Statistical Multiobjective Optimization of Thiospinel CoNi2S4 Nanocrystal Synthesis via Design of Experiments

ACS Nano ◽  
2021 ◽  
Author(s):  
Emily M. Williamson ◽  
Bryce A. Tappan ◽  
Lucía Mora-Tamez ◽  
Gözde Barim ◽  
Richard L. Brutchey
Keyword(s):  
Multiobjective Optimization ◽  
Design Of Experiments ◽  
Nanocrystal Synthesis

scholarly journals Finite Elements Analysis and Multiobjective Optimization: A Way to Reduce Material and Manufacturing Cost

2012 ◽  
Vol 498 ◽  
pp. 109-114
Author(s):  
S. Sánchez-Caballero ◽  
M.A. Sellés ◽  
R. Plá-Ferrando Caballero ◽  
J. Seguí
Keyword(s):  
Finite Elements ◽  
Multiobjective Optimization ◽  
Design Of Experiments ◽  
Weight Reduction ◽  
Maximum Stress ◽  
Manufacturing Cost ◽  
Allowable Stress ◽  
Finite Elements Analysis ◽  
Stress And Deformation ◽  
Ansys Workbench

The aim of this paper is to introduce a method to reduce the weight in structures which are subjected to multiple restrictions like deformation, max allowable stress, natural frequency, etc. The method is shown through the analysis of an aluminum bracket, whose maximum stress and deformation is well defined. The analysis is done using the Structural and Design of Experiments modules of Ansys Workbench v12.1. As result of the method a weight reduction of 50,2% is achieved.

scholarly journals Optimal Design of Laboratory and Pilot-plant Experiments using Multiobjective Optimization

2021 ◽  
Author(s):  
Esther Forte ◽  
Erik von Harbou ◽  
Jakob Burger ◽  
Norbert Asprion ◽  
Michael Bortz
Keyword(s):  
Experimental Design ◽  
Optimal Design ◽  
Multiobjective Optimization ◽  
Design Of Experiments ◽  
Pilot Plant ◽  
Pareto Frontier ◽  
Trade Offs ◽  
Interesting Part ◽  
Conflicting Objectives ◽  
Statistical Approaches

Performing an experimental design prior to the collection of data is in most circumstances important to ensure efficiency. The focus of this work is the combination of model‐based and statistical approaches to optimal design of experiments. The knowledge encoded in the model is used to identify the most interesting range for the experiments via a Pareto optimization of the most important conflicting objectives. Analysis of the trade‐offs found is in itself useful to design an experimental plan. This can be complemented using a factorial design in the most interesting part of the Pareto frontier.

scholarly journals Optimal Design of Laboratory and Pilot-plant Experiments using Multiobjective Optimization

2018 ◽  
Author(s):  
Ester Forte ◽  
Erik von Harbou ◽  
Jakob Burger ◽  
Michael Bortz ◽  
Norbert Asprion
Keyword(s):  
Experimental Design ◽  
Optimal Design ◽  
Multiobjective Optimization ◽  
Design Of Experiments ◽  
Pilot Plant ◽  
Pareto Frontier ◽  
Trade Offs ◽  
Interesting Part ◽  
Conflicting Objectives ◽  
Statistical Approaches

Performing an experimental design prior to the collection of data is in most circumstances important to ensure efficiency. The focus of this work is the combination of model‐based and statistical approaches to optimal design of experiments. The knowledge encoded in the model is used to identify the most interesting range for the experiments via a Pareto optimization of the most important conflicting objectives. Analysis of the trade‐offs found is in itself useful to design an experimental plan. This can be complemented using a factorial design in the most interesting part of the Pareto frontier.

Development of robust interconnect model based on design of experiments and multiobjective optimization

2001 ◽  
Vol 48 (9) ◽  
pp. 1885-1891 ◽  
Author(s):  
Qiang Zhang ◽  
J.J. Liou ◽  
J. McMacken ◽  
J. Thomson ◽  
P. Layman
Keyword(s):  
Multiobjective Optimization ◽  
Design Of Experiments ◽  
Model Based

Projektowanie dla jakości metodami Shainina i Taguchiego

2008 ◽  
pp. 36-38
Author(s):  
Jarosław Sęp ◽  
Andrzej Pacana
Keyword(s):  
Design Of Experiments

Zespół metod wykorzystywanych do planowania eksperymentów określa się jako Design of Experiments -DOE. Celem stosowania DOE jest uzyskanie jak największej ilości wartościowych i wiarygodnych informacji o badanym wyrobie lub procesie na podstawie jak najmniejszej liczby doświadczeń. W artykule zwrócono uwagę na stosunkowo mało znane metody opracowane przez Shainina oraz Taguchiego. Przedstawiono dobór parametrów metodą Shainina i Taguchiego na przykładzie procesu toczenia.

Defect Reduction in Ring Blank Casting Through Design of Experiments

2015 ◽  
Vol 9 (6) ◽  
pp. 536 ◽  
Author(s):  
P. Kannan ◽  
K. Balasubramanian ◽  
R. Vinayagamoorthy
Keyword(s):  
Design Of Experiments ◽  
Defect Reduction ◽  
Ring Blank
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