Human inspection of high quality components in advanced manufacturing, automotive and aerospace applications is challenging, as detecting imperfections that are variable can result in inconsistent part quality decisions. These inspection tasks are very repetitive. Achieving zero incorrect part quality decisions that are required in high tolerance assembly, as well as in critical process operations becomes […]

This project explores incorporation of artificial intelligence tools for advanced control techniques in order to improve quality on industrial production lines. Particularly, the novelty of this project suggests the use of the recent embedded computer systems and icloud computer assistance. This strategy is currently used for commercial products (i.e., application related to communication). However, this […]

This project encompasses various sub-projects aimed at developing enhanced approaches that will facilitate higher performing machines, geared towards enabling the concept of factories of the future (FOF). While this concept is established, research on new approaches that facilitate FOF are still early. The project conducts research on several sub-projects that include machine learning based robotic […]

This phase of the project continues on the research focus of developing intelligent control for machines using derived deep machine learning schemes. The learning algorithms to be developed will use high volume data from various processes in advanced manufacturing and other systems, combined with could based analytics, formulate complex and accurate process models of these […]