Four analytics applications that majorly impact IIoT success
For controls engineers building factory machinery, key Industrial IoT technologies enhancing data analytics allows them to monitor vast connected assets, fostering a collaborative approach to operations.
Machine Design, a Control Design partner publication, highlighted four technologies that drive effective data analytics.
Cloud computing: This enables scalable data storage and remote access across distributed assets, streamlining cross-location collaboration.
Equipment sensors: These provide real-time monitoring, helping engineers detect and address issues proactively through predictive maintenance strategies.
Artificial intelligence (AI): This accelerates data processing, uncovering complex patterns and insights to optimize equipment performance and process efficiency.
Generative AI chatbots: These facilitate interactive problem-solving and help engineers quickly analyze data trends, supporting quality control and process refinement.
For more, check the full article from Machine Design here.
Are your heavy duty, automation applications tired of the mess, space, complexity, cost and other issues related to hydraulic systems? Converting to electromechanical linear actuators...
Industrial motors account for a significant portion of energy costs. But reduced power spend isn’t the only advantage of using drives. And motor selection isn’t always...
