The Industrial Edge-to-Cloud Strategy

Aug. 6, 2021
It’s not whether you’ll use cloud or edge computing, but how you’ll combine the two. Here’s a look at how Google and Litmus are working together to make this easier for manufacturers.
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Quick hits:

  • Learn why cloud computing is typically used to process aggregated production data for longer-term strategic analysis and planning offsite, while edge computing is used more for real-time analysis—on premises—of specific equipment or system performance.
  • Why Google is incorporating Litmus’ industrial edge computing platform into its suite of smart factory products.
  • How this combination of Google and Litmus technologies makes it easier for manufacturers to gather data from all factory systems, not just a few specific pieces of equipment on the plant floor.

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Read the transcript below:I’m David Greenfield, Director of Content at Automation Worldand thanks for joining me for this Take Five episode where I’ll be explaining the current state of the Industrial Edge-to-Cloud Strategy.

So, no matter if you work on the plant floor or the front office, you’ve been hearing a whole a whole lot about the use of edge and cloud computing in industry over the past several years now. And as the use of cloud and edge computing technologies has grown throughout industry, one thing became clear—and that is: it’s not whether you’ll use cloud or edge computing, but how you’ll combine the two. 

Both technologies are needed in manufacturing and processing industry applications because they are used to address different purposes. Feedback from Automation World readers indicates that cloud computing is more typically used to process aggregated production data for longer-term strategic analysis and planning, whereas edge computing is used more for real-time analysis—on premises—of specific equipment or system performance.

Before going any further, it’s a good idea to make sure we’re all on the same page as to how these technologies are defined. Essentially, edge computers are servers located on the plant floor or even directly connected to assets…that collect and aggregate real-time data from the equipment they’re connected to for analysis on the edge computer itself or for transfer to the cloud for storage and analysis.

Likewise, cloud computers are also servers, like edge computers, but they exist offsite and are often combined as part of a computing array to enable the application of advanced analytics to large amounts of plant floor data. And you’ve likely heard of fog computing as well, which is basically a smaller version of a cloud computing array, but with edge computers located on site.

So with that explanation of edge, cloud and fog computing out of the way and with the understanding that its clear manufacturers are using a combination of edge and cloud computing technologies, let’s look at what technology suppliers are doing to facilitate industry’s use of cloud and edge computing technologies in a hybrid way.

One of the more recent announcements in this area is that Google and Litmus, a supplier of edge computing technology, have announced a strategic partnership to offer an integrated edge-to-cloud system where the Litmus’ industrial edge computing platform is incorporated into Google Cloud’s suite of smart factory products.

John Younes, co-founder and chief operating officer at Litmus, said this partnership between Litmus and Google is unique because he says it’s the first ever combined edge-to-cloud system from a cloud company. This will make it quick and easy for customers to get access to their machine data in the cloud, he said.

I should note here that Litmus and Google already had a partnership agreement around applying artificial intelligence capabilities at the edge with 5G networks. Younes said this expanded alliance more tightly integrates each company’s offerings and allows customers to purchase it all directly from Google through a go-to-market partnership.

As part of this announcement, Google and Litmus note that a primary reason the manufacturing industries haven’t yet undergone a more widespread digital transformation is because cloud analytics, artificial intelligence, and machine learning require a steady and reliable flow of factory data to power the edge and cloud computing systems that run data models. This has been a challenge for industry because it’s not just about gathering data from a few systems, but data from all factory systems.

Vatsal Shah, Litmus co-founder and CEO, said the reality is that factories struggle to connect to all the machines they have, which often have no common data structure among them, and the systems typically don’t talk to each other and can’t easily share complete factory data with the cloud. He said this is the biggest problem companies face when it comes to making the digital transformation because data is critical to enabling smart manufacturing use cases like condition-based monitoring, predictive maintenance, and overall equipment effectiveness.

Younes explained that Litmus’s edge technology standardizes plant floor data into a JSON structure following the IPSO Alliance’s data format structure. He also noted that customers can transform data into their own custom formats if they choose. He said this is how Litmus Edge normalizes data at the edge—across almost all PLCs, robotics, CNC machines, protocols, etc. with its more than 250 drivers—before sending it to the Google Cloud Platform.

So, I hope you enjoyed this Take Five with Automation World episode and remember to keep watching this space for new episodes each week to help keep you on top of what’s happening in the world of industrial automation.

About the Author

David Greenfield, editor in chief | Editor in Chief

David Greenfield joined Automation World in June 2011. Bringing a wealth of industry knowledge and media experience to his position, David’s contributions can be found in AW’s print and online editions and custom projects. Earlier in his career, David was Editorial Director of Design News at UBM Electronics, and prior to joining UBM, he was Editorial Director of Control Engineering at Reed Business Information, where he also worked on Manufacturing Business Technology as Publisher.