A BP-neural network predictor model for plastic injection molding process

By B. Sadeghi. 2000

302 citations recorded by the source corpus.

Subfields: Automotive Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/c0a625b80fa3736c13b78aaef8db267a70a2750c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Hua-jie Mao
2. Lin Hua
3. Wei Hua Guo
4. Gülser Köksal
5. Murat Caner Testik
6. Inci Batmaz

In Mechanical Engineering

1. Maosheng Shu
2. Hua-jie Mao
3. Lin Hua
4. Wei Hua Guo
5. Fei Yin
6. Gülser Köksal
7. Murat Caner Testik
8. Inci Batmaz

Citations in the corpus

• A review of data mining applications for quality improvement in manufacturing industry (2011, methodology): “ANN were considered in diagnosis of the causes of prestressed concrete damages (Tam, Tong, Lau, & Chan, 2004), and in predicting the quality of injected plastic parts (Sadeghi, 2000).”
• Back Propagation neural network modeling for warpage prediction and optimization of plastic products during injection molding (2011, background): “Sadeghi predicted the quality of the injected parts by using the neural network [20].”
• Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook (2020, unknown): “The ability to collect a vast amount of data on these changes can help in increasing ef fi ciency and quality [148,149].”