In digital manufacturing, quality assurance across the assembly line is imperative. Identifying errors, slowdowns and potential failures before they occur, rather than after they happen, can help companies be more proactive and improve productivity.
In light of this issue, Microsoft announced Monday that Jabil, a design and manufacturing solution provider, has built its predictive analytics solution on Microsoft Azure Machine Learning. This new platform predicts errors or failures on the assembly floor before they occur, saving its customers time and money while delivering superior quality and shortened product lead times throughout the entire supply chain. Jabil has rolled out the platform in two of its megasites in Penang, Malaysia and Guadalajara, Mexico, and plans to deploy the solution to its facilities worldwide.
Through a collaboration with Microsoft, Jabil is using Microsoft Azure services to analyze millions of data points from machines running dozens of steps throughout the manufacturing process. Through Azure Machine Learning, Jabil can help predict failures earlier in the process, for example, at step two in a 32-step process instead of step 15.
"Since deploying the Microsoft predictive analytics solutions, we have seen at least an 80 percent accuracy rate in the prediction of machine processes that will slow down or fail, contributing to a scrap and rework savings of 17 percent," said Clint Belinsky, vice president, 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."
"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,” said Jason Zander, corporate vice president of Microsoft Azure at Microsoft. Jabil’s use of digital transformation on the factory floor will be useful as industries continue to evolve.
In addition to time and cost savings through the reduction of waste, Jabil's operators and engineers can proactively make adjustments to equipment based on predictions, eliminating the need for unnecessary inspections that cause downtime.