Combination Of Response Surface Methodology Research Articles

Efficient optimization of high-dose formulation of novel lyophilizates for dry powder inhalation by the combination of response surface methodology and time-of-flight measurement.

Inhalation of proteins/peptides has recently received attention as various biopharmaceuticals have emerged on the market. Novel lyophilisates for dry powder inhalation (LDPIs), which are aerosolized by air impact, have been reported and LDPIs are considered an attractive option for the pulmonary administration of biopharmaceuticals. However, desirable disintegration and aerosolization properties have been unavailable in high-dose formulations, which has been a critical issue. This study aimed to investigate high-dose LDPIs and their optimization. In the present study, lysozyme (Lysoz) was used as a stable model protein and formulated with various amino acids. Furthermore, response surface methodology (RSM) and time-of-flight measurement were applied for efficient optimization. Superior disintegration and aerosolization properties were confirmed in the LDPIs with phenylalanine (Phe) and leucine (Leu). RSM results revealed that 0.5mg/vial of Phe and 1.0mg/vial of Leu are the optimal quantities for high-dose formulation. Based on these optimum quantities, high-dose LDPI formulations were prepared and the maximum formulable quantity of Lysoz with acceptable inhalation performance was confirmed to be 3.0mg/vial. The results suggest that LDPI can cover the milligram-order pulmonary administration of proteins/peptides. LDPIs are expected to have biopharmaceutical applications.

Structural design of an agricultural backhoe using TA, FEA, RSM and ANN

An agricultural backhoe is an important machine designed for multiple assignments in agriculture and livestock. Due to severe working conditions, agricultural backhoe elements are subjected to high loads. Therefore, a structural design must provide a safe machine under all loading conditions at minimum weight and cost. In this work, a 3D model of an agricultural backhoe was proposed, to be used in tractors category II according to the classification of the ASABE S217 standard. In the structural design of the agricultural backhoe Theoretical Analysis (TA), Finite Element Analysis (FEA), Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were used. A finite element model of the agricultural backhoe in the critical position was developed, considering a maximum breakout force according to SAE J1179 standard. The finite element model was theoretically validated through a comparison between numerical and theoretical normal stresses at twelve strategic points of the agricultural backhoe components, finding a maximum absolute difference of 7.0 %. Also, a mass reduction of the principal backhoe components (bucket, arm, boom and links) was done, using Central Composite Design (CCD) under RSM in a commercial FE software and ANN technique with Neural Lab software. A mass reduction of the initial agricultural backhoe model of 24.8% (from 446.3 kg to 335.4 kg) was achieved using the RSM technique, with an increment on the maximum von Mises stress of 6.8% (from 117.4 MPa to 125.4 MPa), as well as a reduction of the minimum safety factor of 4.8% (from 2.94 to 2.80). ANN allowed predicting the results obtained by RSM to reduce the boom mass with a correlation coefficient of 0.96, using 80.0% of data and around 13.0% less time. This study showed that a combination of RSM and ANN techniques with TA and FEA provides useful results to reduce the structural mass of agricultural equipments, thus it is recommended to decrease the number of numerical case studies and the solution time with satisfactory results.

Production of bio-oil from coir pith via pyrolysis: kinetics, thermodynamics, and optimization using response surface methodology

This study evaluates the potentiality of coir pith, an agro-industry by-product, as a low-cost feed-stock for the production of bio-fuels and other value-added chemicals. Thermogravimetric analysis was done to evaluate kinetics, thermodynamic, and mechanistic models of coir pith pyrolysis process. Optimal pyrolysis condition was fixed by using response surface methodology (RSM) in combination with central composite design (CCD). Pyrolysis experiments were carried out by using a miniature fixed-bed reactor at the temperature range of 200–400 °C with the heating rates and nitrogen flow rate ranges of 20–40 °C/min and 70–200 ml/min, respectively. As suggested by the Design expert software, maximum yield of bio-oil (29.31%) can be obtained at temperature of 349.14 °C, heating rate of 21.58 °C/min, and nitrogen flow rate of 196.61 ml/min, which was very much similar to the experimental yield (29.02 ± 0.05%). The bio-oil obtained at this condition was characterized by elemental analysis and different spectroscopic and chromatographic techniques including 1H-NMR, FTIR, and GC-MS. The calorific value of bio-oil was found to be 28.38 MJ/kg. Characterization of bio-oil obtained at the optimum process condition indicates that produced bio-oil is a combination of aliphatic as well as aromatic hydrocarbons which can be represented by the empirical formula of CH1.80 N0.04 O0.35. This investigation also revealed that the kinetic and thermodynamic analyses can correctly predict the possible pyrolysis temperature range for coir pith pyrolysis. The results obtained from the present investigation therefore suggest the suitability of coir pith as a potential feedstock for the conversion of energy and value added chemicals.

Reactive Extraction of Malic Acid using Trioctylamine in 1\u2013Decanol: Equilibrium Studies by Response Surface Methodology Using Box Behnken Optimization Technique

Reactive extraction is a significant technique employed for the removal of organic acids such as carboxylic acid which are usually present in low concentrations in aqueous solutions. This technique was explored by applying Response Surface Methodology (RSM) in process parameter optimization for malic acid recovery from aqueous streams using Trioctylamine as extractant and 1-decanol as organic diluent. Malic acid, a C4 dicarboxylic acid has a wide variety of applications in the polymer, food, chemical and pharmaceutical industries. The optimization of the response function: extraction efficiency was systematically carried out using three process parameters for reactive extraction: temperature, initial malic acid concentration and extractant (Trioctylamine) composition. Response Surface Methodology in combination with Box-Behnken design involving seventeen experimental runs was employed for malic acid reactive extraction in this study. A statistical second-order polynomial predicted an extraction efficiency of 97.53%. The optimum conditions of the process variables were found to be: temperature: 304.73 K, acid concentration: 0.25 kmol/m3, Trioctylamine composition: 23.54% (v/v). Under these optimum conditions, the experimental response of extraction efficiency of 93.25% was obtained. The experimental results obtained was in close conformity with the predicted values by numerical optimization using Response Surface Methodology. These findings can pave the way for the reactive separation process design for recovery of carboxylic acids from dilute aqueous waste streams as well as a fermentation broth.

Optimization of Microwave-Assisted Extraction Process of Callicarpa candicans (Burm. f.) Hochr Essential Oil and Its Inhibitory Properties against Some Bacteria and Cancer Cell Lines

Callicarpa candicans (Burm. f.) Hochr. (Callicarpa cana L.) is a medicinal plant that is distributed mainly in the tropics and subtropics of Asia and finds a wide range of uses in traditional medicine. In this study, we attempted and optimized the microwave-assisted hydro-distillation (MAHD) process to obtain essential oil from the leaves of C. candicans. In addition, the obtained oil was analyzed for volatile composition by gas chromatography–mass spectrometry (GC-MS) and assayed for bioactivity against several bacteria and cancer cell lines. To optimize the extraction process, response surface methodology (RSM) in combination with central composite design (CCD) was adopted. Experimental design and optimization were carried out with respect to three experimental factors including the ratio of water to raw material, extraction time, and microwave power. The optimal extraction conditions were obtained as follows: water to raw material ratio of 6/1 (v/w), extraction time 42 min, and microwave power 440 W. Composition determination of the obtained C. candicans essential oil indicated the presence of predominant components including caryophyllene <b-> (10.45%), cadinene <d-> (10.28%), gurjunene <a-> (8.95%), muurolene <g-> (8.92%), selinene <a-> (7.06%), selinene <b-> (5.59%), and copaene <a-> (5.40%). In comparison with the essential oils obtained via traditional hydro-distillation method, the essential oil extracted by MAHD exhibited superior anti-proliferative activity on all tested cancer cell lines. Current results imply that the MAHD is capable of recovering biologically-active natural products of greater quantity than that recovered by the conventional distillation.

Reactive extraction of propionic acid using trioctylamine in 1–decanol by response surface methodology optimization technique

Abstract Reactive extraction, a novel technique, was experimentally investigated for the removal of propionic acid, which is usually present in low concentrations in aqueous solutions. The experiments were conducted according to statistical design to develop an appropriate regression model. This was aimed at analyzing and optimizing the process variables and extraction efficiency for propionic acid reactive extraction from dilute aqueous streams using trioctylamine as extractant and 1-decanol as organic diluent. Response surface methodology in combination with Box–Behnken design involving 17 experimental runs was utilized for the propionic acid reactive extraction in this study. Three independent process variables were chosen as temperature (T), initial propionic acid concentration (CPAO) in the aqueous phase and trioctylamine composition (CTOA) in the organic phase. The statistical design analysis demonstrated that the propionic acid concentration and TOA composition had a significant effect while temperature had an insignificant effect on the response value as well as an interactive and quadratic effect on the response. The optimum conditions for propionic acid extraction were established as T = 300.752 K, CTOA = 18.252 %v/v, CPAO = 0.408 kmol/m3. Under these optimum conditions, the propionic acid experimental extraction yield was 89.788 %, which was in close conformity with the predicted yield value of 91.939 %.

Control of porous properties of ambient dried sodium silicate-based aerogels using response surface methodology

In this work, response surface methodology (RSM) in combination with central composite design was employed to study the effect of independent variables on the nanoporous characteristics of silica aerogels prepared via ambient pressure drying. Different techniques such as attenuated total reflection–Fourier transform infrared, field-emission scanning electron microscopy, Brunauer–Emmett–Teller, and thermogravimetric differential thermal analyses were used to characterize the aerogel samples. The independent variables in this study were water:Na2SiO3 and trimethylchlorosilane (TMCS):Na2SiO3 volume ratio. The results showed that contemporaneous change of these factors affects the porous structure of silica aerogels considerably. Actually, when water:Na2SiO3 and TMCS:Na2SiO3 volume ratio were 6–7 and 0.8–1.4, respectively, specific surface area was maximum (∼660 m2 g−1). In addition, in this range, mean pore diameter was minimum, approximately 18 nm. Generally, the increasing water:Na2SiO3 volume ratio (to about 8), and the simultaneous increase of TMCS:Na2SiO3 volume ratio (to about 1.6), led to the decrease of mean pore diameter, while the density of the aerogels increased slightly. The combination of using low-cost precursors and ambient pressure drying method followed by applying RSM for producing silica aerogels with optimized properties is a key step toward commercializing these materials. Such a porous structure is ideal for thermal insulation applications.

Application of Response Surface Methodology for Ethanol Conversion into Hydrocarbons Using ZSM-5 Zeolites

The ethanol conversion into hydrocarbons (light olefins and aromatics) using alkali-treated HZSM-5 with different SiO2/Al2O3 ratios (23, 38, and 53) zeolites was evaluated. The desilicated SAR 38 zeolite exhibited significant growth on the external surface area (61–212 m2/g) and the mesopore volume (0.07–0.37 cm3/g) without significate reduction on XRD crystallinity (93%). All catalysts were active on the ethanol conversion into hydrocarbons. At the same set of variables, the alkali-treated HZSM-5 zeolites showed a better conversion and a high selectivity to C4–C9 hydrocarbons when compared to the parent microporous zeolites. Only the parent HZSM-5 zeolite (SAR 53) was chosen for the statistical study using the standard response surface methodology in combination with the central composite design. It was found that maximum BTEX (benzene, toluene, ethylbenzene, and xylenes) and minimum ethylene production were reached for the following conditions: temperature 450 °C, pressure 20 bar, and WHSV (weight hourly space velocity) 5 h−1.

Simultaneous degradation of nitrogenous heterocyclic compounds by catalytic wet-peroxidation process using box-behnken design

The present study investigates the feasibility of nitrogenous heterocyclic compounds (NHCs) (Pyridine-Quinoline) degradation by catalytic wet peroxidation (CWPO) in the presence of nanoscale zerovalent iron supported on granular activated carbon (nFe<sup>0</sup>/GAC) using statistical optimization technique. Response surface methodology (RSM) in combination with Box-Behnken design (BBD) was used to optimize the process parameters of CWPO process such as initial pH, catalyst dose, hydrogen peroxide dose, initial concentration of pyridine (Py) and quinolone (Qn) were chosen as the main variables, and total organic carbon (TOC) removal and total Fe leaching were selected as the investigated response. The optimization of process parameters by desirability function showed the ~85% of TOC removal with process condition of initial solution pH 3.5, catalyst dose of 0.55 g/L, hydrogen peroxide concentration of 0.34 mmol, initial concentration of Py 200 mg/L and initial concentration of Qn 200 mg/L. Further, for TOC removal the analysis of variance results of the RSM revealed that all parameter i.e. initial pH, catalyst dose, hydrogen peroxide dose, initial concentration of Py and initial concentration of Qn were highly significant according to the <i>p</i> values (<i>p</i> < 0.05). The quadratic model was found to be the best fit for experimental data. The present study revealed that BBD was reliable and effective for the determination of the optimum conditions for CWPO of NHCs (Py-Qn).

Optimization of Process Parameters for Cholesterol Oxidase Production by Streptomyces Olivaceus MTCC 6820

Background:Streptomyces olivaceusMTCC 6820 is a potent microorganism for cholesterol oxidase (ChOx) production through the submerged fermentation process. Statistical optimization of the process parameters for submerged fermentation enhances the production of enzymes.Objective:This work is aimed to optimize the culture conditions for the fermentative production of cholesterol oxidase byStreptomyces olivaceusMTCC 6820 using combined Response Surface Methodology (RSM) and Artificial Neural Network (ANN) techniques.Methods:The ChOx production (U/ml) was modeled and optimized as a function of six independent variables (culture conditions) using RSM and ANN.Results:ChOx production enhanced 2.2 fold,i.e1.9 ± 0.21 U/ml under unoptimized conditions to 4.2 ± 0.51 U/ml after the optimization of culture conditions. Higher coefficient of determination (R2= 97.09 %) for RSM and lower values of MSE (0.039) and MAPE (3.46 %) for ANN proved the adequacy of both the models. The optimized culture conditions predicted by RSMvs. ANN were pH (7.5), inoculum age (48 h), inoculum size (11.25 % v/v), fermentation period (72 h), incubation temperature (30°C) and shaking speed (175 rpm).Conclusion:The modeling, optimization and prediction abilities of both RSM and ANN methodologies were compared. The values of Pearson correlation coefficient (r) (ANN0.98> RSM0.95), regression coefficient (R2) between experimental activity, RSM and ANN predicted ChOx activity, respectively (ANN0.96> RSM0.90) and Absolute Average Deviation (AAD) for (ANN3.46%< RSM9.87%) substantiated better prediction ability of ANN than RSM. These statistical values indicated the superiority of ANN in capturing the non-linear behavior of the system.

Research on Superconducting Magnet in a Superconducting Synchronous Generator

Design and test of superconducting magnet (SM) for a superconducting synchronous generator (SSG) are studied in this paper. First, a suitable superconducting material is selected to make SM by analyzing the characteristics and application background of the five practical superconducting materials, and the applicability and feasibility of the selected superconducting materials are demonstrated. Second, the initial structural parameters of the SM are obtained by finite element method (FEM). In addition, the influence of structural parameters of SM on the performance of SSG is analyzed by simulation. Then, an optimal algorithm combining response surface methodology (RSM) and particle swarm optimization (PSO) is proposed to optimize the structure of SM in order to give full play to the advantages of SM. The simulated results verify that the proposed optimal algorithm is feasible and effective. Finally, the prototype of SM is made by the optimized size, and the SM is tested at a low temperature to obtain the critical temperature and critical current of the SM; the experimental results verify that the designed SM can meet the requirements of SSG.

Thermal-hydraulic analysis of sinusoidal fin-based printed circuit heat exchangers for supercritical CO2 Brayton cycle

This paper presents the thermo-hydraulic performance analysis of the printed circuit heat exchangers (PCHEs) with new channel geometries. A new channel geometry for the PCHEs) has been proposed based on a staggered arrangement of sinusoidal fins. Initially, thermal and hydraulic performance of the proposed channel geometry was computed numerically and was compared with the performance of the conventional zigzag channel geometry using supercritical carbon dioxide (sCO2) as a working fluid. Later, the suggested geometry was optimized using response surface methodology in combination with the genetic algorithm. Lastly, thermal and hydraulic performance of the optimized channel geometry was computed numerically along with the zigzag channel geometry for a wide range of Reynolds number based on which heat transfer and pressure drop correlations were proposed. Computed results show that hydraulic performance of the optimized proposed channel geometry is up to 2.5 times better in comparison with the conventional zigzag channel geometry with identical thermal characteristics. Moreover, the overall performance of the optimized proposed channel geometry was found up to 21% and 16% higher for the cold and hot side, respectively.

Selective glucose permeability in presence of various salts through tunable pore size of pH responsive PVDF-co-HFP membrane

Flat sheet, asymmetric pH responsive poly-(vinylidene-fluoride-co-hexafluoro-propylene) (PVDF-co-HFP) membrane was synthesized through phase inversion technique and utilized for permeation study of glucose in presence of various salts. Characterization of the membrane was performed using Field emission scanning electron microscope (FESEM), Thermogravimetric analysis (TGA), Differential scanning calorimeter (DSC) and Mercury intrusion porosimeter (MIP) analysis. Pure water flux (PWF) varied from 142 L/m2 h to 58 L/m2 h with increase in pH indicating swelling and pore blocking activity of the pH responsive membrane. MIP analysis confirmed the variation of pore size and pore distribution of the membrane at different pH. Optimization of the variables (pH, NaCl and KHCO3) for maximizing glucose removal was performed using Design expert software 9.0 TRIAL, through ANOVA (analysis of variance) using the combination of response surface methodology (RSM) and central composite design (CCD). Glucose removal by the pH responsive membrane at a concentration of 8.3 mmol/L (higher than normal glucose concentration after meal), through dialysis technique was obtained maximum of 60.67% ± 3.1 at pH 12 in presence of 0.1 (M) NaCl and KHCO3 solution. At normal human body fluid pH of 7.4 the removal was around 54.3% ± 3.5 (%).

Transverse flux permanent magnet generator design and optimization using response surface methodology applied in direct drive variable speed wind turbine system

Recently, Transverse Flux Permanent Magnet Generators (TFPMGs) have been proposed as a possible generator in direct drive variable speed wind turbines due to their unique merit. Generally, the quality of output power in these systems is lower than multi stage fixed speed systems, because of removing the gears, so it’s important to design these kinds of generators with low ripple and lowest harmful harmonics and cogging torque that is one of the most important terms in increasing the quality of output power of generator. The objective of this paper is introducing a simple design method and optimization of high power TFPMG applied in vertical axis direct drive wind turbine system by lowest possible amplitude of cogging torque and highest possible power factor, efficiency and power density. For this reason an optimum method called combined response surface methodology (RSM) and design of experiment and in order to extract the output values of generator and sensitivity analysis for design and optimization, 3D-Finite element model, was applied. This method has high accuracy and gives us a better insight of generator performance and presents back EMF, cogging torque, flux density and FFT of this TFPMG. This study can help designers in design approach of such generators.

Flux switching permanent magnet generator design and optimization using response surface methodology

Flux Switching Permanent Magnet Generators (FRPMGs) have been used increasingly in direct drive variable speed wind turbines due to their merit such as their high torque density, easy flux weakening operation and robust rotor structure. Generally, the quality of output power in direct drive systems is lower than multi stage fixed speed systems, because of removing the gears, so it’s important to design these kinds of generators with low ripple and lowest harmful harmonics and cogging torque. This aim is one of the most important terms in increasing the quality of output power of generator simultaneously with back-EMF improvement. The objective of this paper is introducing a simple design method and optimization of high power FRPMG applied in direct drive wind turbine system by lowest possible amplitude of cogging torque and highest possible power factor, efficiency and power density. For optimization reason an optimum method called combined response surface methodology (RSM) and design of experiment has been applied. Also in order to extract the output values of generator and sensitivity analysis for design, 3D-Finite element model, was used. This method has high accuracy and gives us a better insight of generator performance and presents back EMF, cogging torque, flux density and FFT of the FSPMG. This study can help in design approach of such machines.

Optimization of the protein extraction method of goat meat using factorial design and response surface methodology

Protein extraction from goat meat was carried out based on the combination of response surface methodology and factorial design to optimize the variables: temperature (25–50 °C), extraction time (8–20 min), volume (3–10 mL) and extractor concentration (0.05–0.1 mol L−1). The proposed model did not present a lack of fit, explaining 96% of the total data variance (R2 = 0.96). The optimum extraction conditions were: 0.05 mol L−1 for extractor concentration, extraction time of 10 min, temperature of 44 °C and extractor volume of 3.5 mL. The protein content (19.3 g/100 g) obtained by the optimized method was higher than some results reported in the literature. HPLC-SEC-DAD analysis revealed that the extraction conditions used did not significantly modify the protein structure. The proposed method proves to be simple, fast, robust, cheap and adequate for native protein extraction, being a potential approach for proteomic research focusing in goat meat.

A semisynthetic approach for the simultaneous reaction of grape seed polymeric procyanidins with catechin and epicatechin to obtain oligomeric procyanidins in large scale.

Polymeric procyanidins (PPCs) were the major constituents of procyanidins, while they have poor bioactivity. To better utilize PPCs, a semisynthetic approach for converting PPCs to oligomeric procyanidins (OPCs) was proposed. Grape seed PPCs were simultaneously reacted with catechin (C) and epicatechin (EC) under acid condition. Combining response surface methodology (RSM) and single-factor experiments, an optimized semisynthetic condition was confirmed with the ratio of PPCs with C and EC of 1:1:1, temperature of 40 °C, reaction time of 20 min and 0.1 M methanolic HCl. High-speed counter-current chromatography (HSCCC) was adopted to obtain three fractions from semisynthetic products and preparative-HPLC was used to isolate individual procyanidins. Thirteen B-type procyanidins including monomers, dimers and trimers were got with high yield of 0.8-17.8 mg from 200 mg semisynthetic products and high purity over 91%. The developed semisynthesis combined with separation method was efficient to obtain individual OPCs in preparative scale.

Catalytic co-gasification of coconut shells and oil palm fronds blends in the presence of cement, dolomite, and limestone: Parametric optimization via Box Behnken Design

In this study, Response Surface Methodology (RSM) in combination with Box-Behnken Design (BBD) was used to optimize the temperature, catalyst loading, and blending ratio for a co-gasification process. The catalytic co-gasification of coconut shells (CS) and oil palm fronds (OPF) blends was performed in the presence of cement, dolomite, and limestone catalysts. A combined effect of temperature, catalyst loading, and blending ratio on production of H2, CO, and tar formation was investigated by using a BBD approach. The results showed the strongest influence of the process temperature on H2 and CO yield, and tar formation followed by the catalyst loading and blending ratio. A catalyst loading of 30 wt%, process temperature of 900 °C and blending ratio of CS50:OPF50 were predicted as the optimized conditions for the reported co-gasification results. The highest H2 yield of 20.64 vol% was produced during catalytic co-gasification of the blended biomass with limestone followed by the cement (18.22 vol%) and dolomite (14.99 vol%). Under optimized process conditions, lowest tar concentration of 0.87 g/Nm3 was obtained with limestone follow by the cement (1.42 g/Nm3) and dolomite (2.13 g/Nm3). However, blending ratio did not affect H2, CO yield, and tar formation appreciably. Conclusively, the mixing ratio of CS and OPF would have a negligible role in controlling the process output.

Desiccant-wheel optimization via response surface methodology and multi-objective genetic algorithm

A two-step computational framework based on the combination of response surface methodology and multi-objective optimization is proposed to model the outlet-air state of desiccant wheels and subsequently optimize their operation. Regeneration temperature, surface area ratio, rotational speed, and wheel diameter are considered as decision parameters in the genetic algorithm. The central composite design and response surface methods have been employed to design experiments, establish predictive empirical models, and determine interactive effects of decision variables on response variables—process outlet temperature and humidity ratio. Several experiments have been performed to verify applicability of the proposed methodology and validate obtained results. A value of the coefficient of determination exceeding 0.95 demonstrates high reliability and accuracy of the modeling process involved in the proposed methodology. Results obtained demonstrate greater dominance of the surface area ratio compared to other decision variables in terms of their influence on response variables. After successful validation against experimental data, the developed models have been considered as a combination of two objective functions. A fast and elitist non-dominated sorted genetic algorithm II-based optimization technique has been employed to simultaneously determine optimum values of decision variables. A Pareto-optimum front has been presented to select the best value of each decision parameter from available points of optimum operation, and a valuable equation for Pareto-optimal points has been deduced for each material to assist designers develop an optimum design of desiccant cooling systems.

Using response surface methodology in combination with Plackett-Burman design for optimization of culture media and extracellular expression of Trichoderma reesei synthetic endoglucanase II in Escherichia coli.

Cellulases like endoglucanase II (EGII) from Trichoderma reesei are the industrial enzymes responsible for breakdown of cellulosic materials. Due to its importance for production of eco-friendly commercial products such as alternative biofuels, industrial EGII production and optimization of its production conditions merit consideration. The gene responsible for EGII expression was designed and sub-cloned in to pET26b expression vector and transformed into BL21 (DE3) pLysS cells. Protein expression and purification was followed by a RSM design (20 experiments) to optimize the IPTG Concentration, post induction period and cell density (OD600). Thereafter, another RSM design (20 experiments) was performed to find and optimize the most important permeabilizing factors to achieve higher extracellular EGII expression. The EGII expression levels were assessed by Ghose method. The EGII gene was sub-cloned and protein expression and purification were successfully performed. The RSM experiments indicated that 0.331mM for IPTG Concentration, 10.89H for post induction period and 3.41 for cell density (OD600) were the optimum culture. Glycine (0.99%), Triton X-100 (0.73%) and CaCl2 (0.232) have been assigned as the most effective membrane permeabalizing factors. Optimization of culture medium components has led to a 3.06 fold increase in extracellular expression of EGII. RSM is an amenable method to optimize the expression of commercially significant enzymes. Our results indicated that optimization of IPTG concentration, post induction period and cell density along with glycine, Triton X-100 and Ca2+ concentration could lead to more cost effective industrial production of EGII.