DELL TECHNOLOGIES, page-37

https://www.delltechnologies.com/en-us/blog/ai-set-to-turbocharge-the-factory-floor/?dgc=SM&cid=10094&lid=spr4733353115&RefID=dtw21_spr4733353115&linkId=116294725

"Manufacturing and the industrial automation industry have always been quick to embrace innovation. Modern factories are now capturing rich data at every step of the manufacturing process.

When this data is fed into new technologies that enable machine learning (ML) and artificial intelligence (AI), manufacturers can quickly achieve previously unattainable levels of efficiency and quality.AI is fundamental to survival. By 2022, IDC predicts that 75% of enterprises will embed intelligent automation into technology and process development, using AI-based software to guide innovation.

This has implications for industrial solution builders, who need to urgently rethink their products and services, or risk being left behind by more agile competitors. Technology and solution architecture must evolve quickly to support this transformation.

ALSO -
https://www.delltechnologies.com/en-us/oem/industrial-automation.htm#scroll=off&pdf-overlay=/en-us/collaterals/unauth/briefs-handouts/solutions/oem-solutions-ai-smart-industry-infobrief-march-2021.pdf

Making faster decisions with AI at the Edge When the goal is to make faster data-driven decisions, rather than train new behaviors or patterns, pushing AI to the Edge allows for quick execution on data streams.

As the bandwidth of available data expands due to the explosion of sensors on equipment and the use of higher-resolution video, the latency of transporting that data to the Cloud for decision-making creates latency on the factory floor. The sheer volume of data can also make transportation to the Cloud cost prohibitive. This is an example of data gravity.

Since latency, volume and cost of transport of the data keeps the data in place, it is necessary to bring the compute closer to the data. Bringing the right technology to the Edge gives a two-fold advantage. First, rather than transporting the data to the Cloud and back for answers, companies can make immediate decisions using the near realtime analytics and data insights delivered at the Edge.

Second, the data can be aggregated and refined at the Edge, moving only the most relevant data to the Cloud for further analysis.