Application Of Fractional Factorial Design Research Articles

Application of fractional factorial design for evaluating the separation performance of the screening machine

ABSTRACT Implementing the planned execution of experiments will optimize the resources and time of a newly developed process or equipment. In the present work, the screening machine is newly developed equipment designed for the separation of coal. The present work was carried out to evaluate the performance of separation efficiency of the screening machine using generalized and forward selection fractional factorial experimental design. Further, the present work will also determine the significance of each operational variable, such as moisture content, angle, and frequency, for increasing separation efficiency. A cube plot was developed from the experimental design, which shows the highest and lowest condition of separation efficiency for each level of the operational variables. Further, a Pareto chart was developed to evaluate the significant operational variable for the screening machine. The results of the generalized method and forward selection method of fractional design show that the moisture content was the most significant operational variable, followed by angle and frequency. The results also show that the screen blinding of a screening machine plays an important role in reducing the separation efficiency of a screening machine.

Application of chemometrics into simultaneous monitoring removal efficiency of two food dyes by an amine-functionalized metal–organic framework

In this study, amine-functionalized of Fe-MIL-101 (NH2-Fe-MIL-101) was synthesized by the solvothermal method and applied for the removal of two food dyes amaranth (AM) and sunset yellow (SU). Due to the overlap of absorption peaks of these two dyes, it is impossible to measure and simultaneous monitor adsorption process of dyes. The principal component regression was assisted in overcoming this problem. To find significant parameters that can potentially influence the adsorption process, a fractional factorial design (26-1) was applied. To optimize the significant factors, the response surface methodology was implemented based on Box–Behnken design. The independent variables of sorbent dose (8–20 mg), solution pH (2–10), initial concentration (20–40 mg L−1) of dyes, and contact time (10–30 min) were considered in this study. The optimal conditions for each variable were achieved by the desirability function approach. The conditions were obtained as follows: adsorbent dosages (14 mg), pH (2), initial concentration (40 mg L−1), and contact time (30 min). Isotherm models of Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich were also studied. Under optimal conditions, the maximum adsorption capacities obtained were 131 and 116 mg g−1 for AM and SU, respectively. (a) There is a strong overlap between the absorption peaks of the two dyes. (b) Application of multivariate calibration method to overcome this problem and modeling with principal component regression (PCR). (c) The graph of the prediction against the actual values after modeling with PCR. (d) Preparation and application of NH2-Fe-MIL-101 for simultaneous adsorption of two food dyes. (e) Application of fractional factorial design to identify significant factors. (f) Optimization of significant factors with response surface methodology (RSM).

A Consistent Procedure Using Response Surface Methodology to Identify Stiffness Properties of Connections in Machine Tools.

Accurate finite element models of mechanical systems are fundamental resources to perform structural analyses at the design stage. However, uncertainties in material properties, boundary conditions, or connections give rise to discrepancies between the real and predicted dynamic characteristics. Therefore, it is necessary to improve these models in order to achieve a better fit. This paper presents a systematic three-step procedure to update the finite element (FE) models of machine tools with numerous uncertainties in connections, which integrates statistical, numerical, and experimental techniques. The first step is the gradual application of fractional factorial designs, followed by an analysis of the variance to determine the significant variables that affect each dynamic response. Then, quadratic response surface meta-models, including only significant terms, which relate the design parameters to the modal responses are obtained. Finally, the values of the updated design variables are identified using the previous regression equations and experimental modal data. This work demonstrates that the integrated procedure gives rise to FE models whose dynamic responses closely agree with the experimental measurements, despite the large number of uncertainties, and at an acceptable computational cost.

Application of fractional factorial design for green synthesis of cyano-modified silica nanoparticles: Chemometrics and multifarious response optimization

Cyano-functionalized spherical silica nanoparticles (SNPs) were synthesized via Stöber method. A 2 k-pIV–fractional factorial design (2k-pIV–FFD) was used to smartly prepare monodispersed evenly distributed SNPs. Six factors were considered; concentrations of tetraethylorthosilicate (TEOS), 3-Cyanopropyltriethoxysilane (CPTS), water, and ammonia, reaction time (RT) and stirring time (ST). Two responses; particle size (PS, measured by SEM) and particle-size distribution (PSD, calculated as standard deviation, ±SD) were measured. Control charts were used to decide on impacts of linear and two-way interactions on both responses. Derringer’s function was used to consolidate these multifarious responses into a uniform execution characteristic. Both screening and optimization were always accompanied by ANOVA testing at a 95.0% confidence interval (CI). The ideal synthetic conditions were obtained from the composite desirability plots. Cyano-functionalized SNPs with an average PS of 474.04 ± 86.71 nm were produced. Raman spectroscopy and FTIR were used to confirm the functionalization process. Thermogravimetric analysis (TGA) was used to evaluate the thermal behavior of synthesized particles.

Application of fractional factorial design to improve hot smoked Nile Perch (Lates niloticus) quality

Application of fractional factorial design to improve hot smoked Nile Perch (Lates niloticus) quality

An application of fractional factorial design in wire electrochemical turning process

Design of experiment (DOE) is a structured, organized method for determining the significant and insignificant factors as well as the relationship between the different input factors affecting the outputs of a process. DOE involves designing a set of experiments, in which all relevant factors are varied systematically. One of the most important methods of DOE is fractional factorial design. Fractional factorial design sacrifices interaction effects so that main effects may still be computed correctly. This paper proposes an application of fractional factorial design to execute the experimental procedures, to determine the significant and insignificant factors, and finally, to investigate a reliable mathematical model for maximizing the metal removal rate in the one of the nontraditional machining processes. Nontraditional machining processes have the ability to machine the highly alloyed materials with a fine surface finish and high-dimensional accuracy. To provide a realistic environment for applying the fractional factorial design, wire electrochemical turning (WECT) process is adopted as a test bed.

Application of fractional factorial designs to study drug combinations

Herpes simplex virus type 1 (HSV-1) is known to cause diseases of various severities. There is increasing interest to find drug combinations to treat HSV-1 by reducing drug resistance and cytotoxicity. Drug combinations offer potentially higher efficacy and lower individual drug dosage. In this paper, we report a new application of fractional factorial designs to investigate a biological system with HSV-1 and six antiviral drugs, namely, interferon alpha, interferon beta, interferon gamma, ribavirin, acyclovir, and tumor necrosis factor alpha. We show how the sequential use of two-level and three-level fractional factorial designs can screen for important drugs and drug interactions, as well as determine potential optimal drug dosages through the use of contour plots. Our initial experiment using a two-level fractional factorial design suggests that there is model inadequacy and that drug dosages should be reduced. A follow-up experiment using a blocked three-level fractional factorial design indicates that tumor necrosis factor alpha has little effect and that HSV-1 infection can be suppressed effectively by using the right combination of the other five antiviral drugs. These observations have practical implications in the understanding of antiviral drug mechanism that can result in better design of antiviral drug therapy.

Application of fractional factorial design to ZSM-5 synthesis using ethanol as template

A 2 IV 4 - 1 fractional factorial design of experiments was applied to synthesis of ZSM-5 zeolite using ethanol as template. With only 16 experiments, two runs for each of the eight experiments, the following results were obtained in this study. Analysis of variance showed that the most important main effect was SiO 2/Al 2O 3 molar ratio, and the most important two-way interaction variable was the interaction of H 2O/SiO 2 and SiO 2/Al 2O 3 molar ratio. A mathematical model for ZSM-5 synthesis was derived from the experimental data and validated by residual plot analysis. An optimum gel composition, H 2O/SiO 2 = 40, SiO 2/Al 2O 3 = 60, OH −/SiO 2 = 0.15 and C 2H 5OH/SiO 2 = 1.5, was found from surface plots.

Application of fractional factorial design for improving performance of 60W transverse flux linear motor

This paper presents an optimum design procedure of permanent-magnet-type 60W transverse flux linear motor to reduce the weight of the machines with the constraints of thrust and detent forces using fractional factorial design and response surface methodology (RSM). RSM is well adapted to make the analytical model of minimum weight with constraints of thrust and detent forces, and it enables objective functions to be easily created, and a great deal of computation time can be saved. Therefore, the usefulness of this method is verified through the comparison of the performances of the optimal model and those of the initial model.

Application of Fractional Factorial Design and Doehlert Matrix in the Optimization of Experimental Variables Associated with the Ultrasonic-Assisted Acid Digestion of Chocolate Samples for Aluminum Determination by Atomic Absorption Spectrometry

A simple and rapid method based on ultrasound energy is described for the determination of aluminum (AI) in complex matrixes of chocolate and candy samples by electrothermal atomic absorption spectrometry. The optimization strategy was carried out using multivariate methodologies. Five variables (temperature of the ultrasonic bath; exposure time to ultrasound energy; volumes of 2 acid mixtures, HNO3-H2SO4-H2O2 (1 + 1 + 1) and HNO3-H2O2 (1 + 1); and sample mass) were considered as factors in the optimization process. Interactions between analytical factors and their optimal levels were investigated using fractional factorial and Doehlert matrix designs. Validation of the ultrasonic-assisted acid digestion procedure was performed against standard reference materials, milk powder (SRM 8435) and wheat flour (SRM 1567a). The proposed procedure allowed Al determination with a detection limit of 2.3 microg/L (signal-to-noise = 3) and a precision, calculated as relative standard deviation, of 2.2% for a set of 10 measurements of certified samples. The recovery of Al by the proposed procedure was close to 100%, and no significant difference at the 95% confidence level was found between determined and certified values of Al. The proposed procedure was applied to the determination of Al in chocolate and candy samples. The results indicated that cocoa-based chocolates have higher contents of Al than milk- and sugar-based chocolates and candies.

Application of Fractional Factorial Design for the Development of Production Media for the Pikromycin Macrolide Family by Streptomyces venezuelae

Application of Fractional Factorial Design for the Development of Production Media for the Pikromycin Macrolide Family by Streptomyces venezuelae

Application of fractional factorial design to levan production by Zymomonas mobilis

Levan is a non-toxic, biologically active, extra cellular polysaccharide composed solely by fructose units. Optimization of levan production by Zymomonas mobilis strain ZAG-12 employing a 24-1 fractional factorial design was performed to analyze the influence of the temperature (20, 25 e 30oC) agitation (50, 75 e 100 rpm), and the initial concentrations of both sucrose (150, 200 e 250 g.L-1) and yeast extract (2.0, 3.5 e 5.0g.L-1) on final levan concentration. Aerobic fermentation was performed batchwise in 500mL Pyrex flasks for 72 hours. Biomass, ethanol, levan and sucrose were determined at beginning and also at end of the fermentations. The experiments showed that the final levan concentration depended on initial sucrose concentration, temperature and agitation velocity and that the initial concentration of yeast extract did not influence levan production. However, when the production of ethanol and biomass were considered, it became evident that yeast extract was a significant variable. The best conditions for levan production occurred at 100 rpm agitation, 20oC and 250g.L-1 of initial sucrose resulting in 14.67g.L-1 of levan.

Application of Fractional Factorial Designs to Screen Active Factors for Antibody Production by Chinese Hamster Ovary Cells

With ever increasing need for cost-effective large-scale production of monoclonal antibodies, it is essential to develop highly productive and commercially viable processes. Previous research showed that growth and production capacity of the culture media can be improved by micronutrient supplements, such as insulin, vitamins, and growth factors. Since these micronutrients may not act independently of one another, factorial designs can expose critical interactions between nutrients as opposed to a serial approach of changing one factor at a time. In this study, fractional factorial designs were applied to observe the effect of several micronutrients on antibody production and culture longevity in shake flasks. Response surface designs were used to investigate the factors in depth and confirm the results of the fractional factorial study. The results demonstrate that fractional factorial design is an effective tool for rapid development of antibody-producing Chinese hamster ovary (CHO) cells.

Fractional factorial design of screening experiments on cryopreservation of fish sperm

Milt of grass carp Ctenopharyngodon idella (Val.) and goldfish Carassius auratus auratus (L.) was cryopreserved in experiments following &Hf1 2 and &Hf1 4 fractional factorial designs. The efficiency of a graphical method and manova was tested, as well as the informative strength of both designs. Fractional factorial design was very suitable for screening experiments, and it allowed separation of important and unimportant effects. A graphical method showed the same efficiency and reliability as manova. The &Hf1 4 fractional factorial design was less informative than the &Hf1 2 fractional factorial design, because it did not allow an estimation of the interactions. The application of fractional factorial designs for multifactorial screening experiments on cryopreservation of fish sperm has been implemented in this study.