Application of Response Surface Methodology to systematically optimize image quality in computer tomography: A case study using fresh chestnuts (Castanea spp.)

2012 ◽  
Vol 87 ◽  
pp. 94-107 ◽  
Author(s):  
Irwin R. Donis-González ◽  
Daniel E. Guyer ◽  
Anthony Pease
Keyword(s):  
Response Surface Methodology ◽  
Image Quality ◽  
Response Surface ◽  
Computer Tomography

scholarly journals Optimization of chlorite and talc flotation using experimental design methodology: Case study of the MCG plant, Morocco

2020 ◽  
Vol 120 (12) ◽  
Author(s):  
K. Boujounoui ◽  
A. Abidi ◽  
A. Baçaoui ◽  
K. El Amari ◽  
A. Yaacoubi
Keyword(s):  
Response Surface Methodology ◽  
Central Composite Design ◽  
Response Surface ◽  
Desirability Functions ◽  
Sulphide Ore ◽  
Experimental Values ◽  
Experimental Design Methodology ◽  
Central Composite ◽  
Good Agreement

SYNOPSIS Response surface methodology (RSM), central composite design (CCD), and desirability functions were used for modelling and optimization of the operating factors in chlorite and talc (collectively termed 'mica') flotation. The influence of pulp pH, cyanide (NaCN) consumption, and particle size was studied with the aim of optimizing ssilicate flotation while minimizing recoveries of galena, chalcopyrite, and sphalerite. Flotation tests were carried out on a representative sample of a complex sulphide ore from Draa Sfar mine (Morocco). The model predictions for the flotation of each of the minerals concerned were found to be in good agreement with experimental values, with R2 values of 0.91, 0.98, 0.99, and 0.90 for mica, galena, chalcopyrite, and sphalerite recoveries, respectively. RSM combined with desirability functions and CCD was successfully applied for the modelling of mica flotation, considering simultaneously the four flotation responses to achieve the maximum recovery of mica and minimal loss of Pb, Cu, and Zn to the flotation concentrate. Keywords: chlorite, talc, flotation, response surface methodology, central composite design, optimization.

scholarly journals Response Surface Methodology Applied to the Optimization of Phenolic Compound Extraction from Brassica

2021 ◽  
Author(s):  
Valentin Reungoat ◽  
Morad Chadni ◽  
Irina Ioannou
Keyword(s):  
Response Surface Methodology ◽  
Phenolic Compounds ◽  
Response Surface ◽  
Phenolic Compound ◽  
Process Optimization ◽  
Prediction Models ◽  
State Of The Art ◽  
Process Engineering ◽  
Statistical Tool

The response surface methodology (RSM) is a relevant mathematical and statistical tool for process optimization. A state of the art on the optimization of the extraction of phenolic compounds from Brassica has shown that this approach is not sufficiently used. The reason for this is certainly an apparent complexity in comparison with the implementation of a one-factor-at-a-time (OFAT) optimization. The objective of this chapter is to show how one implement the response surface methodology in a didactic way on a case study: the extraction of sinapine from mustard bran. Using this approach, prediction models have been developed and validated to predict the sinapine content extracted as well as the purity of the extract in sinapine. The methodology presented in this chapter can be reproduced on any other application in the field of process engineering.

scholarly journals A Case Study for Finding an Efficient M&S Meta Model through Sequential Response Surface Methodology

2012 ◽  
Vol 40 (1) ◽  
pp. 49-59 ◽  
Author(s):  
Sang-Ik Kim ◽  
Yong-Dai Kim ◽  
Yong-Bin Lim ◽  
Ki-Heon Choi ◽  
Jeong-Eun Kim
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Meta Model

Comparative Study on Design of Experiment in Frequency-Based Response Surface Methodology for Damage Detection

2015 ◽  
Vol 735 ◽  
pp. 168-173 ◽  
Author(s):  
Sarehati Umar ◽  
Norhisham Bakhary ◽  
Airil Yasreen Mohd Yassin
Keyword(s):  
Response Surface Methodology ◽  
Damage Detection ◽  
Response Surface ◽  
Design Of Experiment ◽  
Model Updating ◽  
Quadratic Functions ◽  
Modal Frequency ◽  
Simply Supported ◽  
Central Composite

This paper investigates the performance of design of experiment (DOE) in response surface methodology (RSM) for vibration-based damage detection. The ability of three major types of DOE, namely central composite design (CCD), Box-Behnken (BBD) and D-optimal (Dopt) for damage detection based on modal frequency are investigated and compared. A procedure comprising three main stages—sampling, response surface (RS) modelling and model updating—are employed for damage localisation and quantification. By considering Young’s modulus and modal frequency as respective input and output, a set of samples is generated from each DOE. Full quadratic functions are considered in RS modelling while model updating is performed for damage detection. The performances of DOE are compared based on damage detectability. A numerical simply supported beam is used as case study by considering several single damage cases. The results show that CCD provides better prediction compared to other DOEs.

Sign in / Sign up

Export Citation Format

Share Document