Multi-quality prediction of injection molding parts using a hybrid machine learning model
Author:
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00170-023-12329-6.pdf
Reference22 articles.
1. Wang M-L, Chang R-Y, Hsu C-H (2018) Molding simulation: theory and practice. Carl Hanser Verlag GmbH & Co, KG, München
2. Zhang Y, Mao T, Huang Z, Gao H, Li D (2016) A statistical quality monitoring method for plastic injection molding using machine built-in sensors. Int J Adv Manuf Technol 85:2483–2494
3. Kurt MB, Kamber OS, Kaynak Y et al (2009) Experimental investigation of plastic injection molding: assessment of the effects of cavity pressure and mold temperature on the quality of the final products. Mater Des 30:3217–3224
4. Gordon G, Kazmer DO, Tang X, Fan ZA, Gao RX (2015) Quality control using a multivariate injection molding sensor. Int J Adv Manuf Technol 78:1381–1391
5. Huang M-S (2007) Cavity pressure based grey prediction of the filling-to-packing switchover point for injection molding. J Mater Process Technol 183:419–424
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