Two questions we often hear these days are:
(1) Do you make sensors?
(2) Are you an AI company? Do you use AI?
SMART Tire vs "Smart" Sensors
The first one is easy: no, we don't make tire sensors, we eliminate the issues being sensed.
Modern vehicles contain 50-100 sensors on average, including the tires. So what are they sensing? In the tires, primarily air pressure and temperature. SMART Tires contain no pressurized air, and they retain less heat. Pressurized air transfers heat faster, which increases pressure, which transfers heat... you get the idea. Anyone who has seen their tire pressure increase 5-10 PSI or more during a drive knows what I'm talking about.
Does this mean we don't use sensors at all? Not exactly. It's still important to know if a tire is overheating, the tread is worn, the camber is off, and a few other things too. We just happen to think prevention > detection when it comes to the tires keeping you safe on the road.
Are you AI / Do you use AI?
No, we're not an AI company. If you're interested in adding AI to your portfolio, we understand. OpenAI recently raised at a $157B valuation. For perspective, there are only about 10 companies in the world worth $1T, and not all of them are investable. So, whether you are bullish or bearish on AI, let's just say it is already priced accordingly. It would be literally impossible to return 100x on that investment, unless you project the company to be worth more than Apple, Microsoft, Amazon, Facebook, Tesla combined...
What we are is a technology company. I say "technology" versus "manufacturing" or "industrial" or "hardware", because our job is to leverage all the best of modern technology as we build out SMART Tire. For example, our prototyping and manufacturing incorporate some of the best aspects of Industry 3.0 + 4.0, namely 3D printing, software simulation, and intelligent production processes.
Some of our best practices include:
(1) In-house 3D printers used to create molds, fixtures and parts for fast prototyping
(2) Finite element analysis and simulation (in partnership with Dassault Systèmes as part of their 3DExperience startup program)
(3) Custom in-house software for designing and selecting tire build configurations
(4) Custom equipment and trade secret methods of assembly
And yes... a little bit of AI. While AI trickles down into many of the tools we already use, on example of how AI impacts SMART Tire is through the development of (more) advanced materials.
Material Advancements with AI
Artificial intelligence (AI) is being used to significantly advance the development and optimization of shape memory alloys (SMAs) by enabling researchers to predict and design new SMA compositions with superior properties, automate the characterization process, and refine manufacturing techniques, leading to more efficient and tailored applications across various industries like aerospace, medical devices, robotics, and tires.
Key ways AI is impacting shape memory alloys:
Material discovery:
- AI algorithms can analyze vast datasets of material properties to identify promising combinations of elements for creating new SMAs with desired characteristics like improved shape recovery, actuation force, and temperature response, potentially leading to the discovery of novel alloys not previously considered.
Predictive modeling:
- Machine learning models can predict the behavior of SMAs based on their composition and processing parameters, allowing researchers to optimize manufacturing processes and minimize trial-and-error experimentation.
Automated characterization:
- AI-powered image analysis and computer vision can be used to automatically measure the deformation and shape recovery of SMAs during testing, leading to faster and more accurate data collection.
Microstructure analysis:
- Advanced AI techniques can analyze the microstructure of SMAs to identify critical factors influencing their properties, facilitating further material refinement.
Design optimization:
- AI can be used to design complex SMA structures with specific functionalities by simulating their behavior under different loading conditions and temperature variations.
Examples of AI applications in shape memory alloys:
New SMA discovery:
- Researchers at Texas A&M University used an AI-based materials selection framework to identify a novel nickel-titanium alloy with superior shape memory performance compared to existing options.
AI-guided manufacturing:
- Companies utilizing AI to optimize the production of SMA wire, sheets, and foils, improving consistency and reducing manufacturing time while achieving desired mechanical properties.
Predicting SMA behavior:
- Machine learning models are being developed to predict the actuation response of SMAs under different temperature and stress conditions, allowing for better design and application.
Potential benefits of using AI with shape memory alloys:
Faster development cycle:
- AI can significantly accelerate the process of identifying and developing new SMA materials with tailored properties.
Cost reduction:
- By optimizing manufacturing processes and minimizing experimental trials, AI can lead to more cost-effective SMA production.
Enhanced performance:
AI-guided design can result in SMAs with improved functionality and wider application possibilities.
