Model-based scanner tuning for process optimization

2009 ◽  
Author(s):  
Tsung-Chih Chien ◽  
C. Y. Shih ◽  
R. C. Peng ◽  
H. H. Liu ◽  
Y. C. Chen ◽  
...  
Keyword(s):  
Process Optimization ◽  
Model Based

Model based process optimization of nanosuspension preparation via wet stirred media milling

2018 ◽  
Vol 331 ◽  
pp. 146-154 ◽  
Author(s):  
Frederik Flach ◽  
Sandra Breitung-Faes ◽  
Arno Kwade
Keyword(s):  
Process Optimization ◽  
Model Based ◽  
Media Milling

Model-Based Process Optimization Supports the Synthesis of Pharmaceutically Relevant Nucleoside Derivatives

2016 ◽  
Vol 88 (9) ◽  
pp. 1245-1245
Author(s):  
M. N. Cruz Bournazoua ◽  
M. Gruber ◽  
S. Kamel ◽  
R. Giessman ◽  
A. Wagner ◽  
...  
Keyword(s):  
Process Optimization ◽  
Model Based

Economic modelling and model-based process optimization of membrane distillation

Desalination ◽  
2018 ◽  
Vol 436 ◽  
pp. 125-143 ◽  
Author(s):  
I. Hitsov ◽  
K. De Sitter ◽  
C. Dotremont ◽  
I. Nopens
Keyword(s):  
Process Optimization ◽  
Membrane Distillation ◽  
Economic Modelling ◽  
Model Based

Model-based scanner tuning for process optimization

2011 ◽  
Author(s):  
Rafael Aldana ◽  
Venu Vellanki ◽  
Wenjin Shao ◽  
Ronald Goossens ◽  
Zongchang Yu ◽  
...  
Keyword(s):  
Process Optimization ◽  
Model Based

Fast etch recipe creation with automated model-based process optimization

2021 ◽  
Author(s):  
Yang Ban ◽  
Kara Kearney ◽  
Bryan Sundahl ◽  
Leandro Medina ◽  
Roger T. Bonnecaze ◽  
...  
Keyword(s):  
Process Optimization ◽  
Model Based

An Intelligent Decision Model for Spinning Process Optimization

2012 ◽  
Vol 538-541 ◽  
pp. 439-443
Author(s):  
Zhi Jun Lv ◽  
Qian Xiang ◽  
Jian Guo Yang
Keyword(s):  
Process Optimization ◽  
Decision Model ◽  
Industrial Process ◽  
Model Based ◽  
Large Numbers ◽  
Intelligent Decision ◽  
Yarn Properties ◽  
Spinning Process ◽  
Yarn Production ◽  
Intelligent Model

The yarn production is a complex industrial process, and the relation between the spinning variables and the yarn properties has not been established conclusively so far. In fact, the existing process cases which were recorded to ensure the ability to trace production steps can also be used to optimize the process itself. This paper presents a novel process decision model based on CBR and SVM hybird intelligence for optimization of large numbers of spnning parameters. The applied cases are demonstrated that the intelligent model to optimizing the spinning process is promising.

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