Diagnostics, Asset Management
Six edge computing questions to ask about data collection, networking and control systems.
Even in the wake of COVID-19 (coronavirus), manufacturers still need human workers to manage the supply chain. The need for more automation and information is an opportunity for manufacturers.
MIT Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable and robust.
With automation at an inflection point, a variety of technologies and interoperable standards efforts are bringing higher levels of flexibility, integration and optimization.
Expand industrial data access and get more out of it with tools such as message queuing telemetry transport (MQTT), which can help manufacturers realize Industry 4.0’s benefits.
Many manufacturers are becoming increasingly concerned with Covid-19 breakouts on the production floor. There are ways to improve worker safety through preventive best practices and proper preparation.
Case-use examples illustrate the point
It is becoming a reality that artificial intelligence (AI) are starting to change the traditional role of the control engineer. There are some benefits, but there also potential barriers to its adoption in the industrial environment.
MIT researchers have developed flexible sensors and an artificial intelligence model that tell deformable robots how their bodies are positioned in a 3D environment.
Purdue University researchers have developed a cybersecurity tool designed to stop cyber attacks using supervised machine learning, unsupervised machine learning and rule-based learning