Data Mining-Enabled Temperature Control for Sustainable Production in Rubber Extrusion Lines: An Artificial Neural Network-Based Approach-Reference-Cited by-同舟云学术

Data Mining-Enabled Temperature Control for Sustainable Production in Rubber Extrusion Lines: An Artificial Neural Network-Based Approach

Published:2023-11-18 Issue: Volume: Page:539-549
ISSN:2194-0525
Container-title:Lecture Notes in Production Engineering
language:
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Author:

Lukas M.,Leineweber S.,Reitz B.,Overmeyer L.,Aschemann A.,Klie B.,Giese U.

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-47394-4_52

Reference24 articles.

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2. Du, Z., et al.: Effects of mixing temperature on the extrusion rheological behaviors of rubber-based compounds. RSC Adv. 11(56), 35703–35710 (2021)

3. Warren-Thomas, E., Dolman, P.M., Edwards, D.P.: Increasing demand for natural rubber necessitates a robust sustainability initiative to mitigate impacts on tropical biodiversity. Conserv. Lett. 8(4), 230–241 (2015)

4. Ghaffarian, N., Hamedi, M.: Optimization of rubber compound design process using artificial neural network and genetic algorithm. Int. J. Eng. 33, 2319–2326 (2020)

5. Park, K., Park, H., Bae, H.: A data-driven recipe simulation for synthetic rubber production. IEEE Access 10, 129408–129418 (2022)

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1. MINIMIZING TEMPERATURE DEVIATIONS IN RUBBER MIXING PROCESS BY USING ARTIFICIAL NEURAL NETWORKS;Rubber Chemistry and Technology;2024-09-01

2. Real-time temperature control in rubber extrusion lines: a neural network approach;The International Journal of Advanced Manufacturing Technology;2024-07-02