no code implementations • 27 Mar 2024 • Dennis Gross, Helge Spieker, Arnaud Gotlieb, Ricardo Knoblauch
This research presents a method that utilizes explainability techniques to amplify the performance of machine learning (ML) models in forecasting the quality of milling processes, as demonstrated in this paper through a manufacturing use case.
