Google and Litmus Expand Edge-to-Cloud Partnership

This new partnership agreement centers on the integration of the Litmus industrial edge computing platform into Google Cloud’s smart factory suite.

July 22, 2021

4 min read

As the use of cloud and edge computing technologies proliferated throughout industry, one thing became clear—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 of specific equipment or system performance.

To help address industry’s combined use of both technologies, Google (a provider of cloud computing services) and Litmus (a supplier of edge computing technology) have announced a strategic partnership to offer an integrated edge-to-cloud system wherein 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 “it’s the first ever combined solution from a cloud company—both from a product and go-to-market perspective. This differentiates the Google Cloud Platform over AWS (Amazon Web Services) and Microsoft Azure and takes them miles ahead of their edge computing for manufacturing offerings by bundling Litmus. This will make it quick and easy for customers to get access to their machine data in the cloud.”

Litmus and Google already had a partnership agreement around applying artificial intelligence (AI) capabilities at the edge with 5G networks. According to Younes, 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.”

All production data

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

Read more about how industry is using a combination of cloud and edge computing technologies.

“The reality is factories struggle to connect to all machines, have no common data structure, the systems do not talk to each other and cannot easily share complete factory data with the cloud, said Vatsal Shah, Litmus co-founder and CEO. “This is the biggest problem companies face and this is the problem Litmus solves because data is critical to enabling smart manufacturing use cases like condition-based monitoring, predictive maintenance and OEE (overall equipment effectiveness) improvement.”

Shah added, “Litmus is the bridge to Google Cloud, easily connecting to all machines on the factory floor, collecting and structuring all data in way that can be easily sent to Google Cloud to build and run data models, and finally taking those data models and putting them to work next to the equipment on the shop floor to improve manufacturing operations.”

Data standardization

Younes explained that Litmus’ edge technology standardizes plant floor data into a JSON structure following the IPSO Alliance’s data format structure. “But customers can transform data into their own custom formats,” he added. “This is how Litmus Edge normalizes data at the edge—across almost all PLCs, robotics, CNCs, protocols, etc., with our more than 250 drivers—before sending it to the Google Cloud Platform.”

Dominik Wee, managing director, manufacturing and industrial, Google Cloud.

Aggregating data from all plant floor equipment is critical to deriving benefit from AI applications because AI for manufacturing is “limited when not all machine data is analyzed,” said Younes. “With more data points to evaluate, more use cases can be developed with more equipment and data sources, delivering quicker results and more parameters to take decisions on in real time.”

“The biggest challenge our customers face is access to quality machine data,” said Dominik Wee, managing director, manufacturing and industrial, Google Cloud. “Our partnership with Litmus will enable organizations to quickly put factory data to work, seamlessly integrating with our analytics, machine learning, and AI capabilities to improve manufacturing operations across the entire enterprise.”