Full Factorial Central Composite Design Research Articles

Optimization of chlorogenic acid extraction from Elm tree, Ulmus minor Mill., fruits, using response surface methodology

Elm tree, Ulmus minor Mill. belongs to the Ulmaceae family. Some main compounds in this plant are including mucilage, tannins, caffeic acid derivatives, especially chlorogenic acid (CGA) and sterols. Among them, caffeic acid derivatives, especially chlorogenic acid (CGA) with widespread usage in food, cosmetic and pharmaceutical industries, caught our attention and we decided to detect, quantify and finally optimize its extraction from Elm tree, (Ulmus minor Mill.) fruits. Herein, the extraction process was optimized by means of response surface methodology (RSM). Various factors such as temperature, solvent percentage, solid to solvent ratio and extraction time can be effective in an extraction. Screening and selection of important factors was accomplished by 2- level full factorial design and the result of normal probability plot. Based on the results the effect of time was not important and in the next stage of the study using RSM was omitted. In this step, 3-level full factorial central composite rotatable design (CCRD) was used for optimization, in which the temperature, ethanol percent, and solvent ratio were relevant independent variables. Based on the practical results by HPLC and statistical analysis, the optimum conditions for maximum yield was when temperature, solvent to solid ratio and solvent percent were equal to 54.98 °C, 40 (mL/g) and 70% (v/v), respectively, and its desirability function was 0.94.

Optimization of Diesel Biodegrading Conditions Using Response Surface Methodology Based on Central Composite Design

During biodegradation of petroleum products which are the main sources of aromatic compounds, optimization is the major strategy that enhances the performance of the participating organisms. This research aimed at optimizing diesel degrading conditions using the response surface methodology (RSM) based on full factorial central composite design (CCD). Bacteria were isolated from the diesel contaminated soil which were screened based on diesel oil tolerance. Bacteria resting cells (1.5 × 105 cells/ml) of the screened strains were used to formulate consortia using mathematical permutation approach on Bushnell Haas Agar before being tested on heavy metals co-contaminants. Optimization based on CCD was carried out to pH, temperature, salinity, and substrate concentration. The results indicate a total of 47 bacteria were isolated where 4 were finally screened based on their survival at the sole expense of 4% v/v diesel with high growth populations. These bacteria were identified as Alcaligenes sp., Ochrobactrum sp., Alcaligenes aquatilis, and Alcaligenes faecalis UMYU001 (MN519483.1) which were used for the formulation and selection of effective degrading consortium. The selected consortium performed better even in the presence of more than 1 g/L of different heavy metals co-contaminants producing population higher than 1.6 × 104cfu/mL (p-value = 0.0037). Based on the CCD results, parameter values of 7.14 pH, 32 °C temperature, 2.58 g/L NaCl, 3.74% v/v diesel substrate were found to be the optimum conditions for the diesel biodegradation. The interactions among these parameters generated 8.4 × 106cfu/ml which were validated by correlating the predicted and actual experimental results.

Optimization of WEDM process parameters for D3 die steel using RSM

Wire electrical discharge machining is widely used in fields like dies, punches, aerospace and automotive industries for machining conductive, exotic, high strength and temperature resistive materials with better precision and accuracy. Here, to achieve optimal performance is very difficult as there are many process parameters that determine the output characteristics. The objective of the present work is to predict the optimal set of process parameters such as current (I), pulse on/off time (TON/TOFF), wire tension and wire feed to achieve minimum Surface roughness (SR), wire consumption rate (WCR) and maximum material removal rate (MRR). In this work, experiments were carried out by pulse arc discharges generated between brass wire and specimen (D3 die steel) suspended in deionized water dielectric. The experiments were designed based on the five factors and its five levels using full factorial central composite design based on Response Surface Methodology. 52 runs of experiments were constructed based on central composite design procedure and results of the experimentation were analyzed by MINITAB software analytically as well as graphically. Second order regression model has been developed for predicting surface roughness (SR), wire consumption rate (WCR) and material removal rate (MRR) in terms of interactive and higher order machining parameters through response surface methodology. The results revealed that wire tension, current, and their interactions have significant effects on SR, whereas, pulse on time and current have significant effects on MRR and also been observed that wire feed and interaction between current and pulse off time have significant effects on WCR. Finally, the parameters were optimized for maximum MRR, minimum WCR with the desired surface roughness value using desirability function approach.

Towards Potential Removal of Malachite Green from Wastewater: Adsorption Process Optimization and Prediction

Granular activated carbon (GAC) is utilized as an adsorbent for the malachite green (MG) dye removal from aqueous solutions. The GAC was characterized by scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) to realize the GAC chemical and physical features effects on the adsorption efficiency. Batch adsorption processes were carried out with different variables like pH, GAC dose, initial MG concentration and time. The response surface methodology (RSM) was used to design the experiments, model the adsorption process, optimize the operating conditions and predict the response. A 24 full factorial central composite design (CCD) was performed for the experimental design and the analysis of the results. Analysis of variance (ANOVA) was employed to determine the significance of the factors and explore the interaction between the various experimental parameters. An empirical model was derived to correlate the experimental results and predict the behavior of the GAC for the adsorption process. The model showed a good agreement with the experimental results of R2 = 0.9968 and evidenced that the optimum operating parameters are pH 10, 2 g GAC/L, 200 mg/L of MG initial concentration and 113 min adsorption time for complete removal of MG.

Multi-objective optimization of drilling EDM process parameters of LM13 Al alloy–10ZrB2–5TiC hybrid composite using RSM

In this study, a newly engineered stir-cast LM13 aluminium alloy-based hybrid composite (5 wt% of TiC and 10 wt% of ZrB2) is used as workpiece and its machinability investigation is carried out using EDM (electric discharge machining) drilling route with copper electrode. During experimentation, the process variables, namely current (I), pulse on-time (Ton) and pulse off-time (Toff), are varied and the output performance characteristics, viz. material removal rate (MRR), electrode wear rate (EWR) and dimensional accuracy, i.e. overcut (OC), are measured. The series of experiments (20 runs) are formulated through the adoption of response surface methodology (RSM)-based full-factorial central composite design. To recognize the correlation between the process variables and performance characteristics, a mathematical model is developed for each response. Subsequently, adequacy of the proposed models is verified using analysis of variance (ANOVA). Moreover, ANOVA is employed to identify the significantly influencing process parameters over the performance characteristics. From the analysis of results, it is inferred that the current has the most dominant effect on MRR and EWR, whereas OC is highly influenced by Ton. Composite desirability function approach of RSM is utilized to find the optimum set of process parameters in order to satisfy the desired multi-performance characteristics (such as maximizing MRR, minimizing EWR and OC) for obtaining effective holes on hybrid LM13–10ZrB2–5TiC composite. Finally, optimized results are validated with the experimental results to determine the competence of adopted desirability approach.

Removal of color from real textile dyeing effluent utilizing tannin immobilized jute fiber as biosorbent: optimization with response surface methodology.

The present study explored an efficient technoeconomic method for treating intensely colored dyeing effluents from a commercial source. Firstly, the adsorption efficacy of jute fiber (JF) was enhanced through grafting with tannin, a natural polyphenol, via incorporation of active epoxy groups by epichlorohydrin onto fiber surface. The effect of different experimental parameters (e.g., initial pH, adsorbent dose, temperature, and contact time) on extent of color removal was evaluated performing batch studies. A full factorial central composite design (CCD) in response surface methodology (RSM) was applied to optimize the decolorization process for achieving maximum color removal (99.5%) at pH 4.9, adsorbent dose 11.8g/L, temperature 30°C, and time of contact 117.8min. The isotherm and kinetic studies of the process revealed that Langmuir model and pseudo-second-order model provided best fit, yielding high correlation coefficients (R2 > 0.997). Significant desorption (76%) of the spent adsorbent by 0.1M NaOH solution suggested that this tannin-modified JF can find a prospective practical application as a novel, inexpensive, and potential bioadsorbent to treat the dyeing effluent.

Optimization of Bio-oil Production from Empty Palm Fruit Bunches by Pyrolysis using Response Surface Methodology

The need for fuel oil continues to increase in line with the increasing number of human populations and the growth rate of dependence on fuel oil. Bio-oil is a condensed-liquid mixture that results from the thermal derivation of biomass containing hemicellulose, lignin, and cellulose. This research developed an optimization of the operation condition of bio-oil from empty palm fruit bunches (OPEFB) using a modified pyrolysis reactor. The temperature and mass of empty palm fruit bunches were the two parameters considered in this study. Optimization was carried out on process parameters using the surface response methodology (RSM) and variance analysis (ANOVA). The significance of the different parameters and the effect of the relationship between parameters on the bio-oil yield is determined using a full factorial central composite design. The optimal operation condition of pyrolysis was found to be 570.71 oC, and the mass of empty palm fruit bunch 420.71 gr. Predictions from the optimum variable of operating conditions produce a bio-oil yield of 5.58%. The actual bio-oil yield on the optimum condition that was be validated is 5.6 %. The chemical composition of bio-oil obtained was evaluated by GCMS to ensure its characterization as a fuel.Keywords: Empty palm fruit bunches, Bio-oil, Pyrolysis, Response Surface Methodology, Optimization

Optimization of extracellular lipase production by halotolerant Bacillus sp. VITL8 using factorial design and applicability of enzyme in pretreatment of food industry effluents

The effect of macro and micronutrients of media components on lipase production by Bacillus sp. VITL8 was investigated using classical as well as statistical methods. Initially, the carbon source, nitrogen source, inducer and metal ions that affect lipase production were selected using the classical approach. Subsequently, selected nutrients along with other key factors (such as pH, agitation rate, gum acacia and tween 80) were investigated using Placket Burman design. Finally, three significant factors, viz., olive oil, peptone and tween 80 were studied using a 22 full factorial central composite design. Under optimized condition [6% (v/v) of olive oil, 0.7% peptone, 0.9% tween 80 and 25 h of incubation], the enzyme production was found to be 2.2 times higher with an overall enzyme production of 325.0 ± 1.4 U mL−1. Laboratory scale experiment proved that the enzyme could be utilized for pretreatment of food industry effluent rich in fat and oil (dairy, bakery and poultry). The enzyme was capable of hydrolyzing more than 50% of the initial fat present in all these effluents and enabled the reduction in the levels of biological oxygen demand (BOD) and chemical oxygen demand (COD) of the effluent samples. The study thus reveals the utility of the lipase produced by the halotolerant bacterium Bacillus sp. VITL8 in the pretreatment of industrial effluents contaminated with oil and fat.HighlightsLipase production was enhanced by 2.2-fold using statistical methodsOne of the few reports on lipase production by a halotolerant bacterium, especially by Bacillus sp.Production of 325.0 ± 1.4 U mL−1 lipase within 25 h by a halotolerant bacteriumPretreatment of food industry effluents using Bacillus sp. VITL8 lipaseImprovement in effluent quality within 8 h of treatment

Extraction of castor oil from castor seed for optimization of biodiesel production

This research was carried out to optimize biodiesel production from castor oil using 24 full factorial central composite design (CCD). Transesterification method was used for the biodiesel production from castor using KOH & NaOH were used as catalysts. Physico-chemical properties including density, kinematic viscosity, acid value, saponification value, iodine value and pour point. The results were determined both on the castor oil and biodiesel produced. The predicted optimum conditions for the production of castor oil biodiesel are; reaction time of 60 minutes at the temperature of 60°C, catalyst concentration of 3.5 g and a methanol/oil molar ratio of 5:1. The biodiesel yield was 99.76% and the result of the measured properties of biodiesel was compared with the international standards of EN14214 and ASTM D6751. The weight composition of the fatty acid and methyl ester were both determined by the Gas Chromatography (GCMS)

Efficient Photoelectrocatalytic Degradation of BTEX Using TiO2/CuO/Cu2O Nanorod-Array Film as the Photoanode and MWCNT/GO/Graphite Felt as the Photocathode

Wastewater treatment challenges by conventional methods have necessitated the need for alternative/complementary methods that are environmentally safe and efficient especially towards recalcitrant organic pollutants. In this regard, a novel highly active visible-light responsive photoanode with the ternary hybrid CuO/Cu2O/TiO2 nanorods array film is proposed to enhance electron transfer in the photoelectrocatalytic (PEC) degradation of BTEX (benzene, toluene, ethyl benzene, and xylenes) by combining with MWCNT/GO/GF cathode. Structural, morphological, optical, electrochemical, and elemental analysis of proposed electrodes is investigated in detail. Response surface methodology (RSM) comprising of full-factorial central composite design (CCD) with five factors and five levels has been used to examine the effects of different operating parameters such as electrode distance, current density, treatment time (t), solution pH, and conductivity in a PEC batch reactor. BTEX mineralization in aqueous solution was examined with multiple responses such as chemical oxygen demand (COD) and specific energy consumption. During multiple response optimization, the desirability function approach was employed to concurrently maximize COD removal and minimize energy consumption. At the optimum condition, 81.3% COD removal and 9.5 kWh/kg of COD removed were observed. The photoelectrocatalytic oxidization mechanism of BTEX with proposed anode and cathode was discussed, then the possible degradation pathway of BTEX identified using GC–MS.

A cleaner enzymatic approach for producing non-phthalate plasticiser to replace toxic-based phthalates

Dioctyl phthalate (DOP) is industrially commonly used as a polyvinyl chloride (PVC) plasticiser. As DOP does not form a chemical link with PVC, it migrates from flexible PVC segments into the media in contact, a matter that arose concerns due to its noxious effect. Despite the introduction of several non-DOP-based plasticisers recently, most of these new plasticisers are petroleum derived, which is a non-renewable resource. Accordingly, this research aims to produce a natural-based plasticiser using clean production method. Epoxidised 2-ethylhexyl oleate (E-2-EHO) was produced through an esterification and epoxidation reaction between oleic acid and 2-ethyl hexanol; both reactions occur simultaneously, in the presence of hydrogen peroxide as oxygen donor in a solvent-free environment. Candida antarctica lipase (Novozym 435) was used as a cleaner biocatalyst. Several reaction parameters that affect the synthesis of (E-2-EHO) were analysed using response surface methodology based on full factorial central composite design for four variables. The maximum experimental conversion was 94.2% while the value of the predicted conversion was 95.3%. The operation conditions were a temperature of 65 °C, enzyme load of 4 wt%, alcohol-to-oleic acid molar ratio of 4:1, hydrogen peroxide-to-C=C molar ratio of 0.5:1, molecular sieve/g acid of 0.425 g and reaction time of 2 h. In addition, the plasticising effectiveness of (E-2-EHO) to substitute toxic DOP was studied. Comparison with conventional DOP highlighted that (E-2-EHO) had superior and significantly reduced glass transition temperature (tg) and improved mechanical properties. In the proposed study, (E-2-EHO) was proved to be an efficient substitute to DOP by replacing up to 80% of the total plasticiser. Moreover, the product yield obtained in a short time reaction along with the proven stability of Novozym 435 during operation both showed that this ecofriendly and maintainable alternative is favourable when used in large-scale applications.

Electrocoagulation for removal of phosphate from aqueous solution: Statistical modeling and techno-economic study

Abstract The focus of this study is to evaluate electrocoagulation as a process for the remediation of phosphate contaminated synthetic aqueous solutions using scrap aluminium plate electrodes in monopolar-parallel mode. An attempt was made in modeling the phosphate removal as a function of the significant parameters as well as to optimize the process statistically with the help of Response Surface Methodology using Design Expert software Version 7.0.0. The full factorial central composite design was followed to obtain the required number of runs for batch study. Five parameters namely initial pH, inter-electrode distance (IED), the concentration of the supporting electrolyte (SEC), electrolysis-time and voltage were considered for the experimentations. A valid model to predict the removal efficiency was established and the removal efficiencies witnessed were as high as 98%. The techno-economic optimization yielded the following set of parameters as the most economical solution: pH = 7, Voltage = 11.23 V, IED = 3 cm, t = 14.03 min and SEC = 0.46 g/L exhibiting a 90% removal efficiency and an operating cost of 0.22 $/m3 of water treated or 2.52 $/Kg of phosphate removed. The study of crystallinity of the electrocoagulation byproduct was also conducted using XRD analysis, which showed the presence of amorphous or poorly crystalline phases.

Optimization of recombinant maize CDKA;1 and CycD6;1 production in Escherichia coli by response surface methodology

The complex formed by the cyclin-dependent kinase A (CDKA) and cyclin D is responsible for the G1-S transition in the plant cell cycle. Maize (Zea mays L) CDKA; 1 and CycD6; 1 were cloned and expressed in E. coli. The present study describes the optimization of both proteins production using a statistical approach known as response surface methodology (RSM). The experimental design took into account the effects of four variables: optical density of the culture (OD600) before induction, isopropyl β-d-1-thiogalactopyranoside (IPTG) concentration, post-induction temperature, and post-induction time. For each protein, a 24 full factorial central composite rotary design for these four independent variables (at five levels each) was employed to fit a polynomial model; which indicated that 30 experiments were required for this procedure. An optimization of CDKA; 1 and CycD6; 1 production levels in the soluble fraction was achieved. Protein conformation and stability were studied by circular dichroism and fluorescence spectroscopy. Finally, in vitro Cyc-CDK complex formation and its kinase activity were confirmed.

Optimization of calcium alginate beads production by electrospray using response surface methodology

Preparing the alginate hydrogel beads with desired size and enough mechanical strength is the main aim in biomedical application. Such beads were produced from the viscid alginate solution using electrospray method. In a recent study, the combined effects of different parameters on calcium alginate beads production were studied using response surface methodology. A 24 full-factorial central composite design was chosen to explain four parameters, viz. concentration of polymer, nozzle diameter, flow rate, and voltage. The small p-value (<0.0001) and large t-value (−16.611) of the coefficient for the linear effect of voltage showed that this independent variable has the greatest effect on calcium alginate beads production. It was found that interactions among the nozzle diameter and other variables were not significant. The optimum values of test variables for production of alginate beads with minimum radius were determined as; 10 g l−1 alginate concentration, 1 mm nozzle diameter, 20 ml h−1 flow rate, and 9000 v voltage. At these conditions, the experimental and predicted values of beads radius are 0.2945 and 0.3 mm, respectively, reveals the accuracy of the developed model.

Optimization of Enterobacter cloacae mediated synthesis of extracellular silver nanoparticles by response surface methodology and their characterization

Synthesis of silver nanoparticles (AgNPs) with desired physicochemical properties using a cost-effective, energy, and time efficient way is vital. In this study, we have optimized the synthesis of AgNPs through protein containing cell-free supernatant of Enterobacter cloacae (SMP1). 23 full factorial central composite design (CCD) of the response surface methodology (RSM) was used for the process optimization. Individual and mutual interaction effects of the experimental variables including temperature, pH, inoculum size, and metal concentration were investigated on the synthesis of AgNPs. Results showed the involvement of 15 kDa protein in the synthesis of AgNPs. The optimized values of pH, temperature, cell-free culture supernatant (CFCS), and metal concentration were 10, 37 °C, 10% (v/v) and 2 mM, respectively. Characterization of AgNPs using UV-Vis spectroscopy reveals surface plasmon resonance peak at 450 nm. AFM and TEM micrographs revealed oval and spherical shaped AgNPs with the size of spherical (15–44 nm) and oval (20–46 nm wide and 240–325 nm long) and zeta potential of −41.3 mV under different experimental conditions. The EDS, X-ray elemental mapping, and FTIR reviled the presence of metallic AgNPs and signatures for nitrogen, carbon, oxygen, sulfur, and functional groups of different biomolecules.

Full-factorial central composite rotational design for the immobilization of lactase in natural polysaccharide-based hydrogels and hydrolysis of lactose

A full-factorial central composite rotational design (FFCCRD) was applied for studying the immobilization of lactase in Arabic gum-based and chitosan-based hydrogels, and hydrolysis of lactose. The optimal immobilization capacities of both hydrogels aiming to obtain high immobilized enzyme activity and low released fraction were determined at 25.0 °C, 39.88 mg mL−1 initial enzyme concentration and pH 6.5. The immobilized enzyme activity and released fraction from the Arabic gum-based hydrogel were 0.322 U mg−1 and 0.193, respectively, during the hydrolysis of lactose contained in UHT milk. These values were 0.289 U mg−1 and 0.136, respectively, using a chitosan-based hydrogel. The immobilized enzyme activity and released fraction from these hydrogels during the hydrolysis of standard lactose were 0.246 U mg−1 and 0.407, and 0.211 U mg−1 and 0.245, respectively. The best conditions for the immobilization of lactase and hydrolysis of lactose were achieved by applying FFCCRD, which were compared with experimental results.

Characterization of a cold-active, detergent-stable metallopeptidase purified from Bacillus sp. S1DI 10 using Response Surface Methodology

The colder regions of Earth are inhabited by cold-adapted microorganisms designated as psychrophiles that are known to produce cold-active enzymes, such as peptidases, chaperones, lipases, cellulases, and phosphatases. These types of enzymes are a major part of the market of industrial enzymes. Bacteria isolated from water samples collected from the Chamba region in the Himalayas were screened for peptidase production using skim milk agar plates. Among the peptidase-producing bacteria isolated, 20% of the isolates exhibited fast growth and maximum zones of clearance, and thus, were used for further studies. The 16S rDNA sequence analysis of isolate S1DI 10 identified it as a Bacillus sp. The peptidase was cloned in pET28a vector and expressed in Escherichia coli BL21(DE3) and the His-tagged recombinant protein was purified using Ni-NTA column. The purified peptidase of SIDI 10 was found to be an alkaline, cold-active peptidase with optimal enzyme activity at 10°C and pH 8. An approach of one variable at a time was used to further study the effect of various metal ions, organic solvents and detergents on the peptidase enzyme. The peptidase activity was enhanced in the presence of Fe2+ and Mn2+ (metal ions), hexane (organic solvent), SDS- sodium dodecyl sulfate (anionic detergent) and Tween 80 (nonionic detergent). Response surface methodology (RSM) was used to determine the cumulative effect of these five variables. A 25 full factorial central composite design was applied for the five independent variables to determine the optimal combinations of these constituents at the maximum peptidase activity.

Optimization of physical parameters for enhanced production of lipase from Staphylococcus hominis using response surface methodology.

Lipase, a versatile hydrolytic enzyme, is gaining more importance in environmental applications such as treatment of oil and grease containing wastewater, pretreatment of solid waste/industrial wastewater for anaerobic treatment. In the present study, the attempts have been made to improve the production of lipase from Staphylococcus hominis MTCC 8980 by optimization of pH, temperature, and agitation speed in lab scale shake flasks culture. The experiments were designed using the full factorial central composite design of experiment. A total of 20 experiments were conducted, and the optimized pH, temperature, and agitation speed were found to be 7.9, 33.1 °C, and 178.4rpm, respectively. The results of the analysis of variance (ANOVA) test revealed that the linear terms for temperature and agitation were significant (p value < 0.05). Interaction for pH and agitation speed was found to have a significant effect on lipase production from S. hominis MTCC 8980. A 150% increase in enzyme activity was observed under the optimized conditions with the maximum lipase activity of 1.82U/ml. Further enhancement of enzyme activity can be expected from the optimization of medium components.

Parametric optimization of TIG welding using Response Surface Methodology

Abstract In this study, Response surface methodology (RSM) is a method used to analyze and represent the cause and effect of interaction between mean responses and input control parameters influencing the responses as a two or three-dimensional surface. Tungsten Insert Gas (TIG) or Gas Tungsten Arc Welding (GTAW) is extensively used in industry to join a thin section of stainless steel. This welding technique gives the operator greater control over the weld than other welding processes. In this study influence of the input parameters like welding current, speed, voltage, and pulsed on time was determined. The main problem faced by manufacturing industry is the proper combination of the input parameter to get an optimum response. This problem is encountered by the development of a mathematical model by RSM using design expert 11 statistical software through full-factorial central composite design (CCD). RSM is a useful statistical tool for process optimization to obtain the required quality of weld. The Surface plot obtained from Design Expert Software 11 represent that the actual value of response i.e. depth of penetration (DOP) versus the predicted value of response are close to each other. The higher value of DOP represents higher strength; analysis of variance (ANOVA) gives the highest value of F-ratio of welding speed, this result obtained from RSM showed that welding speed is the most influencing parameter which affects performance characteristics.

Integration of RSM with Grey based Taguchi Method for optimization of pulsed TIG welding process parameters

Abstract This research paper focused on process parameters optimization of Tungsten Inert Gas (TIG). Taguchi method is very effective and efficient to solve the process parameter optimization problem to the find optimum processing parameter, but it is found that the traditional Taguchi method is not sufficient to solve the problem with multi response problem to get optimum results and to meet the global challenges of the manufacturer as it is impractical to obtain more than one optimal processing parameter through Taguchi. In order to survive in the global market it is necessary to used advanced and modified optimization techniques. To intensify the efficiency of Taguchi method, it is absolutely necessary to integrate it with the other optimization approach. However, it is important to integrated Taguchi method with Grey Retion Analysis (GRA) to solve multi response optimizaton promblem futher Taguchi method is integrated with Response Surface Methodology (RSM) to determine optimum value of each parameters. Using orthogonal array L9 experiments were performed. Experimental data are used to obtain signal to noise ratio by using Minitab18 and then response surface plot is developed to obtain optimum level for every input parameter. Further, the process is integrated with RSM to developed mathematical model by using design expert 11 statistical software through full-factorial central composite design (CCD). RSM is a useful statistical tool for process optimization to obtain the required quality of weld. The Surface plot obtained from Design Expert Software 11 represent that the actual value of response i.e. depth of penetration (DOP) and width of penetration (WOP) versus the predicted value of response are close to each other. The higher value of DOP and WOP represents higher strength; analysis of variance (ANOVA) gives the highest value of F-ratio of welding speed in DOP and WOP, this result obtained from RSM showed that welding speed is the most influencing parameter which affects response characteristics.