by Team ProcessMiner | Mar 11, 2021 | Press Release
ProcessMiner™, an artificial intelligence platform for manufacturing, announced today its expansion into Europe to integrate its solutions and address the growing needs of Finland and the greater EU region.
by Team ProcessMiner | Mar 8, 2021 | Press Release
ProcessMiner, an artificial intelligence platform for manufacturing, and Industrial IoT Solutions, an information technology integrator and solutions distributor focused on delivering proven IIoT (Industrial Internet of Things) technology in Brazil, today announced a partnership to deliver ProcessMiner’s real-time AI-powered decision automation platform to manufacturing industries across Latin America.
by Team ProcessMiner | Feb 23, 2021 | Press Release
Understanding Deep Learning: Application in Rare Event Prediction Chitta Ranjan, Ph.D., Director of Science, ProcessMiner, Inc. Think of deep learning as an art of cooking. One way to cook is to follow a recipe. But when we learn how the food, the spices, and the fire...
by Team ProcessMiner | Jan 21, 2021 | Press Release
ProcessMiner™ will partner with the manufacturing industry’s most innovative companies to deliver its real-time AI-powered decision automation platform to manufacturing industries across the globe. ProcessMiner™, an artificial intelligence platform for...
by Team ProcessMiner | Jan 13, 2021 | Press Release
ProcessMiner™ announced today that Professor William H. Woodall has been appointed to the company’s Scientific Advisory Board. Dr. Woodall is Professor Emeritus of Statistics at Virginia Tech, a former editor of the Journal of Quality Technology (2001–2003), and was a longtime Associate Editor of Technometrics.
by Team ProcessMiner | Aug 19, 2020 | Press Release
Developed with ProcessMiner™, a leading AI platform, Solenis’ adaptive analytics system accurately learns complex variable relationships in pulp and paper manufacturing processes and yields a digital measure of product quality. Autonomous manufacturing using AI with machine learning allows for improved product quality, optimized use of raw materials and reduced water and energy consumption.