Edge Computing, Embedded Systems
Artificial intelligence at the edge improves manufacturing productivity
AI at the plant floor’s edge empowers machine builders to increase production quality and efficiency
AMP upgrades to edge controllers
Largest U.S. rotary heat-treating facility modernizes controls and automation with tight database integration.
Edge computing, artificial intelligence power automation innovation
Edge computing allows engineers to use lower costs to develop newer applications such as shop-floor data analysis and quality prediction. Artificial intelligence (AI) improves the efficiency and accuracy of plant operations.
Edge I/O brings more connectivity to field devices and sensors
Latest remote I/O combines IIoT communication with even more processing power than traditional intelligent I/O
Automation at the Industrial IoT edge
Leverage edge technologies in good times and bad by using remote visualization, monitoring, access and management as well as artificial intelligence (AI), machine learning (ML) and analytical applications.
Patching embedded systems aids cybersecurity efforts
Improving the process of patching code in vulnerable embedded systems is a major cybersecurity concern because much of the code currently running is vulnerable to hackers.
Embedded HMIs excel in automation applications
Delivering the right human-machine interface (HMI) experience is critical whenever people need to interact with automation.
How edge computing will unleash the potential of IIoT
Combining the potential of Industrial Internet of Things (IIoT) devices with the processing power of edge computing, automation solutions and analytics is giving manufacturing production data more value. See five ways to make edge IIoT deployment more effective.
Is it time to look at edge computing?
With the rise of 5G in manufacturing, effective edge computing requires consideration of industrial PCs (IPCs) at the edge.
Moving toward self-assembly machine automation systems
Evolving PLC and PAC platforms, networking, and programming methods are leading to self-assembled machine automation systems, reducing risk and user integration efforts.