Factorial Design Technique Research Articles

Modeling biosorption of Cr(VI) onto Ulva compressa L. from aqueous solutions.

The marine biomass Ulva compressa L. (ECL) was used as a low-cost biosorbent for the removal of Cr(VI) from contaminated aqueous solutions. The operating variables were optimized: pH ∼ 2, initial concentration of 25 mg/L, solid/liquid ratio of 6 g/L and a temperature of 50 °C, leading to an uptake elimination of 96%. A full factorial experimental design technique enabled us to obtain a mathematical model describing the Cr(VI) biosorption and to study the main effects and interactions among operational parameters. The equilibrium isotherm was analyzed by the Langmuir, Freundlich and Dubinin-Radushkevich (D-R) models; it has been found that the adsorption process follows well the Langmuir model. Kinetic studies showed that the pseudo-second order model describes suitably the experimental data. The thermodynamic parameters indicated an endothermic heat and a spontaneity of the Cr(VI) biosorption onto ECL.

PCL/PLA Polymer Composite Filament Fabrication using Full Factorial Design (DOE) for Fused Deposition Modelling

In this study, Polycaprolactone / Polylactice Acid (PCL/PLA) composite are used to fabricate filament wire with the specific diameter, which is in the range of 1.75 to 1.80 mm. Full factorial experimental design technique was used to study the main effects and the interaction effects between operational parameter which is (A) die temperature, (B) roller puller speed, (C) spindle speed and (D) inlet temperature. Besides that, there are two levels (-1 and +1) and the response are filament wire diameter. There are 16 numbers of runs and plus 8 centre points per blocks which makes the runs into 24 runs. From the experiment it shows that there are four factor that are significant effects on the filament wire diameter which is A, B, C and BC. The optimum parameter setting are also determined and there are 10 suggestions to achieve the target with different setting of parameter. The margin error for confirmation run is below than 15% when the parameter set at 6 Hz spindle speed, 4.99 rpm roller puller, 100.31 °C die temperature and 79.65 °C inlet temperature which can be noted that the confirmation run result is acceptable. The optimization parameter setting can use to continue in Fused Deposition Modelling (FDM). Filament wire from PCL/PLA are succesfully fabricated with acceptable diameter size and ready to be used for Fused Depotion Modelling process (FDM).

Reduction-melting extraction of trace elements from hazardous waste glass from an old glasswork\u2019s dump in the southeastern part of Sweden

At the southeastern part of Sweden, old art and crystal waste glass has been identified as a hazardous waste due to high weight concentrations of Pb (32.398%), Cd (0.085%), and As (1.976%). The reduction-melting technique was used to investigate the extraction of these trace elements from powder waste glass of particle size < 1 mm. Following a factorial design technique, the experimental results of the reduction-melting method showed that 99.9% of Pb, 100% of Cd, and 99% of As could be extracted. For a batch of 10 g powder waste glass, the found experimental and theoretical optimum operating conditions were 1100 °C of melting temperature, 5 g of Na2CO3, 2 g of carbon, and 120 min of melting time. The reduction-melting method displayed promising results which might help in recycling the extracted trace elements and glass compared to the current used solution of landfilling as hazardous wastes.

Regression Model and Optimization of Magnetic Abrasive Finishing of Flat Brass Plate

Magnetic abrasive machining is a surface finishing process in which a magnetic field is utilized to force abrasive particles against the work piece surface to remove the material as microchips. The aim of the present examination work is to investigate the effect of boron carbide abrasives on surface finishing and material removal rate of flat brass plate using magnetic abrasive finishing process. Four input parameters are taken in this research work which is rotational speed, quantity of magnetic abrasives, mesh number and machining time. Full factorial experimental design technique was used to investigate the effect of the input factors on the surface roughness and material removal rate. The analysis of variance (ANOVA) was investigated using statistical software to find optimal conditions for better surface roughness and material removal rate. Regression models have been developed by using MINITAB-17 statistical software for both surface roughness and material removal rate. Experimental results showed that rotational speed is the most important parameters on change in surface roughness and machining time for change in MRR. Minimum surface roughness (Ra) achieved 0.061μm and maximum material removal rate (MRR) 3mg/min.

Residential Neighbourhoods, Perceived Social Support and Subjective Wellbeing

Research on subjective wellbeing has mainly focused on personality and demographic variables. The influence of residential neighbourhoods are usually not considered. This study, investigates the influence of types of neighbourhoods and perceived social support on life satisfaction among residents in Ibadan metropolis. Using a 2-way factorial design and multistage sampling technique, five of the eleven Local Government Areas (LGAs) in the metropolis were purposively selected for the study. Ten enumeration areas were selected from each LGA using simple random technique. The number of participants in the selected enumeration areas were determined using enumeration area maps. Two hundred and twenty house-owners and renters each were then selected from the low, medium and high density areas of the LGAs using systematic technique, making a total of 1,100 participants. The selected household heads were sampled. A structured questionnaire focusing on socio-demographic profile, life satisfaction scale (r=0.74) and a multi-dimensional scale of perceived social support (r=0.87) was administered to the participants. Data were analyzed using descriptive statistics and analysis of variance at 0.05 level of significance. Three hypotheses were tested. The results reveal that social support did not have significant main influence on life satisfaction (F (1,237) =.04; p&gt;.05) while neighbourhood types significantly influenced life satisfaction (F (1,237) = 10.79; p&lt;.05). There were significant interaction effects of neighbourhood and social support on life satisfaction (F(1,237) = 4.15). The findings suggest that the places we live are important for improvement of our life satisfaction.

Experimental Investigation and Statistical Approach to Wear Characterization of Plasma Nitrided AISI 4140 Steel-A Case Study

&lt;p&gt;Components of forming tool dies such as draw ring, ejector pin use AISI 4140 as material for their manufacturing. The integrity of the die cutting tools is essential to achieve adequate product quality. In present study, the influence of plasma nitriding (PN) on the wear behav-iour of AISI 4140 steel was investigated. Full factorial experimental design technique was used to study the main effects and the interaction effects between operational parameters and the response variable. The control factors at their two levels (-1 and +1) were: applied load (4.905N and 14.715N), sliding speed (3.14 m/s and 5.23 m/s), and sliding distance (500m and 1000m).The parameters were coded as A, B, and C, consecutively, and were investigated at two levels (-1 and +1). Response selected was Wear Volume Loss (WVL). The effects of in-dividual variables and their interaction effects for dependent variables, namely, WVL were determined. The process of selecting significant factors, based on statistical tools, is illustrat-ed. Analysis of Variance (ANOVA) was performed to know the impact of individual factors on the WVL. Untreated and PN treated AISI 4140 specimens were investigated using field emission Scanning Electron Microscope (SEM) equipped with Energy Dispersive X-ray (EDX) analyzer. Finally diagnostics tools were used to check adequacy of the model in terms of assumptions of ANOVA. ‘Design Expert-7’ and ‘Minitab 17’ softwares were used in the study. Results of statistical analysis indicate that the most effective parameters in the WVL were load and sliding speed. The interaction between load and sliding speed was the most influencing interaction. Results of regression analysis indicate regression coefficient (R2) to be above 90% which suggests good predictability of the model. ‘Predicted-R2’ and ‘Adjusted-R2’, found to be in good agreement with R2, for both the materials under investigation. More-over, results of SEM microscopy suggest PN to be an effective technique to reduce wear.&lt;/p&gt;

TiO2/H2O2 mediated UV photocatalysis of Chlorpyrifos: Optimization of process parameters using response surface methodology

Chlorpyrifos (CP), an organophosphate pesticide which is used extensively in agricultural fields of various developing countries, is found to cause neurological and immunological effects on living beings. In this study, TiO2/H2O2 mediated UV photocatalytic oxidation of CP was investigated in a laboratory-scale photo-reactor. Experiments were designed using three level Box-Behnken factorial design (BBD) technique combined with response surface methodology (RSM). Effects of the process parameters such as concentration of TiO2, concentration of H2O2 and initial pH on the response parameters like degradation of chemical oxygen demand (COD) and degradation of CP were analyzed using polynomial regression models. After 3h reaction time, with the optimum process parameters, about 68.29% and 74.38% of COD degradation and CP degradation, respectively were achieved. Kinetic and synergistic studies for different oxidation systems viz., H2O2, UV+H2O2, UV+TiO2 and UV+TiO2+H2O2 were also performed using the optimum conditions. Statistical models developed in this study can be used for optimization of oxidation processes for treatment of industrial as well as agricultural wastewater.

Tribological behavior of alumina obtained by low-pressure injection molding using factorial design

This work presents a tribological study of ceramics parts produced by low-pressure injection molding (LPIM) using factorial design technique. An experimental design of 2k+n0 was used to define the experiments and evaluate the influence of three variables on friction coefficient, wear rate and wear mechanisms. The normal load (5N to 15N), tangential velocity (0.05ms−1 to 0.15ms−1) and counterbody type (with three contact pairs, alumina-alumina, alumina-silicon nitride and alumina-steel) were selected as the input variables. Discs of ceramic with ϕ20×3mm composed by 86wt% alumina (99.8 % Al2O3) and 14wt% organic vehicle were produced by LPIM process and sintered at 1600°C, and used as samples in tribological tests. Unidirectional sliding wear tests were conducted in unlubricated conditions at room temperature using a ball-on-disk tribometer. The statistical analysis indicated that the friction coefficient and the specific wear coefficient were strongly sensitive to the individually variations of velocity and the counterface type, and especially to the interaction between these factors. The wear behavior was analyzed as a function of contact parameter that considered the contact Hertz pressure, velocity and hardness of the materials in contact. The hardness and the chemical nature of the counterface were determinant in the reduction of friction coefficient and the severity of LPIM-alumina wear. It was identified also that the transfering of oxide films from the active counterfaces protected the LPIM-alumina from severe wear and reduced the coefficient of friction, wear rate and brittle fracture of the structural ceramic.

Influence Parameters on Nitriding Process of Ferromanganese Alloy

A 24 factorial design technique was used to investigate the magnitude effect of temperature, time, carbon percent, and pressure of the nitriding process of gas solid reaction of ferromanganese. The design was based on experiments results obtained from nitriding of two grades of ferromanganese alloys containing 0.23% C and 7.1% C at temperatures 700°C and 950°C, during time of 2 hours and 6 hours and with nitrogen pressure of 1 and 8 bar. The required calculations were carried out by Matlab. It was found that the highest positive effect was temperature while the carbon content has the highest negative effect. Nitrogen pressure has more positive effect than time. The interaction combination between two parameters or more of temperature, nitrogen pressure, and time has positive influence with different extent. The interaction combination between carbon and one or more of parameters of time, temperature, or nitrogen pressure has negative effect on nitriding process. The driven models were found to be in good agreement with the experiments and published work of nitriding process of ferromanganese containing different carbon contents (0.23–7.1%) in temperature range 700°C–950°C, with nitrogen pressure up to 8 bar, and during time of 2–6 hours.

The Impact of Interactive Environment and Metacognitive Support on Academic Achievement and Transactional Distance in Online Learning

The aim of the present study is to reveal the impact of the interactive environment and metacognitive support (MS) in online learning on academic achievement and transactional distance (TD). The study is designed as 2 × 2 factorial design, and both qualitative and quantitative research techniques are used. The study was carried out on 127 students, and this research design was implemented in an online learning environment and evaluated based on an achievement test, TD scale, and semistructured interviews. The results of the study revealed that synschronous environments had a significant impact in reducing TD perception. In asynschronous environments, on the other hand, providing students with MS was efficient in reducing TD. In terms of academic success, compared with synschronous environments, MS provided in asynschronous environments caused to a significant difference in achievement test scores of the students. Explanations about findings and implications for instructional design are discussed in Conclusion section.

The Use of Fractional Factorial Design for Atrium Fires Prediction

In order to mitigate the excessive computational cost of atrium fire simulations, a novel methodology based on the use of the Fractional Factorial Design technique to obtain an experimental validated tool, in the form of a surface response model, capable to predict fire induced conditions is proposed. This methodology is supported by results from a Design of Experiments benchmark, which consists of a set of FDS simulations in the present work. Specifically, a $$2^{6-2}_{IV}$$ approach has been considered and applied to a 20 m cubic atrium. Thus, six factors have been considered, namely the fire Heat Release Rate (HRR) and location, the exhaust flow rate, the exhaust location and activation time, and the inlet vents area. Furthermore, the smoke temperature at the roof and 15 m high and the smoke layer height have been considered the variables of interest. Subsequently, a multiple linear regression analysis has been performed to predict and compare the steady and non-steady temperature profiles and the smoke layer drop with six novel full-scale atrium fire tests, and also with specific adjusted FDS models. In addition, this methodology has been extended successfully to predict the non-steady behaviour of the fire tests. At the steady state, the HRR and the exhaust flow rate have been found to be the most relevant factors. The results obtained with the proposed methodology show a good fit both with the fire tests and with the adjusted FDS models, with discrepancies mostly below 14%. For non-steady conditions, a time analysis of the influence of the six factors has been carried out. Again, remarkable good agreement with the time-dependent experimental results is achieved, with average discrepancies below 12%, being the larger differences found in the prediction of local effects, such as the smoke ceiling jet, for high HRR or when the make-up air influence is significant. The results turn this methodology into a powerful and useful tool for fire safety designs.

Factorial Design Methodological Approach for Enhanced Cadmium Ions Bioremoval by Opuntia Biomass

The bioremoval efficiency of Opuntia biomass, a low‐cost biosorbent and renewable resource, for cadmium ions from aqueous solutions was investigated using factorial design methodology. The functional groups involved in the sorption process were identified by FTIR spectroscopy. A factorial experimental design technique, the full factorial design 33, has been used for enhanced cadmium ions bioremoval. Three factors were considered: protonation of the sorbent, initial cadmium concentration, and sorbent dosage at three markedly different levels. An empirical model was statistically developed using response surface methodology for its optimization. The model showed that cadmium ions bioremoval in aqueous solution was affected by all the three factors analyzed. The statistical model revealed a maximum sorption capacity (qe) of 58.4 mg/g with sorbent protonated with 0.67 M HCl, initial Cd(II) concentration of 50 mg/L, and 0.55 g/L of sorbent dosage. Bioremoval kinetic data were properly fitted by chemical sorption of pseudo‐second order. The Langmuir equation fits better the sorption isotherm (equilibrium data) than other classical models.

Material parameters design of vehicle body based on three-level factorial design under impact loading

ABSTRACTThis paper applied a method of screening active factors to material parameters selection under crashworthiness design criterion. The three-level unreplicated saturated factorial design technique was used to deal with factors screening of material parameters in the nonlinear dynamic system. Three types of experiment statistic methods were utilised to analyse the accuracy of all the analytical factors, named H statistic, P statistic and B statistic. Multiobjective crashworthiness optimisation platform was established with discrete variables of material parameters. Radial basis functions regression model was employed to get fitting curves of analytical objectives so as to reduce design sampling points and improve the design efficiency. NSGA-II served as the optimisation algorithm. Material parameters selection based on three-level unreplicated saturated factorial design extends the range of factor screening in the crashworthiness optimisation design of vehicle body. It not only breaks through the traditional design method of just selecting several experienced variables, but also shortens the design cycles of vehicle body.

Clavulanic acid separation on fixed bed columns of layered double hydroxides: Optimization of operating parameters using breakthrough curves

The adsorption of clavulanic acid (CA) in a fixed-bed column of layered double hydroxides (LDHME) was investigated. Breakthrough curves were obtained experimentally and the system was evaluated with regards to column operation time, efficiency and productivity as functions of simultaneous variations of superficial velocity (vz) and bed height (L) using a central composite rotatable design (CCRD). At the optimized condition (vz=1.00cm/min and L=6.5cm), the responses were: 46min, 146min, 100min and 13kg/hcm3, for breakthrough time (tb), exhaustion time (te), the difference te−tb and productivity (P), respectively. These results represent no change in tb, but a 50% decrease of te, 40% decrease of (te−tb) and 38% increase of P, which is advantageous for the process. The factorial design technique was shown to be an efficient tool for assessing factor influences and was effective in optimizing the column operating conditions. Good separation of CA from the amino acids tyrosine (TYR) and proline (PRO) was observed in fixed bed columns. The LDHME adsorbent was shown to be an excellent alternative for CA purification.

TiO2 modified carbon paste sensor for voltammetric analysis and chemometric optimization approach of amlodipine in commercial formulation

A new square wave adsorptive stripping voltammetric (SWAdSV) approach using experimental design and optimization methodology was developed for the quantitative estimation of amlodipine (AMP) in pharmaceutical tablets. To this end, a new carbon paste electrode (CPE) system was fabricated using titanium dioxide (TiO2) nanoparticles to get very well-defined oxidation peak current of AMP under the optimized conditions. Optimal electrochemical conditions for three factor variables, the pH, the accumulation potential, and the accumulation time, were obtained by applying a 33 full factorial design and optimization technique to the oxidation of AMP on the TiO2 modified CPE (TiO2-CPE) system. The numerical values of the optimal voltammetric parameters consisting of the pH, accumulation potential, and accumulation time were found to be 5.69, 562.30 mV, and 64.30 s for the analysis of AMP in samples, respectively. The newly developed voltammetric method for the determination of AMP offers a linear relationship between the peak current and concentration in the range of 1.0 × 10−8 − 1.0 × 10−6 M with the correlation coefficient (r = 0.9990) and the detection limit (LOD = 2.97 × 10−9 M). The lifetime of prepared electrode was also tested, and the current intensity of AMP was nearly stable at least 2 months by using TiO2-CPE. The validity of the method was tested by analyzing standard samples containing the analyzed compound. Under optimized and validated experimental conditions, the proposed method was successfully applied for the quantitative analysis of AMP in commercial tablets.

Optimization of the Atmospheric Plasma Spray Parameters using Design of Experiments for Coatings on AISI 410 Stainless Steel

ABSTRACTIn this work, the effect of three principal and independent parameters of Atmospheric Plasma Spray on the properties of coatings deposited using mixtures of commercial powders of titanium dioxide (TiO2) and chromium oxide (Cr2O3) was studied. The results of this work are used for special applications on turbomachinery components such as wear protection in sliding seals and in steam valves for turbines, chemical protection for centrifugal compressor members, and special seal applications.The design of experiments (DoE) technique has proved to be very useful to study the influence factors and optimization. Pierlot et al. [1] demonstrated that the application of the Hadamard and two factorial design techniques are useful for the optimization of thermal spray processes. An example of the application of the DoE is the one mentioned by Murugan et al. [2]. In their work, a factorial design was used to study the interactions between gas flow, oxygen flow, powder rate and spray distance on the percentage of porosity and hardness of TiO2- Cr2O3composite coatings generated by High Velocity Oxy-Fuel.The ½ fractional two-level factorial DoE technique was used to analyze and optimize the Atmospheric Plasma Spray process parameters. In the current research, experiments were conducted varying the deposition velocity, gas flow and stand-off distance. The effect of these process variables were evaluated by thickness, hardness and microstructure analysis. In this study, an empirical relationship between process variables and response parameters was developed. The entire relationship was made using the results of the DoE.

Characterization of Various Plant-Produced Asphalt Concrete Mixtures Using Dynamic Modulus Test

This research characterizes the performance of various plant-produced asphalt concrete mixtures by dynamic modulus|E∗|test using asphalt mixture performance tester (AMPT). Marshall designed specimens of seven different mixtures were prepared using the Superpave gyratory compactor and subjected to sinusoidal compressive loading at various temperatures (4.4 to 54.4°C) and loading frequencies (0.1 to 25 Hz). A catalog of default dynamic modulus values for typical asphalt concrete mixtures of Pakistan was established by developing stress-dependent master curves separately, for wearing and base course mixtures. The sensitivity of temperature and loading frequency on determination of dynamic modulus value was observed by typical isothermal and isochronal curves, respectively. Also, the effects of various variables on dynamic modulus were investigated using statistical technique of two-level factorial design of experiment. Furthermore, two dynamic modulus prediction models, namely, Witczak and Hirsch, were evaluated for their regional applicability. Results indicated that both the Witczak and Hirsch models mostly underpredict the value of dynamic modulus for the selected conditions/mixtures. The findings of this study are envisaged to facilitate the implementation of relatively new performance based mechanistic-empirical structural design and analysis approach.

Optimizing Cutting Conditions for Minimum Surface Roughness in Face Milling of High Strength Steel Using Carbide Inserts

A full factorial design technique is used to investigate the effect of machining parameters, namely, spindle speed(N), depth of cut(ap),and table feed rate(Vf),on the obtained surface roughness (RaandRt) during face milling operation of high strength steel. A second-order regression model was built using least squares method depending on the factorial design results to approximate a mathematical relationship between the surface roughness and the studied process parameters. Analysis of variance was conducted to estimate the significance of each factor and interaction with respect to the surface roughness. ForRa, the results show that spindle speed, depth of cut, and table feed rate have a significant effect on the surface roughness in both linear and quadratic terms. There is also an interaction between depth of cut and feed rate. It also appears that feed rate has the greatest effect on the data variation followed by depth of cut. ForRt, the results show that the table feed rate is the most effective factor followed by the depth of cut, while the spindle speed had a significant small effect only in its quadratic term. The conditions of minimumRaandRtare identified through least square optimization. Moreover, multiobjective optimization for minimizingRaand maximizing metal removal rateQis conducted and the results are presented.

Biodiesel production from Sterculia striata oil by ethyl transesterification method

Biodiesel is an alternative to fossil fuels. Its industrial production relies on vegetable oil transesterification with a short-chain with ethanol using sodium hydroxide (NaOH) as the catalyst. The growing demand for biofuels has motivated studies on new vegetable oil sources. Sterculia striata (Chicha) seeds are particularly interesting in this sense—their mass consists of about 40% oil, so it is possible to convert them into biodiesel in high yield. Hence, this manuscript aimed to investigate how process variables affect biodiesel production from chicha oil. Application of a factorial design technique aided analysis of four process variables: temperature (30–70°C), oil/alcohol molar ratio (1:6–1:10), catalyst amount (0.5–1.5% w/w), and reaction time (0.5–2.0h). The resulting biodiesel met most of the standard requirements; however, its density lay above the values established by the Brazilian petroleum agency. Considering variables evaluated the best conditions were temperature=30°C, oil/alcohol molar ratio=1:10, 1.5% catalyst in relation to oil (w/w), and reaction time=30min.

Statistical optimization of culture medium for yellow pigment production by Thermomyces sp.

In present study, Thermomyces sp. were able to produce high yield of yellow pigments screened. Pigment production by Thermomyces sp was optimized by employing factorial design and response surface techniques in submerged fermentation. The variables evaluated were the concentrations of, sucrose, yeast extract, ammonium sulphate, magnesium sulphate and dipotassium hydrogen phosphate having as response pigment production. One factor at-a-time method was employed for the optimization of media components. Response surface methodology (RSM) optimized these nutrient parameters for maximum yellow pigment production (1387 OD units), which resulted at 35.5 g/L sucrose 5.5 g/L yeast extract, 2.5 g/L NH4SO4, 0.3 g/L MgSO4 and 1.0 g/L K2HPO4 in the medium. Response surface methodology (RSM) was further used to determine the optimum values of process variables for maximum yellow pigment production. The fit of the quadratic model was found to be significant. A significant increase in yellow pigment production was achieved using RSM.