Understanding Factorial Designs

2014 ◽  
pp. 100-123
Keyword(s):  
Factorial Designs

Identification of effects and confounding patterns in factorial designs

Biometrika ◽  
1977 ◽  
Vol 64 (2) ◽  
pp. 347-354 ◽  
Author(s):  
R. A. BAILEY ◽  
F. H. L. GILCHRIST ◽  
H. D. PATTERSON
Keyword(s):  
Factorial Designs

scholarly journals Auto-correlation robustness of factorial designs and GAMS in studying the effects of process variables in a dual-objective adsorption system

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Mutiu Kolade Amosa ◽  
Fatai A. Aderibigbe ◽  
Adewale George Adeniyi ◽  
Joshua O. Ighalo ◽  
Bisola Taibat Bello ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Factorial Design ◽  
Contact Time ◽  
Factorial Designs ◽  
Adsorption System ◽  
Process Variables ◽  
Operating Variables ◽  
Auto Correlation ◽  
General Algebraic Modeling System ◽  
Combined Models

AbstractThe performance of factorial designs is still limited due to some uncertainties that usually intensify process complexities, hence, the need for inter-platform auto-correlation analyses. In this study, the auto-correlation capabilities of factorial designs and General Algebraic Modeling System (GAMS) on the effects of some pertinent operating variables in wastewater treatment were compared. Individual and combined models were implemented in GAMS and solved with the trio of BARON, CPLEX and IPOPT solvers. It is revealed that adsorbent dosage had the highest effect on the process. It contributed the most effect toward obtaining the minimum silica and TDS contents of 13 mg/L and 814 mg/L, and 13.6 mg/L and 815 mg/L from factorial design and GAMS platforms, respectively. This indicates a concurrence between the results from the two platforms with percentage errors of 4.4% and 0.2% for silica and TDS, respectively. The effects of the mixing speed and contact time are negligible.

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