Installing computer systems can be an arduous process for new and existing manufacturing plants; basic best practices for enclosures can help companies avoid costly pitfalls and long-term challenges. See five tips for using computers on the plant floor.
Integrating safety systems into a machine’s standard control platform simplifies operations, increases diagnostic capabilities and creates safer work environments for engineers and end users.
Test driven development (TDD) is potentially useful for automation applications by eliminating the separate task of creating requirements and specifications by incorporating requirements into the test protocols.
Cover Story: Automation technologies continue convergence across platforms and computer numerical control (CNC) technology advances, along with faster control hardware and software, allow engineers to complete more accurate cuts in less time.
North Carolina State University researchers have developed AOGNets, a framework for building deep neural networks that uses a compositional grammar approach to extract useful information from raw data.
A team of researchers at Texas A&M University looked at the best way to document computer code by using samples and found that good naming, and comment were more important than good documentation.
The MIT-Air Force AI Accelerator, will conduct fundamental research directed at rapid deployment of artificial intelligence (AI) innovations in operations, data management, cybersecurity, and vehicle safety.
North Carolina State researchers have developed a framework for deep neural networks that allows artificial intelligence (AI) systems to become better at performing previous tasks by learning from its prior actions.
While embedded vision is still an emerging technology, to date there are typically two main types of processors used in embedded systems – field programmable gate arrays (FPGAs) and graphics processing units (GPUs).
Texas A&M University researchers have been awarded a National Science Foundation (NSF) grant to research data mining to optimize decision making in the software brain.