Companies need to be open to new technologies to see fundamental paradigm shifts in productivity, beyond incremental improvements. Rapid increases in productivity, visibility, flexibility, and agility are needed.
Some applications require data acquisition strategies without cloud connectivity, but they can still benefit from advanced analytics technology.
Centralized data architectures are adapting to new opportunities for data collection and analytics.
TrendMiner 2019.R1 self-service analytics software release for process manufacturing includes a visual representation of time-series data, making it easier for users to analyze, monitor and predict process and asset performance.
FieldComm Group's process automation device information model specification (PA-DIM) has been endorsed by the OPC Foundation, and Profibus & Profinet International (PI).
New software and input/output (I/O) devices can help users eliminate useless data through effective diagnostics, error localization and filter designs to extract accurate figures.
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Did you just see something extraordinary in the recorded data or was it a data anomaly in measurement, communications, or data aggregation? Data collection should help us learn, not confuse. Heed these five strategies for better industrial data.
The Industrial Internet of Things (IIoT) equipment should be integrated even into older manufacturing systems to optimize facility and system operations. Think you’re using IIoT technologies? Are you adding sensors in 12 steps or 6 steps?
With processing power increasing, controllers tucked in input/output (I/O) communication blocks make distributed controls easier than ever. With the increased controller capabilities, higher speed/more open communication protocols and more powerful, lower cost microprocessors, more distributed and autonomous systems seems likely.