment negatively. This low-stakes depiction of our ideas allows the client to share their honest thoughts. I created these sketches digitally:
We moved forward with the smart table and rigger dashboard
We made low-fidelity screens of a rigger dashboard that displays personal stats including performance stats, and daily/lifetime packs. There is also a team section that shows leaderboards for that floor or different forts. These stats would be embedded into the pack table so the rigger could view their stats in real-time.
We designed two testing protocols: one for testing the dashboard, and one for testing the overall flow of the new solution ecosystem. The dashboard user testing involved think-aloud protocol and semi-structured interviewing. We wanted to test if riggers understood how to navigate the dashboard, and their understanding and reaction to the displayed metrics. For testing the system flow, we instructed them broadly on how to use the new system, then observed their behavior as they packed with our prototype conductive strip, scanner, lights, and dashboard. After, we asked them questions about the process in a semi-structured interview.
The embedded dashboard would break
We constantly had to move our iPad, i.e the "embedded dashboard", out of the way while riggers worked to avoid damage. Riggers also gave feedback that anything fragile near the pack table would break.
The overall flow was streamlined
Riggers quickly understood the interactions in our new system and liked how quick and easy they were. The conductive strip and light signaling had especially positive feedback.
Constant display of statistics was stressful
Riggers reported the constant display of performance stats like average time was actually discouraging to them. Riggers may get tired throughout the day, so seeing such minute changes would be stressful.
We pulled in inspectors to get their perspective on the dashboard. This is where the idea for an inspector-facing hub was formed. Together, we ideated a centralized dashboard, situated near the pack tables, that helped both riggers and inspectors.
Leveraging computer vision
Computer vision could be used to determine errors made, or predict when a rigger check needs to be called. It can also collect data to better inform the packing process and create a positive feedback loop. It is the next step towards automation.
Automating parts of the packing process
Specific parts of the packing process could be automated to save time and improve rigger health. Introducing autonomy to one part of the packing process is a step towards the fully automated future ADFSD desires.
Redesigning the parachute
The current T-11 parachute design is the source behind all of the problems we identified, because it cannot feasibly be packed by machines. In order for the process to be fully automated in the future, the parachute needs to be redesigned.
Our Impact
Outcomes
Riggers, inspectors, and our clients at ADFSD had very positive reactions to our designs. User testing showed that both riggers and inspectors could understand our new solution ecosystem. Our clients plan on taking our prototypes to DEVCOM for testing and development. Our users were especially excited about the adjustable smart table, they felt it would truly help alleviate their health problems.
