Who we are
TwinTech Materials is tackling the "garbage in, garbage out" problem in manufacturing simulation, starting with the casting industry. The reliability of simulation tools is contingent on the accuracy of the input data provided by the end user.
Today, foundries lack a reliable way to determine the thermophysical properties of materials required for accurate simulation, leading to a critical disconnect between digital predictions and real-world results on the manufacturing floor. These discrepancies result in costly scrapped parts and time-consuming repairs.
TwinTech combines a physical test kit that collects real-world data from each foundry's unique process with AI-powered software that translates this data into precise material property inputs for simulation software. Our technology enables foundries worldwide to achieve near-perfect digital twin simulations, reliably predicting and preventing defects before they lead to costly repairs and scrap.
Leadership
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Cayman Cushing
FOUNDER
Expertise at the intersection of casting science, simulation, and machine learning.