Jabil, a leading design and manufacturing solution provider, has built a new predictive analytics solution on Microsoft Azure Machine Learning.
Revealed at this week’s Hannover Messe event, the new platform helps prevent errors or failures occurring on the assembly floor by predicting potential problems in advance. This helps Jabil deliver high quality products in shorter lead times across the supply chain.
Jabil is using Microsoft Azure services to analyse millions of data point from machines across the manufacturing process. Thanks to Azure Machine Learning, the company can identify potential problems early in manufacturing process, and before they have a major impact. This enables Jabil to be more proactive in the work they do and improve productivity.
“Since deploying the Microsoft predictive analytics solutions we have seen at least an 80% accuracy rate in the prediction of machine processes that will slow down or fail, contributing to a scrap and rework savings of 17%,” said Clint Belinsky, vice president of global quality, Jabil. “As our customers constantly look for ways to innovate, it is very impactful to show them a predictive solution that will ensure quality and increase their speed to market.”
The company has saved money and time since introducing the solution, as well as a reduction in the number of equipment inspections, which causes machine downtime.
To date, the platform has been rolled out at two of the company’s ‘megasites’ in Guadalajara, Mexico and Penang, Malaysia. Jabil is now planning to introduce the solution at its facilities worldwide.
“Jabil’s digital transformation on the factory floor will reshape its industry,” said Jason Zander, corporate vice president of Microsoft Azure at Microsoft. “As product cycle times shorten and products get smarter, Jabil understands how the intelligent cloud combined with predictive analytics will help it support the needs of its customers.”
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