At Boston University’s College of Engineering, an autonomous research system combines automation and machine learning to accelerate the pace of creating the most efficient energy-absorbing shape.
At the Kent State University Experimental Archeology Lab, Dr. Metin Erin and Dr. Michelle Bebber rely on their universal testing system to analyze ancient technologies in the hopes of better understanding the material record of hominin history.
Providing a wide range of flame-retardant materials as well as special technical compounds, Vamp Tech develops tailor-made solutions to meet customers' specific needs, becoming a reliable partner in a variety of industries.
As a leader in the development and manufacture of medical devices, Primo Medical Group holds over 130 patents and has produced thousands of products. Adaptability and security in their testing process is critically important to their goal of shipping the highest quality products possible.
LOLIWARE is working on developing a bio-renewable, biodegradable plastic derived from seaweed that they hope will reduce the impact of single-use plastic products that get discarded every day. As a start-up, being able to move quickly is critical – so they brought their testing in-house with the acquisition of a 3400 Series Universal Testing System.
Through the use of machine learning, Siemens Digital Industries have incorporated the ability to predict fatigue behaviour for 3D printed components in their Simcenter 3D Specialist Durability software. With test data provided by ElectroPuls users at KU Leuven, the machine learning algorithm can assess build orientation and surface roughness to provide local SN curve predictions.