Response Surface Methodology Process And Product Optimization Using Designed Experiments Pdf

response surface methodology process and product optimization using designed experiments pdf

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Experimental design plays an important role in several areas of science and industry. Experimentation is an application of treatments applied to experimental units and is then part of a scientific method based on the measurement of one or more responses. It is necessary to observe the process and the operation of the system well.

Biometrics & Biostatistics International Journal

The adsorptive removal of total dissolved solids by activated coal using response surface methodology was investigated. A four-variable central composite experimental design was applied to correlate the adsorption variables effluent pH, adsorbent dosage, contact time, and adsorption temperature. The adsorption variables were optimized based on the removal of total dissolved solids from fibre cement industry effluent.

Three-dimensional surface plots were generated to estimate the effect of the combinations of the independent variables on the adsorption efficiency.

The results of the model validation gave experimental yield The good agreement found between observed and predicted values supports the suitability of the applied model to predict the adsorption treatment. Coal can be used to produce activated carbon resulting from the carbonization of the substance.

This process involves the heat treatment of coal in an inert atmosphere to required temperature leading to increase in carbon contents and decreases in contents of heteroatoms Harry and Francisco Available data show that coal occurrences in Nigeria have been indicated in more than 22 coal fields Falade and Adeyeye Nigerian coal is one of the most bituminous in the world owing to its low sulphur and ash content and therefore rated environmentally friendly Adedinni This has prompted research into conventional and non-conventional uses of the substance.

Coal is used for heating, electricity generation, and as precursor for numerous industrial chemicals. Activated carbon adsorbent has been produced from agricultural by-products such as rice husk and rubber seed shell Okiemen et al.

The limitation of fresh water resources in most parts of Nigeria has necessitated the use of unconventional water resources.

Wastewater effluent is one of these unconventional sources. However, the environmental impacts of wastewater reuse should be carefully studied Abedi et al. The discharge of effluent contaminated with dissolved solids to the environment is distressing for both toxicological and aesthetical reasons as dissolved solids impede light penetration, damage the quality of the receiving streams and are toxic to food chain organisms.

Since dissolved solids are composed of cations calcium, magnesium, lead, etc. Adsorption has been successfully employed for the removal of organic constituents Muyibi et al.

A total dissolved solid is a parameter which gives the index of dissolved compounds both organic and inorganic present in wastewater Dhall et al. Adsorption processes are usually thought of as a polishing process for wastewater streams having a number of persistent pollutants after biological treatment Amosa et al.

The application of statistical experimental design techniques such as response surface methodology, in the analysis of adsorption process, as was performed in this paper, has been associated with the following benefits: 1 all experimental units are used in evaluating effects, resulting in the most efficient use of resources; 2 the effects are evaluated over a wide range of conditions with minimum of resources; 3 a factorial set of treatments is optimized for estimating main effects and interactions Annadurai et al.

Response surface method RSM can be defined as a collection of statistical techniques for designing experiments, building models, evaluating the effects factors and searching for the optimum conditions Nwabanne and Igbokwe RSM is based on the use of second-order equation.

However, not all processes fit to a second-order polynomial. Also, not all systems containing curvature are well accommodated by the second-order polynomial. Conventional and classical methods of studying a process involve studying of one factor at a time by maintaining other factors at unspecified constant levels.

This approach does not represent the combined effect of all the parameters involved in the process Jia-Hong et al. This method is not only tedious but time-consuming. These limitations of a classical method can be effectively eliminated by optimizing all the parameters collectively by statistical experimental designs such as response surface methodology Arenas et al. These designs reduce the total number of experiments in order to achieve the best overall optimization of the process.

Full factorial design determines the effect of each factor on response as well as how the effect of each factor varies with the change in level of the other factors Montgomery ; Brasil et al. Interaction effects of different factors could be attained using design of experiments Brasil et al.

The aim of this work is the removal of dissolved solids from fibre cement industry effluent by adsorption onto activated carbon prepared from coal by optimization of process variables such as effluent pH, adsorbent dose, temperature and time using response surface methodology.

Activated carbon was prepared as reported in Ani et al. Coal was collected from Enugu Coal Mine, south-east of Nigeria. The washed and dried raw material was pulverized using a laboratory milling machine and sieved to particle sizes of 2.

The carbonized coal sample was washed and dried. Finally, the prepared activated coal adsorbent was tested and used for adsorptive removal of dissolved solids from a fibre cement industry wastewater effluent.

The structure and morphology of coal and activated coal adsorbent molecules were examined by scanning electron microscope SEM Phenom Pro X. The removal efficiency of DS molecules was calculated by Eq. Optimization studies were carried out by studying the effect of four variables including effluent pH, adsorbent dosage, contact time and adsorption temperature.

To analyse the factorial design, the original measurement units for the experimental factors uncoded units were transformed into coded units. The licensed software, Design Expert—7. The empirical equation which explains the behaviour of the system is represented as. The transformation of coded value to actual value was obtained using Eq.

The morphology of the adsorbent was studied by SEM. It was observed that raw coal particles consists of fine particles which did not have regular and fixed shape and size exhibiting low porosity Fig.

However, the smooth surface of raw coal became thicker and coarser after DS adsorption Fig. The formation of these cavities resulted from the evaporation of the dehydrating agent H 3 PO 4 during carbonization, leaving the space previously occupied by the reagent El-Hendawy et al. However, carbonization of the coal resulted in the formation of additional functional groups namely N—H amine, C—H aromatic, C—N amine and C—O alcohol or phenol.

The table depicts the characteristics of the original effluent stream as well as the characteristics after adsorption. The adsorption treatment ultimately reduced the concentration of the pollutants to levels well below the WHO specifications for recycled effluent streams.

The alkaline nature of the FCIE could be attributed to the type of raw materials used in the processing of the product. Silica, cement, cellulose and water were the major raw materials used for the formulation of fibre cement products.

The measured value of the total dissolved solids for FCIE was The adsorption efficiency of COBAC for the treatment of fibre cement industry effluent depends on whether there is significant variation in the combination of the process parameters. The empirical relationship between adsorption efficiency Y 2 and the four process variables namely pH, Adsorbent dosage, contact time and adsorption temperature coded A , B , C and D, respectively, which was obtained by Design expert 7.

Coefficients with one factor represent the effect of that particular factor, while the coefficients with more than one factor represent the interaction between those factors.

Positive sign in front of the terms indicates synergistic effect, while negative sign indicates antagonistic effect of the factor. The adequacy of the proposed model was tested using the Design expert 7. From the sequential test, it can be seen that the model F -value A model is considered significant if the p value significance probability value is less than 0. Based on this, the insignificant terms of the model were removed but B was included because of its importance in the process and to maintain the hierarchy; the model reduced to Eq.

The experimental data were also analysed to check the correlation between the experimental and predicted adsorption efficiency of COBAC for the treatment of FCIE waste. The actual and predicted plot is shown in Fig. It can be seen from the figure that the data points on the plot were reasonably distributed near to the straight line, indicating a good relationship between the experimental and predicted values of the response, and that the underlying assumptions of the above analysis were appropriate as has been described in a similar work by Chigoziri and Okechukwu The result also suggests that the selected quadratic model was adequate in predicting the response variables for the experimental data.

Plot of predicted values versus actual values for adsorption of fibre cement industry effluent using coal-based activated carbon. The three-dimensional response surface plots were generated to estimate the effect of the combinations of the independent variables on the adsorption efficiency. The plots are shown in Figs. Adsorption efficiency increased as the pH and adsorbent dosage increased. Adsorption efficiency increased as both the pH and adsorption time increased up to a point and then decreased.

However, increasing initial pH to a value higher than 6 is not a good idea as there has been precipitation of some metal cations to hydroxides leading to electrostatic repulsion. Similar result has been reported by Jumina et al.

Contour plot showing the effect of pH and adsorbent dosage on adsorption efficiency in the treatment of fibre cement industry effluent using coal-based activated carbon. Contour plot showing the effect of pH and adsorption time on adsorption efficiency in the treatment of fibre cement industry effluent using coal-based activated carbon. Contour plot showing the effect of adsorbent dosage and adsorption time on adsorption efficiency in the treatment of fibre cement industry effluent using coal-based activated carbon.

Contour plot showing the effect of adsorbent dosage and adsorption temperature on adsorption efficiency in the treatment of fibre cement industry effluent using coal-based activated carbon. Adsorption efficiency increased speedily as adsorption time increased and gradually as adsorbent dosage increased.

Adsorption efficiency increased gradually as adsorption temperature and adsorbent dosage increased up to a point and then decreased slightly.

The initial faster rate may be due to the availability of the uncovered surface area of the adsorbents, since the adsorption kinetics depends on the surface area of the adsorbents.

As a consequence, some portion of the active adsorbent sites may be blocked with the passage of time; hence, the rate becomes slower and reaches equilibrium when the surface becomes almost saturated. Igwe and Abia obtained a similar trend. The adsorption process was optimized with the design expert to obtain optimal conditions for the process.

Comparing the experimental and predicted results, it can be seen that the error between the experimental and predicted is less than 0. Scanning Electron microscopy showed the adsorption of dissolved solids on the coal-based activated carbon. FTIR spectrophotometer confirmed the presence of functional groups on the investigated samples. The selected quadratic model can be used in predicting response variables under the same conditions of the experiments.

Adsorption efficiency also increased gradually as adsorption temperature and adsorbent dosage increased up to a point and then decreased slightly. The generated model has sufficient accuracy to predict the efficiency of the process. Abedi KJ, Eslamian SS, Khaleghi M Performance of tire powder for absorption of lead, zinc and manganese heavy metals and determination of kinetic and adsorption isotherms.

Google Scholar. Adedinni A Coal: revenue source in need of revitalization. Accessed 28 Jan Int J Environ Sci Technol — Water Qual Expo Health — Waste Biomass Valoriz — Int J Chem Sci 10 3 —

Response Surface Methodology

Haemophilus influenzae type b Hib is the leading cause of bacterial meningitis, otitis media, pneumonia, cellulitis, bacteremia, and septic arthritis in infants and young children. The Hib capsule contains the major virulence factor, and is composed of polyribosyl ribitol phosphate PRP that can induce immune system response. Vaccines consisting of Hib capsular polysaccharide PRP conjugated to a carrier protein are effective in the prevention of the infections. However, due to costly processes in PRP production, these vaccines are too expensive. To enhance biomass, in this research we focused on optimizing Hib growth with respect to physical factors such as pH, temperature, and agitation by using a response surface methodology RSM. We employed a central composite design CCD and a response surface methodology to determine the optimum cultivation conditions for growth and biomass production of H. The treatment factors investigated were initial pH, agitation, and temperature, using shaking flasks.

Regret for the inconvenience: we are taking measures to prevent fraudulent form submissions by extractors and page crawlers. Correspondence: Andre I. Received: October 29, Published: March 10, Citation: Khuri AI. A general overview of response surface methodology.

The adsorptive removal of total dissolved solids by activated coal using response surface methodology was investigated. A four-variable central composite experimental design was applied to correlate the adsorption variables effluent pH, adsorbent dosage, contact time, and adsorption temperature. The adsorption variables were optimized based on the removal of total dissolved solids from fibre cement industry effluent. Three-dimensional surface plots were generated to estimate the effect of the combinations of the independent variables on the adsorption efficiency. The results of the model validation gave experimental yield

[PDF Download] Response Surface Methodology: Process and Product Optimization Using Designed

In statistics, response surface methodology RSM explores the relationships between several explanatory variables and one or more response variables. The method was introduced by George E. Box and K. Wilson in The main idea of RSM is to use a sequence of designed experiments to obtain an optimal response.

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Response surface methodology : process and product optimization using designed experiments

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The RSM introduces statistically designed experiments for the purpose of making inferences from data. The second-order model is the most frequently used approximating polynomial model in RSM. The survey reveals that second-order model is the most frequently used approximating polynomial model in RSM.

Organize knowledge in graphs, tables, and code to support concise, comprehensible, and scientifically defensible written interpretations to produce knowledge. Distinguish a testable scientific hypothesis or data-supported interpretation from an opinion. Understand from a data story the goals of the study and apply the correct statistical procedure. Explain the scientific aspects of a problem to nonscientists in a fashion that enhances understanding and decision making. Understand fundamental concepts of matching experimental designs with analysis models.

Process and Product Optimization Using Designed Experiments

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Featuring a substantial revision, the Fourth Edition of Response Surface Methodology: Process and Product Optimization Using Designed Experiments presents.

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