3M
AI Solution engine
Getting to the heart of the problem with 3M adhesives
My starting line
3M adhesives are tough - tough enough to hold airplanes together. This is the message 3M was shouting, but the question remained:
“Why aren’t more manufacturers using adhesives in place of nuts and bolts”
— 3M
My goal
Understand why manufacturers lack confidence in structural adhesives and create a user-centered solution.
My team
1 Lead designer (me)
5 Support designer
5 Project manager
My role
Lead designer and researcher
Responsible for research, synthesis, concept creation, service design, IxD
My process
1
Stakeholder alignment
I facilitated a full-day workshop with 8 3M stakeholders to align on the the project goal and prioritize areas of the customer journey for our research to target.
2
User research
I led contextual observations in 3 US cities, with 4 different companies, and 20 participants.
3
Target the problem
I extracted and coded over 800 data points from the interview transcripts, and synthesized them into insights which spotlighted the core problem.
4
Converge on a solution
I delivered a future workflow and detailed wireframes for a machine learning platform.
My Research findings
So why weren’t more manufacturers using adhesives in place of nuts and bolts?
Structural adhesives are tough and 3M thought it was about convincing manufacturers of that.
I found it wasn’t the final holding power that was the issue. It was the overwhelming complexities which lead to excessive failure points in the design and assembly process that kept customers at bay!
Congnitive load was to blame 25% percent of the time.
My recommendation
Leverage AI to reduce cognitive load
Use AI models to manage the intrinsic cognitive load caused by the innate properties of materials such as chemistry and environment, and minimize the extraneous cognitive load caused by 3M such as inconsistent language and knowledge silos.
My persona
Meet Joshua, material scientist and engineer
Joshua needs intelligent feedback in order to make educated design decisions for attaching next generation materials in his 2020 vehicle design.
If only he had a tool which helped him manage all the complexities introduced by adhesives and recommend viable solutions, it would increase his likelihood of using adhesives instead of traditional fasteners.
My solution
The 3M Solution Engine
The 3M Solution Engine is a machine learning platform that reduces cognitive load by delivering expert solutions (a) so Joshua can have more confidence in adhesives.
Joshua experiences a guided step-by-step guide (b) to solving his engineering problems. He can input information specific to:
Substrate materials
Joint stress requirements
Environmental conditions
Manufacturing process
And more…
It’s educational and informative at every step, and it allows Joshua to input as much or as little info as he desires.
The solution engine learns with every new engineering problem.
Joshua receives recommended solutions with confident ratings.
Solutions populate in real time as he enters new data, and they are ranked according to confidence based on the system’s machine-learning algorithms.
Each solution includes:
A confidence rating (a)
Pros and cons (b)
Option for viewing details (c)
A simple way to request samples (d)
The Solution Library helps Joshua organize his projects.
He can keep track of all his samples, recording which ones worked or failed during his testing. He can collaborate more easily with his colleagues and share the knowledge he learns. Nothing falls through the cracks and huge amount of data now seems manageable thanks to the Solution Library.
My impact
3M was missing out on an opportunity to put valuable data to use and help alleviate customer pains by offering tools and frameworks to facilitate the design and engineering process.
Today 3M’s executive team is aligned on the correct problem and the AI solution.