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pro vyhledávání: '"Richárd Dominik Párizs"'
Autor:
Richárd Dominik Párizs, Dániel Török
Publikováno v:
Results in Engineering, Vol 23, Iss , Pp 102667- (2024)
Searching for the optimal injection molding settings for a new product usually requires much time and money. This article proposes a new method that uses reinforcement learning with prior knowledge for the optimization of settings. This method uses a
Externí odkaz:
https://doaj.org/article/b11c54960512416cafbf7389dfd7ce72
Publikováno v:
Polymer Testing, Vol 117, Iss , Pp 107837- (2023)
In this paper, we created a general mathematical equation for the cushion curves of polymeric foams, using the measurement results of drop weight impact tests on commercially available, closed-cell ethylene-vinyl acetate and cross-linked polyethylene
Externí odkaz:
https://doaj.org/article/97d9535e4f4849f5a0e0bce6bc9317b6
Publikováno v:
Sensors, Vol 23, Iss 3, p 1735 (2023)
The simultaneous improvement of injection molding process efficiency and product quality, as required by Industry 4.0, is a complex, non-trivial task that requires a comprehensive approach, which involves a combination of sensoring and information te
Externí odkaz:
https://doaj.org/article/67d077e5f1bc44f99adfca73060d0ec3
Publikováno v:
Sensors, Vol 22, Iss 7, p 2704 (2022)
One of the essential requirements of injection molding is to ensure the stable quality of the parts produced. However, numerous processing conditions, which are often interrelated in quite a complex way, make this challenging. Machine learning (ML) a
Externí odkaz:
https://doaj.org/article/11f26ba5fd9f482fa6a6888bef4b039b