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December 11, 2020

3M manufacturing plant uses data analytics to increase efficiency and cost savings with Azure SQL Edge

3M produces more than 60,000 products in its Safety and Industrial, Transportation and Electronics, Healthcare, and Consumer Business Groups. At one of its US manufacturing plants, the 3M Corporate Research Lab partnered with the local 3M Manufacturing team and identified an opportunity to predict anomalies and then use those insights to reduce manufacturing downtime. They proposed integrating data streams from two production lines, correlating them, and then running analytics and machine learning locally. Because the data came from two systems that arrive at different times, and because the plant’s network connectivity was limited, the team determined that building a custom module with Microsoft Azure SQL Edge deployed through Microsoft Azure IoT Edge would give the performance, management, and security needed. With this new edge capability deployed, the resulting faster and more streamlined processes will allow 3M to identify a manufacturing line’s problems in advance, thus providing both operational efficiency and cost savings benefits.

3M

“Azure SQL Edge is a great bridge between traditional processes and the newest AI and compute features in the cloud. This is the type of solution that will drive us towards Industry 4.0.”

Mike Gerlach, Manufacturing Technology Manager, 3M

The 3M brand is a familiar household name to consumers. It’s unusual to find a work desk that doesn’t include some of its products, such as Scotch® tape and Post-it® notes. 3M produces much more than office supplies, though, including the N95 respirators certified by the National Institute for Occupational Safety and Health as personal protective equipment for healthcare personnel. 3M categorizes its more than 60,000 products—which are as varied as dental and orthodontic products, window film, electronic connecting materials, and healthcare software—into four diverse business groups: safety and industrial, transportation and electronics, healthcare, and consumer. Having begun as a Minnesota-based mining company in 1902, 3M has evolved into a Fortune 500 company that employs 96,000 employees in 87 countries.

Predictive maintenance lets 3M fix problems before they occur

Edge computing and IoT edge devices are transforming manufacturing by driving better efficiency and productivity as well as helping companies cut costs. At one of 3M’s manufacturing plants, increasing its manufacturing lines efficiency was often time-consuming and labor intensive. It was difficult to gather, transfer and use the data from the production systems. The 3M corporate research team and local manufacturing organization came to a bold new solution, processing and analyzing the big data locally – at the edge. By applying analytics and machine learning to their manufacturing data using Microsoft Azure SQL Edge, a highly secure database engine optimized for IoT edge workloads, 3M discovered a way to streamline processes, maximize efficiency, and save money.

“We leverage the latest cloud capabilities to accelerate our research & development towards new epic solutions. Efficient edge and cloud data flow capabilities are strategic areas of focus. Cloud capabilities are constantly evolving, so it is critical for us to stay close to or in front of these rapid technology evolutions,” says Hung Brown Ton, Chief Architect & Lab Manager at 3M. The goal was to push data from the plant’s on-premises SQL Server to Azure SQL Edge, enable downstream applications to use the data stored in the SQL Edge device, and then upload it to the cloud.

When 3M was developing an algorithm that allowed them to predict problems on the manufacturing line hours before they appeared, they created an IoT edge solution for the algorithm. “The module sits on our Azure IoT Edge device. It’s cloud trained and deploys to Azure SQL Edge, where the manufacturing line data resides, and operates seamlessly to create predictions,” explains Aaron Burstein, Data Systems Manager at 3M.

By correlating and analyzing two data streams, one with sensor data about the manufacturing equipment and the other product information as it went through the line, they were able to apply analytics and machine learning to the data. Using Azure SQL Edge, the team created a solution to sync data from there to the cloud, which Burstein says is “fault-tolerant” under almost any network condition.

“And once it was in the cloud, we could bring in all our machine learning tools— Azure Machine Learning Studio, HDInsight Machine Learning Services, and our Databricks clusters. We’d never had that capability there to be able to visualize it and use some of the compute in the cloud.”

Using SQL Edge also resolved the plant’s problem of limited network capacity. When they began processing data at the edge, their efficiency increased because they were able to keep operating even when the plant was offline.

The plant’s pivot to edge computing, which reduced latency too, also saved 3M time. Moving data from the plant to Azure went from taking weeks to just minutes. Previously, an export of a SQL dataset was uploaded into SharePoint, spun up with virtual machines, and restored back to a database into a subscription or a SQL service in the cloud.

Working at the edge with SQL Edge and IoT Edge has been a breakthrough for the local manufacturing team. “Data processing at the edge is really attractive because it takes your local process and pushes it to a device that I call a bridge to the cloud. Our plant engineer can use their existing processes and tools and do everything locally while connecting with the same SQL codebase at the edge,” says Burstein.

Easy interoperability makes processes easier and faster

Burstein says the team investigated and then selected Azure SQL Edge because 3M aims to use native services whenever possible. “We’re always interested when Microsoft comes out with new services and technologies we think can advance us further. We’re always looking to use the latest and greatest.”

According to Libby Oliver, Data Engineer at 3M, “It took only one engineer an average of six hours to add Azure SQL Edge into the company’s current stack business processes. Prior manual steps could take weeks, and with the new solution it takes minutes.”

“Without the consistent SQL codebase, we’d have to write a lot more code, and coordinate between each module of the code we wrote,” Oliver says. “It would be a lot more work for us to provide, coordinate, and manage the modules. There would be much more custom monitoring, amendments, and support.”

Saving money, time, and effort as Industry 4.0 approaches

“Thanks to faster, more efficient processes at the edge, we’re anticipating significant improvements and cost savings,” Burstein says. “That’s with the overall algorithm savings. Once we scale some of these things, we could see even more substantial savings.”

Mike Gerlach, Manufacturing Technology Manager, says he’s happy the team chose Azure SQL Edge because it was so efficient to incorporate into their pipeline. He notes that it will be easy to repeat the process and deploy the edge gateways and devices to other manufacturing sites. He believes the investment in the IoT edge will be critical in 3M manufacturing. “Azure SQL Edge is a great bridge between traditional processes and the newest AI and compute features in the cloud. This is the type of solution that will drive us towards Industry 4.0.”

“We leverage the latest cloud capabilities to accelerate our research & development towards new epic solutions. Efficient edge and cloud data flow capabilities are strategic areas of focus. Cloud capabilities are constantly evolving, so it is critical for us to stay close to or in front of these rapid technology evolutions.”

Hung Brown Ton, Chief Architect & Lab Manager, 3M

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