Journal articles: 'Response Surface Methodology (RSM)'

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Dube, Vinitkumar Dilipkumar. "Optimization of Biodiesel (MOME) Using Response Surface Methodology (RSM)." International journal of Emerging Trends in Science and Technology 04, no. 11 (November 13, 2016): 4736–41. http://dx.doi.org/10.18535/ijetst/v3i11.02.

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Zhang, Pei Pei, and Zi Dong Yin. "A New Response Surface Methodology: XU-RSM." Advanced Materials Research 396-398 (November 2011): 126–29. http://dx.doi.org/10.4028/www.scientific.net/amr.396-398.126.

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This paper aims to develop a new Response Surface Methodology (RSM)— XU-RSM— adapted to Reliability-Based Design Optimization (RBDO) based on Diffuse Approximation (DA) and First-Order Reliability Method (FORM). The essential of the new response surface methodology is to use simultaneously the points both in a design space (X-space) and an independent standard normal random space (U-space). Mixing the points allows for more precise local approximation due to denser sampling points and leads to a faster convergence. Finally, a mathematic example is given to show how to use the new method and the comparison of results of evolutions.

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Hadiyat, Mochammad Arbi, Bertha Maya Sopha, and Budhi Sholeh Wibowo. "Response Surface Methodology Using Observational Data: A Systematic Literature Review." Applied Sciences 12, no. 20 (October 21, 2022): 10663. http://dx.doi.org/10.3390/app122010663.

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In the response surface methodology (RSM), the designed experiment helps create interfactor orthogonality and interpretable response models for the purpose of process and design optimization. However, along with the development of data-recording technology, observational data have emerged as an alternative to experimental data, and they contain potential information on design/process parameters (as factors) and product characteristics that are useful for RSM analysis. Recent studies in various fields have proposed modifications to the standard RSM procedures to adopt observational data and attain considerable results despite some limitations. This paper aims to explore various methods to incorporate observational data in the RSM through a systematic literature review. More than 400 papers were retrieved from the Scopus database, and 83 were selected and carefully reviewed. To adopt observational data, modifications to the procedures of RSM analysis include the design of the experiment (DoE), response modeling, and design/process optimization. The proposed approaches were then mapped to capture the sequence of the modified RSM analysis. The findings highlight the novelty of observational-data-based RSM (RSM-OD) for generating reproducible results involving the discussion of the treatments for observational data as an alternative to the DoE, the refinement of the RSM model to fit the data, and the adaptation of the optimization technique. Future potential research, such as the improvement of factor orthogonality and RSM model modifications, is also discussed.

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Kumar, Rupak, and Meega Reji. "Response surface methodology (RSM): An overview to analyze multivariate data." Indian Journal of Microbiology Research 9, no. 4 (January 15, 2023): 241–48. http://dx.doi.org/10.18231/j.ijmr.2022.042.

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In recent years, the fascinating range of Response surface methodology (RSM) applications has captured the interest of many researchers and engineers worldwide. RSM is entirely based on well-known regression principles and variance analysis principles that enable the user to improve, develop and optimize the process or product under study. An overview of the theoretical principles of RSM, the experimental strategy and its tools and components, along with the applications and pros and cons, are described in this paper. Some of the widely used experimental designs of RSM compared in terms of its characteristics and efficiency are included, which helps to point out the importance of design of experiments (DOE) in optimization using RSM. The live demonstrations of a few optimization examples using response surface methodology in different research manuscripts included in this paper also provide a better understanding of the characteristics of RSM in different scenarios.

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HARRIS, P. L., S. L. CUPPETT, and L. B. BULLERMAN. "Optimization of Lipase Synthesis by Pseudomonas fluorescens by Response Surface Methodology." Journal of Food Protection 53, no. 6 (June 1, 1990): 481–83. http://dx.doi.org/10.4315/0362-028x-53.6.481.

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Using response surface methodology (RSM), the optimum environmental conditions of temperature, pH. and aeration for lipase synthesis by Pseudomonas fluorescens were found to be 25°C, 8.07, and 65 rpm, respectively, for 5 d of incubation. Of the three factors, temperature was most influential in affecting extracellular lipase production.

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Chu, Tsu Hsiao, Kuang Hua Fuh, and Wei Ching Yeh. "Experimental Optimization of Deep Drawing Using Response Surface Methodology." Applied Mechanics and Materials 121-126 (October 2011): 1495–99. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.1495.

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A ultrasonic vibration system with ram motion of two steps is developed to optimize the formability for thin workpiece at the end of forming. The deep drawing force and forming height can be predicted in view of optimizing the values of the working variables involved in the process parameters. A response surface methodology (RSM) based on design of experiments was used in order to minimize the forming force and maximum the forming height during the deep drawing process. Associated plots are shown to be efficient for a quick choice of the optimum values of the forming process parameters.

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Kant, Girish, Vaibhav Rao V, and Kuldip Singh Sangwan. "Predictive Modeling of Turning Operations Using Response Surface Methodology." Applied Mechanics and Materials 307 (February 2013): 170–73. http://dx.doi.org/10.4028/www.scientific.net/amm.307.170.

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This paper focuses on the development of a predictive model using the measured forces acting on the cutting tool during turning operation of AISI 1045 Steel using a Tungsten Carbide cutting tool insert. On the basis of the experimental results, second order mathematical model is developed in terms of machining parameters by using the Response Surface Methodology (RSM). The results are analyzed statistically and graphically. It has been observed that the predicted values using RSM also follow the same trend as given by the measured values.

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Achyutha Kumar Reddy, M., V. Ranga Rao, K. Naga Chaitanya, and Veerendrakumar C. Khed. "Optimization of Bentocrete parameters using Response Surface Methodology (RSM)." AIMS Materials Science 8, no. 2 (2021): 221–46. http://dx.doi.org/10.3934/matersci.2021015.

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Azhari, Ayu Wazira, Kamaruzzaman Sopian, Dewi Suriyani Che Halin, Abdul Haqi Ibrahim, and Saleem H. Zaidi. "Response Surface Methodology (RSM) in Fabrication of Nanostructured Silicon." Materials Science Forum 857 (May 2016): 151–55. http://dx.doi.org/10.4028/www.scientific.net/msf.857.151.

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In this paper, a respond surface methodology (RSM) model has been developed using three levels Box-Benkhen experimental design (BBD) technique to study the influence of several metal-assisted chemical etching (MACE) process variables on the properties of nanostructured silicon (Si) wafer. Five process variables are examined i.e. concentrations of silver (Ag), hydrofluoric acid (HF), deposition time, H2O2 concentration and etching time as a function of etching rate. Design-Expert® software (version 7.1) is used in formulating the RSM model of five factors with 46 experiments. A regression quadratic model is developed to correlate the process variables where the most significant factors are identified and validated using analysis of variance (ANOVA). The model for etching rate is found to be significant with R2 of 0.8, where both Ag concentrations and etching time are the major influence.

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Manpreet, Singh, Chawla Rekha, Khatkar Sunil Kumar, and Singh Sandeep. "Development of Milk Chocolate Using Response Surface Methodology (RSM)." International Journal of Current Microbiology and Applied Sciences 6, no. 6 (June 10, 2017): 2881–94. http://dx.doi.org/10.20546/ijcmas.2017.606.341.

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Aktaş, Nahit. "Optimization of biopolymerization rate by response surface methodology (RSM)." Enzyme and Microbial Technology 37, no. 4 (September 2005): 441–47. http://dx.doi.org/10.1016/j.enzmictec.2005.03.010.

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Nooraziah, Ahmad, and V. Janahiraman Tiagrajah. "A Study on Regression Model Using Response Surface Methodology." Applied Mechanics and Materials 666 (October 2014): 235–39. http://dx.doi.org/10.4028/www.scientific.net/amm.666.235.

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Response Surface Methodology (RSM) mostly employs statistical regression method as it is practical, economical and relatively easy to use. The first and second order polynomial equation was developed using RSM. This polynomial model usually refers as a regression model. In this research, the objective is to find the best response surface method to model three factors and three levels parameters in machining. From the study, the Box-Behnken Design can develop a good regression model rather than Central Composite Design or Full Factorial Design. While, the second order regression model has proved to be more effective in predicting the performance of the given data set.

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Ekpu, M. "Optimisation of a microelectronic assembly package using response surface methodology." Nigerian Journal of Technology 39, no. 4 (March 24, 2021): 1058–65. http://dx.doi.org/10.4314/njt.v39i4.12.

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This article addressed heat conduction in microelectronics applications. ANSYS finite element design software was used to design the model, while Design Expert software was used for the response surface methodology (RSM) analysis. The components analysed were heat-sink base (HSB) thickness, thermal interface material (TIM) thickness, and chip thickness. A design of experiment comprising of 15 central composite design (CCD) for the coded levels (low (-) and high (+)) of the factors were generated. Heat flow was applied to the chip while a convective coefficient was applied to the heat-sink. The temperature solution was used to calculate the thermal resistance response for the 15 CCD experimental runs. The results from the RSM study proposed an optimal (minimization analysis) combination of 3.5 mm, 0.04 mm, and 0.75 mm, for HSB thickness, TIM thickness, and chip thickness respectively. While the optimal mean thermal resistance of 0.31052 K/W was achieved from the proposed optimal parameters. Keywords: RSM; CCD; thermal resistance; temperature; microelectronics

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Mohamad, Nor Syahirah, and Salmiah Kasolang. "Optimized characterization of response surface methodology on lubricant with titanium oxide nanoparticles." Industrial Lubrication and Tribology 69, no. 3 (May 8, 2017): 387–92. http://dx.doi.org/10.1108/ilt-09-2016-0214.

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Purpose An optimized model is often deployed to reduce trial and error in experimental approach and obtain the multi-variant correlation. In this study, response surface methodology (RSM), namely, Box–Behnken design (BBD) approach, has been used to optimize the characterization of lubricant with additives. BBD is based on multivariate analysis whereby the effects of different parameters are considered simultaneously. It is a non-linear system which is more representative of the actual phenomenon. This study aims to investigate the effect of three independent variables, namely, speed, load and concentration of TiO2, on the coefficient of friction (CoF). Design/methodology/approach RSM was applied to get the multiplicity of the self-determining input variables and construct mathematical models. Mathematical models were established to predict the CoF and to conduct a statistical analysis of the independent variables’ interactions on response surface using Minitab 16.0 statistical software. Three parameters were regulated: speed (X1), load (X2) and concentration of TiO2 (X3). The output measured was the CoF. Findings The result obtained from BBD has shown that the most influential parameter was speed, followed by concentration of TiO2 nanoparticles and then normal load. Analysis of variance indicated that the proposed experiment from the quadratic model has successfully interpreted the experimental data with a coefficient of determination R2 = 0.9931. From the contour plot of BBD, the optimization zone for interacting variables has been obtained. The zone indicates two regions of lower friction values (<0.04): concentration between 0.5 to 1.0 Wt.% for a speed range of 1,000 to 2,000 rpm, and load between 17 to 20 kg for a speed in the range of 1,200 to 1,900 rpm. The optimized condition shows that the minimum value of CoF (0.0191) is at speed of 1,782 rpm, load of 20 kg and TiO2 concentration of 1.0 Wt.%. Originality/value In general, it has been shown that RSM is an effective and powerful tool in experimental optimization of multi-variants.

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Yusoff, Siti Ruqaiyah Mohd, Ain Aqilah Basirun, and Mohd Izuan Effendi Halmi. "Biebrich Scarlet Biodegradation Optimization Using Response Surface Methodology." Journal of Environmental Microbiology and Toxicology 8, no. 1 (July 31, 2020): 42–49. http://dx.doi.org/10.54987/jemat.v8i1.522.

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The study was carried out to isolate bacterial strain potential for decolourizing the azo- dye Biebrich Scarlet and to optimize the dye decolourisation using Response Surface Methodology (RSM). From azo- dye screening, five isolates were capable of decolourising Biebrich scarlet and out of these, isolate 33 shows the highest decolourisation rate of 4.9x10-6 mgml-1min-1 compared to the other four. Response Surface Method (RSM) which includes Central Composite design (CCD) was employed following a screening procedure as such the Plackett- Burman design to attain optimal condition in order to achieve full azo- dye Biebrich scarlet decolourisation. Seven variables; pH, temperature (Â°C), ammonium acetate (%), glucose (%), salinity (%), yeast (%) and dye concentration (ppm) were studied. From Plackett- Burman design, four of these variables were chosen for further optimisation. Out of 30 individual runs of CCD, three variables; dye concentration, pH and yeast excluding ammonium acetate showed significant model terms (P-value < 0.05). Morphological identification was carried out on isolate 33 and results predicted that the isolate was a Gram-negative bacterium with catalase and cytochrome oxidase enzymes. This isolate gave a gamma hemolysis on blood agar medium and it decolourises Biebrich scarlet better in a minimal oxygen condition. The optimum ranges expected for a maximum dye decolourisation from this study were ammonium acetate (%) of 0.310.60; dye decolourisation (ppm) of about 112.16 or less; pH of 6.62-7.38 and yeast (%) of 0.23- 0.37. The significance of this study is to isolate, screen and identify the best isolated bacterial strain capable of decolourising Biebrich scarlet azo- dye, to study on the factors promoting the growth and the decolourisation of azo- dye by the isolated bacterium through means of RSM and to estimate the optimum condition in the factors which has a significant effect on the decolourisation percentage.

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M. S., Ranganath, Vipin ., Nand Kumar, and Rakesh Kumar. "Experimental Analysis of Surface Roughness in CNC Turning of Aluminium Using Response Surface Methodology." International Journal of Advance Research and Innovation 3, no. 1 (2015): 206–12. http://dx.doi.org/10.51976/ijari.311536.

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The main controllable parameters for the CNC turning machines are cutting tool variables, work piece material variables, and cutting conditions. The desired output is surface roughness, material removal rate and tools wear. Optimization of machining parameters needs to determine the most significant parameter for required output. Various techniques are used for optimization of machining parameters including Taguchi, RSM and ANOVA approach to determine most significant parameter. This work presents the findings of an experimental investigation into the effects of cutting speed, feed rate, and depth of cut in CNC turning of Aluminium KS 1275. Response surface methodology (RSM) is used to accomplish the objective of the experimental study. Face centered central composite design has been used for conducting the experiments. The result from RSM reveals that feed is the most significant factor followed by depth of cut.

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Nandakumar, C., and B. Mohan. "Multi-Response Optimization of CNC WEDM Process Parameters for Machining Titanium Alloy Ti 6AI-4V Using Response Surface Methodology (RSM)." Applied Mechanics and Materials 541-542 (March 2014): 354–58. http://dx.doi.org/10.4028/www.scientific.net/amm.541-542.354.

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This research deals with the multi-response optimization of CNC WEDM process parameters for machining titanium alloy Ti 6AI-4V using Response Surface Methodology (RSM) to achieve higher Material Removal Rate (MRR) and lower surface roughness (Ra). The process parameters of CNC WEDM namely pulse-on time (TON), pulse-off time (TOFF) and wire feed rate (WF) were optimized to study the responses in terms of material removal rate and surface roughness. The surface plot and the contour plots were generated between the process parameters and the responses using MINITAB software. The results show that the Response surface methodology (RSM) is a powerful tool for providing experimental diagrams and statistical-mathematical models to perform the experiments appropriately and economically.

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Rastbood, A., Y. Gholipour, and A. Majdi. "Finite Element Based Response Surface Methodology to Optimize Segmental Tunnel Lining." Engineering, Technology & Applied Science Research 7, no. 2 (April 24, 2017): 1504–14. http://dx.doi.org/10.48084/etasr.1045.

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The main objective of this paper is to optimize the geometrical and engineering characteristics of concrete segments of tunnel lining using Finite Element (FE) based Response Surface Methodology (RSM). Input data for RSM statistical analysis were obtained using FEM. In RSM analysis, thickness (t) and elasticity modulus of concrete segments (E), tunnel height (H), horizontal to vertical stress ratio (K) and position of key segment in tunnel lining ring (θ) were considered as input independent variables. Maximum values of Mises and Tresca stresses and tunnel ring displacement (UMAX) were set as responses. Analysis of variance (ANOVA) was carried out to investigate the influence of each input variable on the responses. Second-order polynomial equations in terms of influencing input variables were obtained for each response. It was found that elasticity modulus and key segment position variables were not included in yield stresses and ring displacement equations, and only tunnel height and stress ratio variables were included in ring displacement equation. Finally optimization analysis of tunnel lining ring was performed. Due to absence of elasticity modulus and key segment position variables in equations, their values were kept to average level and other variables were floated in related ranges. Response parameters were set to minimum. It was concluded that to obtain optimum values for responses, ring thickness and tunnel height must be near to their maximum and minimum values, respectively and ground state must be similar to hydrostatic conditions.

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Na, Xian, and Hu Guohua. "Effects of xanthan gum and corn flour on the quality of sponge cake using response surface methodology." Czech Journal of Food Sciences 36, No. 4 (September 3, 2018): 344–51. http://dx.doi.org/10.17221/476/2016-cjfs.

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Effects of partial replacement of wheat flour with corn flour (2.93–17.07%) blended with xanthan gum (0.1172–0.6828%) on physical properties, textural and sensory characteristics of sponge cakes were evaluated by response surface methodology (RSM). The significant regression models (P ≤ 0.05) were established to explain the influence of corn flour and xanthan (Xan) on the dependent variables and optimize the formulation. Xanthan significantly increased moisture content, hardness and chewiness, but it decreased specific volume and springiness (P ≤ 0.001). Corn flour had significant positive effects on specific volume, hardness, springiness, colour and overall acceptability (P ≤ 0.05). Hence corn flour and xanthan significantly improved the baking quality of sponge cakes (P ≤ 0.05) and thereby augmented the potential for using wheat-corn blend flours in cake baking. Based on RSM optimisation, a balance between amounts of corn flour (12.7%) and xanthan (0.416%) led to products with desired physical properties and acceptable sensory quality.

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Nur, Ahmad Moh, Hairul Huda, and Rif'an Fathoni. "OPTIMALISASI PROSES EKSTRAKSI MINYAK BIJI NYAMPLUNG MENGGUNAKAN RESPONSE SURFACE METHODOLOGY (RSM)." Jurnal Chemurgy 6, no. 2 (December 25, 2022): 97. http://dx.doi.org/10.30872/cmg.v6i2.9450.

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Nyamplung (Calophyllum inophyllum L.) is a plant with great potential as a fuel source that can be developed in Indonesia. The oil content of nyamplung seeds is 60-75%. This study aims to optimize the process of extracting oil from nyamplung seeds using hexane solvent at various operating conditions and obtain optimum extraction operating conditions. In the process stage, extraction will be carried out using hexane solvent with several operating variations, namely extraction temperature (35-45oC); extraction time (4-6 hours); stirring speed (200-600 rpm), the process of optimizing oil extraction from nyamplung seeds was carried out using the Response Surface Methodology (RSM). The oil obtained was then characterized through several analyzes, namely yield, acid number, density and viscosity. Based on the research results, optimization of the nyamplung seed oil extraction process resulted in an oil yield of 52.43% which was obtained at 40oC, 5 hours of extraction time and 500 rpm of stirrer speed. Optimization with the aim of maximizing the oil yield response was obtained 55.33% yield at 45oC, 6 hours extraction time and 600 rpm stirrer speed. Optimization of each oil quality does not produce a significant model response. The quality of the oil resulting from the optimization of the yield is an acid number of 10.51 mgKOH/g, a density of 0.94 g/ml, and a viscosity of 4.47 cP.Keywords: calophyllum, oil, optimization, response surface methodology

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Fan, Xiaohu, Xi Wang, and Feng Chen. "Biodiesel Production from Crude Cottonseed Oil: An Optimization Process Using Response Surface Methodology." Open Fuels & Energy Science Journal 4, no. 1 (February 17, 2011): 1–8. http://dx.doi.org/10.2174/1876973x01104010001.

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Biodiesel, known as fatty acid methyl ester (FAME), was produced from crude cottonseed oil (triglycerides) by transesterification with methanol in the presence of sodium hydroxide. This process was optimized by applying factorial design and response surface methodology (RSM) with SAS and PSIPLOT programs. A second-order mathematical model was obtained to predict the yield as a function of methanol/oil molar ratio, catalyst concentration, reaction temperature, and rate of mixing. Based on ridge max analysis and RSM, as well as economic cost consideration, the practical optimal condition for the production of biodiesel was found to be: methanol/oil molar ratio, 7.9; temperature, 53 °C; time, 45 min; catalyst concentration, 1.0%; and rate of mixing, 268 rpm. The optimized condition was validated with the actual biodiesel yield of 97%. Furthermore, the biodiesel was confirmed by HPLC analyses that triglycerides of cottonseed oil were almost completely converted to FAME.

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Galai, Said, Youssef Touhami, and Med Nejib Marzouki. "Response surface methodology applied to laccases activities exhibited by Stenotrophomonas maltophilia AAP56 in different growth conditions." BioResources 7, no. 1 (January 6, 2012): 706–26. http://dx.doi.org/10.15376/biores.7.1.706-726.

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Stenotrophomonas maltophilia AAP56, laccase-producing bacteria, growing under different conditions, exhibit laccase activity that is highly affected by some environmental factors. Response surface methodology (RSM) was applied for the determination of laccase factor dependence using two substrates: ABTS (2,2’-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid)) and DMP (2,6 Dimethoxy-phenol). RSM was carried out with a 24 factorial design using four variables, namely, dye (0 to 0.1 mg mL-1), Cu in Med (0 to 400 µM), shaking (0 to 150 rpm), and CuSO4 in assay (0 to 0.2 mM). Significant correlation between the effects of these variables on R1 (ABTS oxidase activity) and R2 (DMP oxidase activity) responses was detected. Astonishing results showed differences between these two activities with respect to copper activity dependence. Anoxic conditions exhibited a significant ability to induce the enzyme. This bacterial laccase activity (produced under optimal conditions according to RSM) was used to decolorize an azoic dye, Reactive Black 5 (RB5). It was efficient only in the presence of a redox mediator to degrade RB5 after 20 min of incubation time.

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Goemaere, Ilia, Deep Punj, Aranit Harizaj, Jessica Woolston, Sofie Thys, Karen Sterck, Stefaan C. De Smedt, Winnok H. De Vos, and Kevin Braeckmans. "Response Surface Methodology to Efficiently Optimize Intracellular Delivery by Photoporation." International Journal of Molecular Sciences 24, no. 4 (February 5, 2023): 3147. http://dx.doi.org/10.3390/ijms24043147.

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Photoporation is an up-and-coming technology for the gentle and efficient transfection of cells. Inherent to the application of photoporation is the optimization of several process parameters, such as laser fluence and sensitizing particle concentration, which is typically done one factor at a time (OFAT). However, this approach is tedious and runs the risk of missing a global optimum. Therefore, in this study, we explored whether response surface methodology (RSM) would allow for more efficient optimization of the photoporation procedure. As a case study, FITC-dextran molecules of 500 kDa were delivered to RAW264.7 mouse macrophage-like cells, making use of polydopamine nanoparticles (PDNPs) as photoporation sensitizers. Parameters that were varied to obtain an optimal delivery yield were PDNP size, PDNP concentration and laser fluence. Two established RSM designs were compared: the central composite design and the Box-Behnken design. Model fitting was followed by statistical assessment, validation, and response surface analysis. Both designs successfully identified a delivery yield optimum five- to eight-fold more efficiently than when using OFAT methodology while revealing a strong dependence on PDNP size within the design space. In conclusion, RSM proves to be a valuable approach to efficiently optimize photoporation conditions for a particular cell type.

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Song, Cuina, Liping Zhu, Yanchun Shao, and Fusheng Chen. "Enhancement of GABA content in Hongqu wine by optimisation of fermentation conditions using response surface methodology." Czech Journal of Food Sciences 39, No. 4 (August 29, 2021): 297–304. http://dx.doi.org/10.17221/47/2021-cjfs.

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γ-aminobutyric acid (GABA) is an important inhibitory neurotransmitter in the human body, but its content decreases with age. So it is suitable to supplement the body's GABA from diet. Hongqu wine is popular because of the addition of Monascus strains in the saccharification process, which makes the wine rich in functional ingredients such as GABA, and monacolin K. In this study, the fermentation parameters of Hongqu wine were optimised to maximise the GABA content through response surface methodology (RSM). The optimal conditions were as follows: 500 g of steamed rice was mixed with 115.4% of boiled water containing 10 g of sodium glutamate and adjusted to pH 3.8 with lactic acid, and then 32% of Hongqu seed inoculum was added. After 5 days of fermentation at 28 °C, 1.5 g of activated yeast was inoculated for ethanol fermentation at 30 °C for 5 days. Finally, the average content of GABA in Hongqu wine amounted to 710.24 mg L<sup>–1</sup>, which is close to the value predicted by RSM model (692.44 mg L<sup>–1</sup>), indicating the statistical fit is good. This provided technical support and theoretical guidance for the production of Hongqu wine rich in GABA by two-stage fermentation.

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Ebrahimi, Shamsi, Coswald Stephen Sipaut@ Mohd Nasri, and Sazmal Effendi Bin Arshad. "Hydrothermal synthesis of hydroxyapatite powders using Response Surface Methodology (RSM)." PLOS ONE 16, no. 5 (May 20, 2021): e0251009. http://dx.doi.org/10.1371/journal.pone.0251009.

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Hydroxyapatite (HAp)—[Ca10 (PO4)6(OH) 2] has a similar chemical composition to bone material, making it the main mineral supplement in bone-making. Due to its high biocompatibility, hydroxyapatite is widely used in the repair of bone deficiencies and in the production of dental or orthopedic implants. In this research, hydroxyapatite nanopowder was synthesized using a hydrothermal technique. Fourier Transform Infrared Spectroscopy (FTIR) and transmission electron microscopy (TEM) were used to investigate the chemical structure and morphology of the synthesized hydroxyapatite powder. X-ray diffraction (XRD) was used to evaluate the phase analysis of HAp nanopowder. In addition, bioactivity HAp assessment was conducted by scanning electron microscopy (SEM) attached with Energy Dispersive X-Ray Spectroscopy (EDX) analysis. Response Surface Methodology (RSM) with central composite design (CCD) was used in order to determine the optimal conditions for yield, size, and crystallinity. Three independent variables (pH, temperature, and hydrothermal treatment time) were investigated. The yield was observed to increase in alkaline conditions; pH showed the greatest influence on the yield, size, and crystallinity of the synthesized hydroxyapatite, based on Analysis of Variance. The results of bioactivity evaluation are showed high bioactivity due to the formation of apatite on the surface of the synthesized nanopowder.

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Sudha, G., and V. Ganesh. "Enzymatic Degradation of Polycarbonates: Response Surface Methodology (RSM) Based Approach." Journal of Physics: Conference Series 1979, no. 1 (August 1, 2021): 012006. http://dx.doi.org/10.1088/1742-6596/1979/1/012006.

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Adnan Abdel-Rahman, Zaid. "Optimization of Sodium Bicarbonate Production Using Response Surface Methodology (RSM)." DJES 11, no. 3 (September 1, 2018): 22–28. http://dx.doi.org/10.24237/djes.2018.11304.

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The main objective of this study was to evaluate the use of batch bubble column to produce high particle size (>300 micron) of sodium bicarbonate product to improve filtration and drying operations in the production process. Lab scale batch bubble column of 80 mm diameter and 0.5 m height was used to study the process for sodium bicarbonate production using 20% sodium carbonate solution as a starting solution. Three operating variables were considered, CO2 gas content (20-100 %), temperature (30-70 oC) and time (0.5-2.5 h). The bicarbonate yield and crystals size were considered to be the objective variables of the process. Response surface methodology (RSM) was used with central composite design (CCD) of experiments. Empirical polynomial multivariable equations were obtained. The reaction time was found to be the most effective operating condition on the yield of sodium bicarbonate, and temperature was found to be the most effective operating condition on crystal size of sodium bicarbonate. The optimum conditions achieved 400 microns particle size at temperature 70 oC and time 2.5 h. Kinetics study of the process showed that zero order reaction with both sodium carbonate and CO2 concentrations was approximately fitted the experimental data, useful for shortcut process design purposes.

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Lee, Hyunk-Ok, and A. Montag. "Antioxidative Wirksamkeit von Tocochromanolen – Rangfolgebestimmung mit „Response Surface Methodology (RSM)”." Fett Wissenschaft Technologie/Fat Science Technology 94, no. 6 (1992): 213–17. http://dx.doi.org/10.1002/lipi.19920940605.

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Priadi, Gunawan, Fitri Setiyoningrum, Fifi Afiati, Nela Rifda Nur Millatina, Budi Nurtama, and Des Saputro Wibowo. "Optimasi formula yogurt bawang hitam menggunakan response surface methodology (RSM)." Jurnal Litbang Industri 13, no. 1 (June 30, 2023): 1. http://dx.doi.org/10.24960/jli.v13i1.7863.1-10.

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Pak, Ro Jin. "Combination of importance-performance analysis and response surface methodology for enhancing satisfaction." International Journal of Quality & Reliability Management 33, no. 6 (June 6, 2016): 792–802. http://dx.doi.org/10.1108/ijqrm-06-2014-0079.

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Purpose – In order to know how to enhance the satisfaction of online courses in preparing for the college entrance examination in Korea, the purpose of this paper is to combine both the importance-performance analysis (IPA) and the response surface methodology (RSM). Design/methodology/approach – IPA is a simple but powerful tool for understanding the current status of factors or attributes in management problems. However, it lacks to provide the proper indication of what to do next on those factors or attributes to optimize a goal. RSM is a statistical tool helping us to set up a direction of factors or attributes in optimizing an output. The author attempts to combine both IPA and RSM in order to discover the next step after IPA for optimizing the goal. As an example, the author considers how to enhance the satisfaction of online courses in preparing for the college entrance examination in Korea. Findings – The combination of IPA and RSM enables us to find a way to attain a goal, for example, satisfying customers in a concrete and creative way. Research limitations/implications – Sample size is enough for research purpose but is a bit small for general purpose. Practical implications – This research tries to answer what to do next after IPA. Social implications – This research provides a predictive guide to satisfy customers. Originality/value – As far as the author knows, combining both IPA and RSM has not been made so far. It is a fusion of managerial and engineering techniques.

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Irfan, Muhammad, Sharjeel Waqas, Ushtar Arshad, Javed Akbar Khan, Stanislaw Legutko, Izabela Kruszelnicka, Dobrochna Ginter-Kramarczyk, Saifur Rahman, and Anna Skrzypczak. "Response Surface Methodology and Artificial Neural Network Modelling of Membrane Rotating Biological Contactors for Wastewater Treatment." Materials 15, no. 5 (March 4, 2022): 1932. http://dx.doi.org/10.3390/ma15051932.

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Membrane fouling is a major hindrance to widespread wastewater treatment applications. This study optimizes operating parameters in membrane rotating biological contactors (MRBC) for maximized membrane fouling through Response Surface Methodology (RSM) and an Artificial Neural Network (ANN). MRBC is an integrated system, embracing membrane filtration and conventional rotating biological contactor in one individual bioreactor. The filtration performance was optimized by exploiting the three parameters of disk rotational speed, membrane-to-disk gap, and organic loading rate. The results showed that both the RSM and ANN models were in good agreement with the experimental data and the modelled equation. The overall R2 value was 0.9982 for the proposed network using ANN, higher than the RSM value (0.9762). The RSM model demonstrated the optimum operating parameter values of a 44 rpm disk rotational speed, a 1.07 membrane-to-disk gap, and a 10.2 g COD/m2 d organic loading rate. The optimization of process parameters can eliminate unnecessary steps and automate steps in the process to save time, reduce errors and avoid duplicate work. This work demonstrates the effective use of statistical modeling to enhance MRBC system performance to obtain a sustainable and energy-efficient treatment process to prevent human health and the environment.

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Ovat Friday Aje and Anyandi Josephat Adie. "Response surface methodology and Taguchi method based applications – A Review." Global Journal of Engineering and Technology Advances 5, no. 1 (October 30, 2020): 053–59. http://dx.doi.org/10.30574/gjeta.2020.5.1.0062.

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Response surface methodology (RSM) is usually applied together with a factorial design to reduce the cost of experimentation and is especially useful when there are more potential factors than money to study a response. It was designed as a tool to have a lot of (partial) answers with as few experiments as possible; to detect factors that influence a response, and whether they interact, as well as finding an optimum treatment within a specific setup. On the other hand, the Taguchi method is a statistical method, also called robust design method, to improve the quality of manufactured goods, and more recently also applied to engineering. This paper presents an extensive literature review on the concept of the RSM and Taguchi methods in solvent extraction, engineering optimization and several machining process parameters.

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Pondi, P., J. Achebo, and A. Ozigagun. "Optimization of the Tungsten Inert Gas Process Parameters using Response Surface Methodology." International Journal of Emerging Scientific Research 2 (June 27, 2021): 26–33. http://dx.doi.org/10.37121/ijesr.vol2.150.

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Optimization is a very important techniques applied in the manufacturing industry that utilizes mathematical and artificial intelligence methods. The complexity associated with most optimization techniques have resulted to search for new ones. This search has led to the emergence of response surface methodology (RSM). The paper aims to optimize tungsten inert gas process parameters required to eliminate post-weld crack formation and stabilize heat input in mild steel weldment using RSM. The main input variables considered are voltage, current and speed whereas the response parameter is Brinell hardness number (BHN). The statistical design of experiment was done using the central composite design technique. The experiment was implemented 20 times with 5 specimens per experiment. The responses were measured, recorded and optimized using RSM. From the results, it was observed that a voltage of 21.95 V, current of 190.0 A, and welding speed of 5.00 mm/s produced a weld material with the following optimal properties; BHN (200.959 HAZ), heat input (1.69076 kJ/mm), cooling rate (72.07 /s), preheat temperature (150.68 ) and amount of diffusible hydrogen (12.36 mL/100g). The optimal solution was selected by design expert with a desirability value of 95.40 %.

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Zaid, Hiba, Zainab Al-sharify, Mohammed Hazwan Hamzah, and Salih Rushdi. "OPTIMIZATION OF DIFFERENT CHEMICAL PROCESSES USING RESPONSE SURFACE METHODOLOGY- A REVIEW." Journal of Engineering and Sustainable Development 26, no. 6 (November 4, 2022): 1–12. http://dx.doi.org/10.31272/jeasd.26.6.1.

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Several chemical and biological processes have been investigated and predicted using Response Surface Methodology (RSM) models. Response Surfaces Methodology is a useful instrument for designing laboratory-scale experiments that optimize and support the research outcomes with statistical analysis. It is a powerful statistical technique for complex variable study systems. The standard optimization (one component at a time) strategy is well-studied. However, it has significant drawbacks, such as requiring more experimental runs and time and failing to reveal the synergistic impact of processing parameters. It is a valuable instrument for process improvement. Recent research has shown, for instance, that RSM successfully optimizes biodiesel in fats and oils generated from diverse feedstocks. According to this study, Response Surface Methodology is the best cost-effective technique for maximizing environmentally friendly and sustainable methods applied to different experimental procedures. The current review reported RSM's application, theory, methodology, advantages, and limitations for different processes using different oil sources.

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G, Ramanan, Rajesh Prabha.N, Diju Samuel.G, Jai Aultrin. K. S, and M. Ramachandran. "Prediction of Machining Characteristics of Hybrid Composites Using Response Surface Methodology Approach." International Journal of Engineering & Technology 7, no. 3.1 (August 4, 2018): 162. http://dx.doi.org/10.14419/ijet.v7i3.1.17078.

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This manuscript presents the influencing parameters of CNC turning conditions to get high removal rate and minimal response of surface roughness in turning of AA7075-TiC-MoS2 composite by response surface method. These composites are particularly suited for applications that require higher strength, dimensional stability and enhanced structural rigidity. Composite materials are engineered materials made from at least two or more constituent materials having different physical or chemical properties. In this work seventeen turning experiments were conducted using response surface methodology. The machining parameters cutting speed, feed rate, and depth of cut are varied with respect to different machining conditions for each run. The optimal parameters were predicted by RSM technique. Turning process is studied by response surface methodology design of experiment. The optimal parameters were predicted by RSM technique. The most influencing process parameter predicted from RSM techniques in cutting speed and depth of cut.

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Abdul Ghani, Muhammad Ridzuan, and Oh Pei Ching. "Optimization of Ethanol Production from Mango Peels Using Response Surface Methodology." Applied Mechanics and Materials 625 (September 2014): 766–69. http://dx.doi.org/10.4028/www.scientific.net/amm.625.766.

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This study aims to optimize bioethanol production from mango peels using Response Surface Methodology (RSM). The effect of temperature (25–40oC), yeast concentration (6–14 g/ml) and fermentation time (48–96 hours) on bioethanol yield was investigated. Prior to the fermentation process, mango peels were treated with 0.25–1% (w/v) sulphuric acid. Optimum glucose yield was obtained at 0.25% (w/v) sulphuric acid. RSM using 3-factor 2-level central composite design (CCD) was employed to evaluate and optimize the synthesis parameters. Based on numerical optimization, the optimum fermentation conditions were at 38oC using 6 g/ml yeast for 48 hours, giving a yield of 7.34 g/ml bioethanol.

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Arancibia-Bravo, María P., Freddy A. Lucay, Felipe D. Sepúlveda, Lorena Cortés, and Luís A. Cisternas. "Response Surface Methodology for Copper Flotation Optimization in Saline Systems." Minerals 12, no. 9 (September 7, 2022): 1131. http://dx.doi.org/10.3390/min12091131.

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Response surface methodology (RSM) is one of the most effective tools for optimizing processes, and it has been used in conjunction with the Analysis of Variance (ANOVA) test to establish the effect of input factors on output factors. However, when this methodology is used in mineral flotation, its polynomial model usually performs poorly. An alternative is to use artificial neural networks (ANNs) in such situations. Within this context, the ANOVA test is not the best option for these model types; moreover, it requires statistical assumptions that are difficult to satisfy in flotation. This work proposes replacing the polynomial model of the RSM with ANNs and the Sobol methods to determine the influential input factors instead of the ANOVA test. This proposal is applied to two porphyry copper ores with a high content of pyrite, clay, and dilution media. In addition, this study shows how other computational intelligence techniques, such as swarm intelligence, can be incorporated into this type of problem to improve the learning process of ANNs. The results gave an adjustment of over 0.98 for R2 using ANNs, in comparison to values of around 0.5 when the polynomial model of RSM was utilized. On the other hand, the application of Global Sensitivity Analysis (GSA) identified the aeration rate and P80 size as the most influential variables in copper recovery under the conditions studied. Additionally, we identified significant interactions that affect the recovery of copper, with the interactions between the aeration rate, frother concentration, and P80 size being the most important.

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El Mrabti, Iliass, Abdelhamid Touache, Abdelhadi El Hakimi, and Abderahim Chamat. "Comparison of Artificial Neural Network Model and Response Surface Methodology for Springback Prediction." MATEC Web of Conferences 343 (2021): 03012. http://dx.doi.org/10.1051/matecconf/202134303012.

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In sheet metal manufacturing, the ability to predict failures, such as springback, wrinkling and thinning, are of high importance. The objective of this study is to compare the response surface methodology (RSM) and the artificial neural network (ANN) model for predicting springback during the deep drawing process. In this investigation, friction coefficient, punch speed and blank holder force were considered as input variables. Sample data were planned by the complete factorial design and obtained via numerical simulation. To compare the RSM and ANN models, a goodness of-fit test was performed. The results of the two methods are promising and it is found that the ANN results are more accurate than the RSM results.

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Singh, Ram Sarup, and Shveta Lotey. "Enhanced exoinulinase production from Kluyveromyces marxianus YS-1 using response surface methodology." Brazilian Archives of Biology and Technology 53, no. 5 (October 2010): 1005–13. http://dx.doi.org/10.1590/s1516-89132010000500002.

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Optimization of critical medium components for exoinulinase production by Kluyveromyces marxianus YS-1 at shake-flask was investigated using response surface methodology (RSM) based on a central composite rotatable design (CCRD). A five-level with five factors CCRD was used to evaluate the influence of related factors including concentration of inulin, meat extract, calcium chloride, sodium dodecyl sulphate and medium pH. Optimum values obtained by RSM were 2% inulin, 2.17% meat extract, 0.65 mM calcium chloride, 0.10 mM sodium dodecyl sulphate and pH 5.5. Optimized medium projected a theoretical exoinulinase production of 63.61 IU/mL and biomass yield of 0.965 (OD600/10). Multiple correlation coefficient R was 0.9976 and 0.9605 for exoinulinase production and biomass yield, respectively, which being close to one, justified an excellent correlation between the predicted and experimental values. Maximum productivity of exoinulinase (64.05 IU/mL) obtained experimentally by RSM was more than double in comparison to earlier findings using classical one-variable-at-a-time technique.

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Han, Shu, Qing Long An, Ming Chen, Gang Liu, and Yun Shan Zhang. "Investigation of Surface Roughness during Turning Process Based on Response Surface Methodology." Advanced Materials Research 135 (October 2010): 243–48. http://dx.doi.org/10.4028/www.scientific.net/amr.135.243.

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The purpose of this study was to analyze the effects of cutting parameters on the surface roughness (Ra) when turning of alloy cast iron using uncoated carbide insert under dry cutting condition. The mathematical model for the surface roughness was developed by response surface methodology (RSM).Response surface contours were constructed and used for determining the optimum cutting conditions to reduce machining time without increasing the surface roughness.

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Etin-Osa, C. E., and L. M. Ebhota. "Prediction of Optimum Weld Tensile Strength Using Response Surface Methodology." European Journal of Engineering and Technology Research 6, no. 3 (April 28, 2021): 81–84. http://dx.doi.org/10.24018/ejers.2021.6.3.2422.

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Metals are often subjected to various types of stresses, usually under tensile stress, quick failure of material can be encouraged especially when poor combinations of process parameters are employed in joining of the material. Tensile strength is regarded as the maximum stress that a material can sustain under tension. The aim of this study is to predict the weld tensile strength of tungsten inert gas (TIG) mild steel welds using Response Surface Methodology (RSM), with the purpose of achieving optimum results. The input parameters considered were current, voltage, and gas flow rate. The TIG welding process was used to join two pieces of mild steel plates, after which tensile test was conducted on the specimen. The experimental result was analyzed using the RSM. Weld Tensile test of 596.218MPa with a desirability value of 95.70% was observed to be the best, resulting from the optimized process parameters of current of 120.00 Amp, voltage of 20.00 volt and gas flow rate of 12.00 L/min.

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Stefan, Daniela Simina, Cristina Orbeci, and Mircea Stefan. "Optimizing Enzymatic Biodegradation of Skins Waste Using Response Surface Methodology." Revista de Chimie 70, no. 6 (July 15, 2019): 2087–90. http://dx.doi.org/10.37358/rc.19.6.7280.

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Response surface methodology (RSM) was employed to evaluate the optimum biodegradation of pelt skin wastes (BPSW). The parameters investigated include the pH, temperature, and enzymes mixture ratio of hydrolases, proteases and oxide - reductases on biodegradation degree for Pelt skin waste. The pH varied between 4.00 � 0.2 and 7.00� 0.2 and temperature between 30-50�C. Was used three mixtures tested having the following composition expressed as ratio between E1:E2:E3. M1- (1:1:1); M2-(2:1:1) and M3-(3:1:1) expressed in mg/L. Response surface methodology (RSM) was used to evaluate the influence of each independent variable on the overall biodegradation efficiency of waste skin. Optimum biodegradation efficiency was achieved at pH=8.4, E1 concentration in the enzyme mixture 2 mg/L and temperature 42.4 0C. Biodegradation degree is 0.996. Very similar results could be obtained for optimal extraction conditions using the desirability profiles available also in STATISTICA software.

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Etin-Osa, C. E., and L. M. Ebhota. "Prediction of Optimum Weld Tensile Strength Using Response Surface Methodology." European Journal of Engineering and Technology Research 6, no. 3 (April 28, 2021): 146–49. http://dx.doi.org/10.24018/ejeng.2021.6.3.2422.

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Metals are often subjected to various types of stresses, usually under tensile stress, quick failure of material can be encouraged especially when poor combinations of process parameters are employed in joining of the material. Tensile strength is regarded as the maximum stress that a material can sustain under tension. The aim of this study is to predict the weld tensile strength of tungsten inert gas (TIG) mild steel welds using Response Surface Methodology (RSM), with the purpose of achieving optimum results. The input parameters considered were current, voltage, and gas flow rate. The TIG welding process was used to join two pieces of mild steel plates, after which tensile test was conducted on the specimen. The experimental result was analyzed using the RSM. Weld Tensile test of 596.218MPa with a desirability value of 95.70% was observed to be the best, resulting from the optimized process parameters of current of 120.00 Amp, voltage of 20.00 volt and gas flow rate of 12.00 L/min.

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Inger, Marek, Agnieszka Dobrzyńska-Inger, Jakub Rajewski, and Marcin Wilk. "The Use of Response Surface Methodology in Ammonia Oxidation Reaction Study." Journal of Chemistry 2019 (February 6, 2019): 1–8. http://dx.doi.org/10.1155/2019/2641315.

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The design of experiments (DoEs) with response surface methodology (RSM) were used to investigate the effect of operating parameters on the ammonia oxidation process. In this paper, the influence of reactor’s load and temperature of reaction as independent variables was investigated. The efficiency of NH3 oxidation to NO and N2O concentration in nitrous gases gas was identified as response variables. As a result of these studies, statistically significant models for two responses variables were developed.

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Taofiq, Oludemi, Ana Rita Silva, Cristina Costa, Inês Ferreira, João Nunes, Miguel A. Prieto, Jesús Simal-Gandara, Lillian Barros, and Isabel C. F. R. Ferreira. "Optimization of ergosterol extraction from Pleurotus mushrooms using response surface methodology." Food & Function 11, no. 7 (2020): 5887–97. http://dx.doi.org/10.1039/d0fo00301h.

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Panthakant Janepinich, Chutimon Satirapipathkul, Naparat Kasetsomboon, and Piyaphong Yongphet. "Enhancing lutein extraction from marigolds through ultrasound-assisted optimization using response surface methodology." Maejo International Journal of Energy and Environmental Communication 5, no. 1 (February 20, 2023): 14–19. http://dx.doi.org/10.54279/mijeec.v5i1.248359.

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This research aimed to enhance and optimize the ultrasound-assisted extraction (UAE) of lutein from marigold flowers. The Response Surface Methodology (RSM) was the primary optimization technique. Three key independent variables were considered to determine the best conditions for the highest lutein yield: ultrasonic amplitude, extraction temperature, and extraction time. These variables were systematically varied following the Central Composite Design (CCD). Lutein quantitation was achieved using ultraviolet-visible spectrophotometry analysis. Using both the RSM and CCD frameworks, the study established specific ranges for the operational conditions: 21.6–38.4% for ultrasonic amplitude, 23.18–56.82 °C for extraction temperature and 3.18–36.82 minutes for extraction duration. The study determined the optimal extraction conditions to be 32.76% ultrasonic amplitude, 40.08 °C extraction temperature, and 25.82 minutes of extraction time. Under these optimized conditions, the experimental lutein yield closely matched the yield predicted by the RSM model, thus confirming the model's accuracy. The UAE demonstrated a notably superior lutein yield compared to traditional extraction techniques. The RSM is a robust tool for refining and determining optimal UAE conditions for lutein extraction from marigold flowers. With its efficiency, speed, and eco- friendliness, the optimized UAE technique presents significant potential for widespread industrial use.

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Abdelhady, Saleh S., MM Atta, AA Megahed, KA Abu-Hasel, Mohammed Alquraish, Ashraf A. Ali, and Said H. Zoalfakar. "Modeling electrospun PLGA nanofibers’ diameter using response surface methodology and artificial neural networks." Journal of Industrial Textiles 52 (August 2022): 152808372211426. http://dx.doi.org/10.1177/15280837221142641.

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The present work is an attempt to model the diameter of Poly Lactic-co-Glycolic Acid (PLGA) nanofibers by utilizing response surface methodology (RSM) and artificial neural networks (ANNs). Hence, determining the optimal electrospinning process conditions to produce a minimum fiber diameter. For modelling the average diameter of nanofibers, RSM approach based on four parameters (polymer concentration, high voltage and needle tip to collector distance and spinning angle) with five-level was compared to ANN technique. In the RSM approach, central composite design (CCD) was used to determine the individual and interaction impacts of the parameters on the average diameter of nanofibers. Several ANNs of single and double hidden layers with different number of cells for each were tried to obtain the best network structure. The experimental and predicted PLGA fiber diameters using an ANN showed a strong correlation, indicating that the network topology of 4-14-1 has good predictability for analyzing factors impacting PLGA fiber diameter. The average absolute relative error for predicting PLGA nanofibers’ diameter using ANN (2.24%) is slightly less than that obtained from RSM (2.59%). The high regression coefficient between the variables and the response (R2 = 0.9636) shows a good second-order polynomial regression model for evaluating experimental data. The R2 value was 0.945, indicating that the ANN model was good fitting with the experimental results. The optimum combinations (PLGA concentration of 26 wt.%, high voltage 22 kV, needle tip to collector distance 20 cm, and spinning angle 60o) were developed by RSM model for electrospinning PLGA nanofiber that can produce fine, consistent, and high-quality nanofibers.

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Nalbur, Berrak Erol, Arzu Teksoy, Seval Kutlu Akal Solmaz, and Hilal Safiye Azak. "Modelling Dimethoate Removal by Fenton-Like Process Using Response Surface Methodology." Proceedings 2, no. 11 (August 1, 2018): 649. http://dx.doi.org/10.3390/proceedings2110649.

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The (RSM) is a useful method for optimizing analytical methods and it has been applied to evaluate independent variables in FPs. In this study, the removal of dimethoate (DMT) which is a commonly used pesticide and has a toxic effect on the environment, was evaluated in terms of oxidation and mineralization efficiency using response surface methodology (RSM) in the Fenton-like process (FLP). The obtained optimum conditions for DMT oxidation and mineralization using the FLP included DMT/Fe+3/H2O2 ratio of 0.018 mM/0.03 mM/0.15 mM and reaction time of 65 min. DMT oxidation efficiency was 78% and mineralization efficiency was 18%. The initial DMT concentration was the most significant variable affecting both the oxidation and mineralization efficiency of DMT.

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Ibrahim, Mohammad Taufik, and Nooryusmiza Yusoff. "Optimization of Condensate Fractionation Unit Using Response Surface Methodology." Applied Mechanics and Materials 625 (September 2014): 462–65. http://dx.doi.org/10.4028/www.scientific.net/amm.625.462.

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Response Surface Method involving central composite design is employed to determine the optimal configuration of nine factors for maximizing the profit of a Condensate Fractionation Unit. When compared with the results from the base case and Taguchi method, the result from RSM shows higher profits by 33.1% and 1.16%, respectively. A further benefit of 0.64% is noticed when three insignificant factors were removed from the nine-factor experiment due to interactions between factors.

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SEDARA, Adewale, and Emmanuel ODEDİRAN. "Optimization of Operational Parameters of an Improved Maize Sheller Using Response Surface Methodology." Turkish Journal of Agricultural Engineering Research 2, no. 2 (December 1, 2021): 413–24. http://dx.doi.org/10.46592/turkager.2021.v02i02.14.

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The research was carried out to optimize parameters for evaluating an improved motorize maize sheller. Statistical analysis was performed using response surface methodology (RSM) with 3 by 3 factorial experiment with 3 replicates. The three parameters are speed (850 rpm, 950 rpm and 1100 rpm), moisture content (12, 15, and 17%) and feed rate (120 kg h-1, 130 kg h-1 and 140 kg h-1) used to illustrate the ability of the machine to shell maize (throughput capacity, shelling rate and machine efficiency). Results obtained showed that for optimum throughput capacity of 630.97 kg h-1; shelling rate 485.34 kg h-1 and machine efficiency 93.86% of the machine; is maximum for 129.6 kg h-1 feed rate and moisture content 16.49% and machine speed of 1026.9 rpm. The machine can be used on commercial farms with these operational results.

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Journal articles on the topic 'Response Surface Methodology (RSM)'

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