Artificial neural networks to model formulation-property correlations in the process of inline-compounding on an injection moulding machine | Zendy

Elmar Moritzer | Zendy; Ellen Müller | Zendy; Yannick Martin | Zendy; Rainer Kleeschulte | Zendy

Open Access

Artificial neural networks to model formulation-property correlations in the process of inline-compounding on an injection moulding machine

Author(s) -

Elmar Moritzer,

Ellen Müller,

Yannick Martin,

Rainer Kleeschulte

Publication year - 2015

Publication title -

aip conference proceedings

Language(s) - English

Resource type - Conference proceedings

eISSN - 1551-7616

pISSN - 0094-243X

DOI - 10.1063/1.4918476

Subject(s) - compounding , injection moulding , workflow , process (computing) , computer science , flexibility (engineering) , new product development , software , artificial neural network , workbench , property (philosophy) , product (mathematics) , manufacturing engineering , process engineering , artificial intelligence , mechanical engineering , engineering , materials science , mathematics , visualization , philosophy , statistics , geometry , epistemology , marketing , database , business , composite material , programming language , operating system

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research