Application of machine learning for prediction and process optimization—case study of blush defect in plastic injection molding

HIGHLIGHTS

• who: Alireza Mollaei Ardestani and colleagues from the Department of Civil and Mechanical Engineering, Technical University of Denmark have published the Article: Application of Machine Learning for Prediction and Process Optimizationu2014Case Study of Blush Defect in Plastic Injection Molding, in the Journal: (JOURNAL)
• what: The research by Tabi et_al aimed at improving the needle-shaped defects around the gate location. The aim of the study was to compare FEA simulation results with experiments with focus on flow hesitation. This research has inspected the effects of eight injection molding factors (flow rate, melt temperature, holding pressure . . .
  

   

  

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