Through machine learning, DataProphet has been tasked with reducing quality variation and the resulting scrap and rework. DataProphet consolidated several thousand process parameters that have an impact on overall quality, upon which the controllable prescriptions will be delivered in-line.
“We wanted to take a deeper look at our data to see if we could improve plant productivity,” said Jeff Sutter, Global Director of Innovation & Continuous Improvement, Nexteer Automotive. “With DataProphet’s advanced deep learning capabilities, we are exploring factors that will allow us to not only reduce scrap but improve the entire manufacturing process. Deep learning allows us to further build on our investments in Digital Trace™ Manufacturing.”
DataProphet’s AI for dynamic process control is built specifically to learn complexities and provide operators on the line with the optimal plan to reduce scrap. By learning from historic production and quality data, DataProphet PRESCRIBE is able to prompt the operator with the next best action – preserving the institutional knowledge otherwise hidden in the data. DataProphet’s solutions are proven to frequently deliver over 50 percent reduction in scrap for manufacturing customers around the world.
Read the full press release here.