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Bridging the gap between design specification and manufacturing reality
In tire design, there's a fundamental gap between two critical stages:
Designers work with flat, unvulcanized components (extruded profiles and calendered sheets) in the spec matrix.
The mould section shows vulcanized components pushed against curved surfaces, chemically transformed and geometrically deformed.
For decades, translating between these representations relied entirely on designer experience.
Manual trial and error to find the right flat profile for the desired vulcanized geometry
Critical expertise locked in senior designers' experience
Different designers may interpret specifications differently
Our artificial intelligence learns from vast datasets of tire designs, understanding the complex relationships between flat and vulcanized components.
Instantly converts between specification-stage and manufacturing-stage geometries
Decades of engineering knowledge encoded in intelligent algorithms
Reliable, repeatable predictions every time
Real tires with known geometries
Geometric die from section design
Learning geometric-to-physical mapping
Actual production die specification
Comparison & Optimization
Predicts real dies from geometric designs
We're developing AI that goes beyond geometric translation
Designers work with dies and geometric profiles - abstract representations that approximate component behavior
AI automatically identifies the actual extruded profiles and calendered sheets from the spec matrix that match your design intent
Map geometric dies to production component specs
Intelligent component recommendations
From vulcanized to unvulcanized specs
Capture expert knowledge in algorithms
Moonar's AI eliminates critical bottlenecks where designer experience has traditionally been irreplaceable
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