Major car manufacturer migrates production floor to the cloud
Migrating production floor to the cloud in less than six months
One single application providing analytics to support business processes
Using relevant data to reduce costs, downtime and improve quality
Wrangling with disparate data
A major U.S. car manufacturer has made a bold commitment to shift more of its production to electric vehicles (EVs). In 2021 it announced it would begin producing an electric version of one of its most popular vehicles.
Shifting from internal combustion engines to electric motors isn’t simple. The move changes the entire architecture of the shop floor. The higher level of electronics in cars, especially EVs, creates an opportunity to boost productivity and improve quality by enabling better communication among vehicles, facilities, and the manufacturing process during assembly.
The increased connectivity of the Internet of Things (IoT) produces vast amounts of data, but that data must be located, organised, and analysed. In the car-making process, data sets are typically spread among vendors, parts-manufacturing facilities, and assembly plants. As a result, much of the data resides on vendors’ hardware, with on-premises data centers at various manufacturing plants, and on many different clouds. In addition, data are collected from sensors and other IoT devices on the production floor, but there is little consistency from one plant to the next.
In this carmaker’s case, it wanted to aggregate its manufacturing data into a single platform that it could access from any location. The company envisions an environment of seamless connectivity among its EVs, its people, and its manufacturing equipment.
Digitising the factory floor
GFT has deep knowledge in automotive and manufacturing, and it has worked closely for many years with Google Cloud, the manufacturer’s preferred cloud provider. That enabled GFT to develop a cloud platform that could collect, aggregate, and synthesise manufacturing data from disparate sources onto a single application based on Google Cloud’s Manufacturing Data Engine platform.
GFT created data parameters, processed the collected information, and then used machine learning to develop dashboards and other data visualisation interfaces for the car manufacturer and its suppliers.
For a test bed, GFT and the manufacturer selected a stamping plant that makes outer body panels for pickups and commercial vans. The line produces about 900 parts per hour, or about 3 million panels a year. For each of those, the company’s sensors and other monitoring equipment track incoming materials, analyse assembly line operations, and collect images of each part produced by the line. The company hosted the image collection on Google Cloud, but the volume of data was overwhelming.
In a matter of months, they had amassed 500 million data points that needed flexible and reliable storage. One of the first steps was working with the company to identify extraneous data that it didn’t need for the new application. GFT took the remaining data sets and defined operational and technical requirements, and then tested the system on the stamping line.
By processing and analysing the stamping-line data, the manufacturer was able to spot variations in materials, control the stamping process parameters more effectively, and determine the output for better-quality parts.
Collecting all the data on a single platform allows the manufacturer to review data sets from different sensors. By comparing two sets of data from similar equipment, the company can monitor differences in performance, spot malfunctions early, and make repairs with less disruption to the production line.
GFT conducted the pilot effort in about three months, and the entire rollout was completed in about six.
Using relevant data to reduce costs and downtime, improve quality
The pilot proved successful, and the car maker is implementing the platform across other factories. With the consolidated cloud platform, the company can create new applications based on access to more manageable and meaningful data than the company had before.
For example, with information collected from factory sensors, the company can better understand operating patterns and detect irregularities. As a result, it can target preventive maintenance efforts to ensure machines are repaired before they break down and that routine maintenance isn’t done unnecessarily on equipment that’s working properly.
The platform also will allow better quality control of body panels, batteries, parts, and other components before they’re installed. By making any necessary adjustments early in the process, it can improve the quality and reduce defects, recalls, assembly line stoppages, and other costly corrections.
GFT, working with Google Cloud, has built a robust data platform that gives the manufacturer a comprehensive structure integrating all data sources and providing analytics to support its business processes across factories and manufacturing lines.
“Ultimately, the platform is addressing a very common need across all manufacturers, which is that all this information is being produced, but the data isn’t being used to its full potential. We took all the native core cloud components and configured them for ingesting and managing manufacturing data to produce greater insights and operating efficiencies.”
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GFT, as an official global service provider, used the Google Cloud Manufacturing Data Engine solution to bring digital transformation to the car manufacturer's shop floor in less than six months.