Approaches to Identify Relevant Process Variables in Injection Moulding using Beta Regression and SVM-Reference-Cited by-同舟云学术

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Approaches to Identify Relevant Process Variables in Injection Moulding using Beta Regression and SVM

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 8th International Conference on Data Science, Technology and Applications
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Author:

Tripathi Shailesh¹,Strasser Sonja¹,Mittermayr Christian²,Dehmer Matthias¹,Jodlbauer Herbert¹

Affiliation:

1. Production and Operations Management, University of Applied Sciences Upper Austria, Wehrgrabengasse 1-3, Steyr and Austria, --- Select a Country ---

2. Greiner Packaging International GmbH, Greinerstrasse 70, 4550 Kremsmuenster and Austria, --- Select a Country ---

Publisher

SCITEPRESS - Science and Technology Publications

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhance the Injection Molding Quality Prediction with Artificial Intelligence to Reach Zero-Defect Manufacturing;Processes;2022-12-27

2. Identifying key interactions between process variables of different material categories using mutual information-based network inference method;Procedia Computer Science;2022

3. Machine Learning Methods for Quality Prediction in Thermoplastics Injection Molding;2021 International Conference on Electrical, Computer and Energy Technologies (ICECET);2021-12-09

4. Large scale predictability analysis of process variables from injection molding machines;Procedia Computer Science;2021

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