Lam Research Corporation has launched Dextro, a collaborative robot (cobot) designed to enhance maintenance tasks in semiconductor wafer fabrication facilities. This marks the first such cobot introduced to the semiconductor industry, with the aim of improving yield, reducing downtime, and increasing the precision and repeatability of maintenance processes.
Dextro is engineered to operate alongside fab engineers, tackling complex maintenance tasks on advanced wafer fabrication equipment. It is capable of sub-micron precision, which improves the consistency of tool performance and reduces variability in production. Lam Research highlights that Dextro’s deployment has already begun in several advanced wafer fabrication plants globally.
Chris Carter, Group Vice President of the Customer Support Business Group at Lam Research, emphasized the cobot’s contribution to productivity and cost-effectiveness, noting its ability to perform tasks beyond human precision. Carter framed Dextro as a pivotal addition to Lam’s offerings aimed at helping semiconductor manufacturers optimize their operations.
Dextro addresses challenges arising from the growing scale and complexity of fabs, as well as a shortage of skilled engineers. It enhances maintenance efficiency by automating tasks that are time-intensive or prone to human error. Examples include the precise assembly of components, the tightening of high-precision bolts, and the removal of chamber polymer build-up—all with greater accuracy and reduced risks compared to manual methods.
Samsung Electronics, which has implemented Dextro, reported benefits such as improved production variability and yield. Young Ju Kim, Vice President and Head of the Memory Etch Technology Team at Samsung, described the cobot as a milestone in advancing toward an autonomous fab.
In addition to its current compatibility with Lam’s Flex G and H series dielectric etch tools, Dextro is expected to support additional tools in 2025. This aligns with Lam Research’s broader portfolio of automation and efficiency solutions, including its Equipment Intelligence® platform, which leverages artificial intelligence and machine learning to optimize fab operations.
