Advanced Remanufacturing and Technology Centre (ARTC)

A specially designed computational model guides the development of next-generation metal welding processes by predicting how heat affects the strength of welded joints.

A novel machine learning model predicts wear and tear in manufacturing parts with less real-world data for cost savings and improved productivity.

An algorithm inspired by nature guides metal-depositing lasers for faster, more precise component manufacturing.

Game-changing new ideas and products are born from connecting the right minds and hands. In this cover story, we spotlight how A*STAR facilitates those connections and cultivates the culture needed for an ecosystem of innovation.

A*STAR’s steady investments in R&D and talent create the ideal conditions for impactful science, says its Chief Executive Officer Frederick Chew.

By breaking complex actions into their basic components, researchers have developed a versatile framework that enables robots to learn from human demonstrators.

By eliminating bottlenecks and automating manual processes, the RESOLUTE test kit and RAVE system co-developed by A*STAR scientists will help give COVID-19 testing a much-needed boost.

Researchers across A*STAR are developing the hardware and software needed to take factories to the next level in Industry 4.0.

The strength of steel comes from carbon, which is lost when steel is heated, resulting in weakening of the alloy. A*STAR researchers have found a way to overcome carbon loss with lasers.

Laser-based sensor measures the surface roughness of materials in real time.

A new class of collaborative robots may be the future of industrial remanufacturing