Injection molding is widely used to produce plastic components with large lot size. However, guaranteeing consistency and quality of parts in injection molding is challenging. Failures occur due to variation during injection cycles. Thus, real-time detection of failures will have a high impact on quality and productivity.
The SHION approach into use cognitive technologies (specially Deep Learning algorithms) helped to be able to extract the knowledge to generate a predictive model to detect when a defect in the production is going to happen. SHIOn Experiment Partners now had the opportunity to publish their experiment analysis at IEEE.org.
Learn more about SHION Experiment:
SHION: Towards An Interactive Digital Twin Supporting Shopfloor Operations on Real Time
Download study at IEEE.org: