Taguchi Orthogonal Array Method Research Articles

Orthogonal Array Approach Optimization of Catalytic Systems

The paper presents the optimization of the epoxidation process of crotyl alcohol on the Ti-MWW catalyst at atmospheric pressure, based on the Taguchi orthogonal array method. Shown are the influence of the most important process parameters, such a temperature, molar ratio of crotyl alcohol to H2O2, methanol concentration, Ti-MWW catalyst concentration and reaction time. The response functions characterizing epoxidation process were selectivity of transformation to 2,3-epoxybutan-1-ol with respect to reacted crotyl alcohol – S2,3EB1O/CA, conversion of crotyl alcohol CCA, yield of 2,3-epoxybutan-1-ol W2,3EB1O. Based on the calculated signal/noise ratios for individual parameters of the process, their impact on all output parameters was determined and optimal process conditions were determined to reach its the maximum. The empirical verification of this process was also performed by comparing both output parameters predicted and achieved in the tests. This method allows limiting the number of tests required to reach the wished test results, diminution the time needed course for their achievement, and at the same time their expenses.

Community-level decentralized energy system planning under uncertainty: A comparison of mathematical models for strategy development

Distributed energy systems renewable energy are one solution to the environmental and economic concerns of energy use. While energy planning and optimization have been conducted mainly as a mathematical exercise, practical approaches that incorporate the engineering realities and uncertainties are limited. Decision makers find challenges in community energy planning due to the lack of expertise, planning tools, and information. While a multitude of models and tools are currently available, there are no means of identifying the most appropriate or accurate methods, especially considering uncertainty. The main objective of this study is to compare and identify the strengths and limitations of various mathematical modelling techniques used in energy planning for grid connected renewable energy systems. As a case study demonstration, different multi-objective optimization techniques with and without uncertainty consideration (i.e. robust optimization, linear optimization, Taguchi Orthogonal Array method, and Monte Carlo simulation) were applied on a selected neighborhood in British Columbia. The optimization outcomes and the time and effort for evaluation were compared for the different methods. The findings indicate that robust optimization can be used to develop an uncertainty-based decision model. It significantly reduces evaluation time compared to the other methods. Although the presence of uncertainties can change the optimal configuration of a planned energy system, the assessment method itself does not significantly impact the outcomes. The findings of this study will enable the energy planners and researchers to compare different multi-objective optimization techniques, and to select the best for planning renewable energy projects, especially during the pre-project planning stage.

Comparison of novel surface treatments of Al 2024 alloy for al/cfrp adhesive bonded joints

The objective of this study is to investigate the effect of silane and fiber laser treatments on the shear strength and failure type characteristic ofAA2024-T3/unidirectional carbon fiber-reinforced epoxy composite [0]8 laminates (Al/CFRP) adhesively bonded joints. Epoxy-based paste 2 part adhesive (Loctite EA 9396 AERO) was used for adhesive joining. Chemical surface treatment was tested with three different silane concentrations (1, 3 and 5 vol%) applied to AA2024-T3 aluminum plates after cleaning. In addition, 50 W pulsed fiber laser was used to AA2024-T3 aluminum plates for laser treatment. For determining the optimum fiber laser parameters (laser power, frequency and scanning speed) L9 orthogonal array Taguchi method (3 variables and 3 levels) was used. The chemical composition of the fiber laser and silane treated AA2024-T3 sample's was analyzed using Fourier transform infrared spectroscopy – attenuated total reflectance (FTIR–ATR). Shear strength values of the Al/CFRP bonded joints were determined by using single lap shear tests. From the test results, the silane concentration of 3 vol% on AA2024-T3 aluminum plates had a significant effect on shear strength of Al/CFRP bonded joints (16.44 MPa) compared to untreated samples (6.46 MPa). In addition, it was determined that the laser treating parameters of scanning speed of 100 mm/s, frequency of 80 kHz and power of 50 W laser power achieved the optimum surface of AA2024-T3 to be strongly bonded with CFRP (23.68 MPa). After mechanical tests, failure modes were also observed by using the digital camera.

Prediction of uniaxial tensile flow using finite element-based indentation and optimized artificial neural networks

This study derives a uniaxial tensile flow from spherical indentation data using an artificial neural network (ANN) combined with finite element (FE) analysis. The feasibility of the FE-based simulations is confirmed through experimental indentation for various steels. Parametric studies of the FE simulation are performed to generate an ANN training database. An encoding for feature extraction and a hyperparameter optimization is implemented to design the ANN with high predictive performance. The indentation load–depth curves are converted into hardening parameters through the trained ANN. The predictive performance of the FE–ANN model using real-life indentation data is investigated in-depth with thorough error evaluation, and verified by uniaxial tensile tests. The emphasis is made that the mean absolute percentage error between the experimental and simulated indentation data is required to be meticulously controlled below 1% to accurately predict the tensile properties. The validations demonstrate that the applied FE–ANN modeling approach is very robust and captures the tensile properties well. Furthermore, the Taguchi orthogonal array (OA) method that can achieve high efficiency and fidelity with less training data is discussed. The FE–ANN model is concisely designed using the Taguchi OA method and can predict elasticity as well as plasticity.

Performance Prediction Model of Solid Oxide Fuel Cell System Based on Neural Network Autoregressive with External Input Method

An accurate performance prediction model for the solid oxide fuel cell (SOFC) system not only contributes to the realization of the operating condition but also plays a role in long-term prediction performance. Accordingly, a research study has been developed to suitably deal with the time-series model and accurately build the performance prediction model of SOFC system based on neural network autoregressive with external input (NNARX) method. The architecture regressor parameters of the NNARX model were efficiently determined using the Taguchi orthogonal array (OA) method for optimal sets. The identified and evaluated optimal parameter levels were used to conduct an analysis of variance (ANOVA) to prove correctness. Moreover, a series of statistics criteria and multi-step prediction were also employed for investigating the uncertainty of the predicted model and solve the overfitting and under fitting problems; further. These criteria were also used to determine the performance of the proposed model architecture. The predicted results of the current study indicated that the developed optimal model level parameters consistently had the least statistics errors and reduced workload of the trial-and-error processes.

Enhanced biomass and lutein production by mixotrophic cultivation of Scenedesmus sp. using crude glycerol in an airlift photobioreactor

This study presents the mixotrophic cultivation of Scenedesmus sp. using crude glycerol (CG) obtained from lab scale biodiesel unit in an internal loop airlift photo-bioreactor (ALR) for enhanced biomass and lutein production. Prior to reactor studies, shake flask experiments were designed using Taguchi orthogonal array method to evaluate the influence of CG concentration, nitrogen to phosphorus ratio (N/P), and inhibitors concentration (methanol and KOH). Experimental run carried out with 5 g/l CG, 20:1 N/P ratio, 0.5 % methanol concentration, and 7.5 mg/l KOH produced a maximum biomass and lutein productivity of 310.18 mg/(l d) and 2.25 mg/(l d) respectively. During the mixotrophic cultivation of Scenedesmus sp. in an ALR, the step-wise addition of CG during the growth phase improved the productivity. The CG concentration of 6 g/l showed highest biomass and lutein productivity of 768 mg/(l d) and 3.59 mg/(l d), respectively. Monod and Logistic models were employed to fit the growth data. This study illustrated that the fed-batch strategy and mixotrophic cultivation offer higher biomass and lutein production.

Multi-Performance Characteristics of AA5052 + 10% SiC Surface Composite by Friction Stir Processing

In this paper, optimization of the fabrication parameters of an aluminum surface composite with respect to tensile strength and tool wear rate is reported. The surface layer was reinforced with SiC particles to improve the tribological properties of AA-5052. The Taguchi design with orthogonal array L8 was used for the experimental design, which included three processing parameters: the number of passes, rotational speed, and traversal speed. The experiment used optimal fabrication parameter searching to produce a multi-response prediction of both the tensile strength and tool wear rate. The experimental result was determined by grey relational analysis for multi-performance characteristics. Afterward, the prediction result of the optimal fabrication parameters was confirmed by repeated experiments to confirm the selection of optimal process parameters. The results revealed that the optimal fabrication parameters for multi-performance characteristics are two passes, rotational speed of 1000 revolutions per minute (RPM), and traversal speed of 30 mm/min (condition N2R1T2). These showed high tensile strength (229.90 MPa), low tool wear rate (0.0851), and a uniform distribution of SiC particles in the matrix. In addition, grey relational analysis showed that the parameter priority was 51.68% for rotational speed (the most significant process parameter), 36.18% for transversal speed, and 7.05% for the number of passes. Therefore, the grey-based orthogonal array Taguchi method can optimize multi-performance characteristics through the setting of process parameters for friction stir processing of an aluminum surface composite.

Thermal pyrolysis optimization for highest density of Ti-6Al-4V mix with Palm Stearin and Polyethylene

Titanium metal injection molding (Ti-MIM) is coming ever closer to delivering its promise of high value markets, such as the aerospace and medical sectors. It is therefore an inspiration in this study to try to use palm stearin (PS) combined with backbone polyethylene (PE) for injection along with Ti-6Al-4V atomized powder. The uniqueness of PS is a potential binder system that can be used since it is very cheap material and highly available in Malaysia. The present work attempts to optimize the process parameters of thermal pyrolysis stage using Taguchi method of orthogonal array. Density is important characteristic in determine the quality of the brown part. Using these characteristics, the heating rate, temperature and soaking time are optimized in this study. The results show that no swelling or distortion was observed on the molded specimens on both binder systems. It was found that heating rate was the most significant factor followed by pyrolysis time and pyrolysis temperature. A verification test was also performed to prove the effectiveness of Taguchi technique after all the optimum parameters were determined. The optimization of thermal pyrolysis prepared in this study has enabled to improve the final density and mechanical properties of final part. Based on these results, sample displaying yield strength of 929.91 MPa and a plastic elongation of more than 12.15% were produced and meet the requirements of the ASTM B817-08.

Analyzing the effect of the parameters of laser etching process influencing the corrosion resistance and surface roughness of marine grade 316 stainless steel

Laser etching process is used for marking those materials which cannot be marked by conventional machining processes. The aim of the current study attempts to investigate the effects of Laser etching parameters specially the scanning speed [ns], peak power [kW], frequency [kHz] and heat input [J/mm2] on the corrosion resistance and variations in surface roughness properties of the Marine grade 316 Stainless Steel. In the laser etching process the surface of the material is incident by a laser beam which heats up the marked area and subsequently vaporizes the material leading to formation of oxide layer on the surface, which when comes in contact with aggressive environment causes a chemical reaction on the bare steel leading to corrosion. The experiment was performed after marking on the material surface body with Nd: YAG Solid State UV Laser beam using Laser annealing process. Surface roughness is an important parameter that affects the tribological behavior of surfaces. In the food processing industry the '316′ grades are unofficially known as the 'food' grades because the lower the surface roughness, the better, since corrosive material and bacteria are less likely to stick to a very smooth surface. The samples were subjected to salt spray test to check corrosion resistance of materials. Taguchi method of orthogonal array based on Minitab 18 was used to determine the best factor level condition. Marking quality was evaluated by visual examination. Analysis of variance (ANOVA) has been applied on experimental data to identify the relative significance of process parameters on the response. The analysis shows that the laser beam scanning speed is the most influential operating factor.

Design and formulation of surfactant stabilized O/W emulsion for application in enhanced oil recovery: effect of pH, salinity and temperature

Mobilization of crude oil from the subsurface porous media by emulsion injection is one of the Chemical Enhanced Oil Recovery (C-EOR) techniques. However, deterioration of emulsion by phase separation under harsh reservoir conditions like high salinity, acidic or alkaline nature and high temperature pose a challenge for the emulsion to be a successful EOR agent. Present study aims at formulation of Oil-in-Water (O/W) emulsion stabilized by Sodium Dodecyl Sulfate (SDS) using the optimum values of independent variables – salinity, pH and temperature. The influence of above parameters on the physiochemical properties of the emulsion such as average droplet size, zeta (ζ) potential, conductivity and rheological properties were investigated to optimize the properties. The influence of complex interactions of independent variables on emulsion characteristics were premeditated by experimental model obtained by Taguchi Orthogonal Array (TOA) method. Accuracy and significance of the experimental model was verified using Analysis Of Variance (ANOVA). Results indicated that the experimental models were significantly (p < 0.05) fitted with main influence of salinity (making it a critical variable) followed by its interactions with pH and temperature for all the responses studied for the emulsion properties. No significant difference between the predicted and experimental response values of emulsion ensured the adequacy of the experimental model. Formulated optimized emulsion manifested good stability with 2417.73 nm droplet size, −72.52 mV ζ-potential and a stable rheological (viscosity and viscoelastic) behavior at extensive temperature range. Ultralow Interfacial Tension (IFT) value of 2.22E-05 mN/m was obtained at the interface of crude oil and the emulsion. A favorable wettability alteration of rock from intermediate-wet to water-wet was revealed by contact angle measurement and an enhanced emulsification behavior with crude oil by miscibility test. A tertiary recovery of 21.03% of Original Oil In Place (OOIP) was obtained on sandstone core by optimized emulsion injection. Therefore, performance assessment of optimized emulsion under reservoir conditions confirms its capability as an effective oil-displacing agent.

Hydraulic Performance Prediction Methodology in Regenerative Pumps Through CFD Analysis

Peripheral pump efficiency is a factor of performance defined by geometrical parameters and characteristic curves of the system. Due to the need to determinate an appropriate pump operating point in order to obtain an adequate hydraulic system performance in industrial and home applications, this paper presents a methodology that simulates the flow behavior of vortex or regenerative pumps using geometrical factors that directly define its optimal performance. An approximated real behavior of the flow phenomena is determined through the application of numerical methods and turbulence models based on Computational Fluids Dynamics with the aim to link and validate the results obtained in the predictive approach. The technological advance of the computational methods used in the analysis of flow phenomena enables an approximated description of the flow studied by means of computational tools. Therefore, numerical analysis is developed by using OpenFOAM software. This computational tool is an open-source code computed in the C++ library characterized by the development of complex analysis related to the flow phenomena applied in engineering applications based on the performance of turbomachinery used in energy transformation systems. The methodology used in this paper improves the prediction of the flow in a peripheral pump using statistical models based on the multiple linear regression model determined with the Taguchi Orthogonal Array method. A deviation of less than 5 percent between the predictive approach and the numerical model compared has been reached. Geometrical optimization of the peripheral centrifugal pump, taking into account the angular velocity of the impeller, inlet, and outlet angles of the blade, and height impeller blades have been developed.

Optimization of Palm Oleic Acid Epoxidation via in Situ Generated Performic Acid Using Taguchi Orthogonal Array Design and the Study of Reaction Kinetics

ABSTRACTThe epoxidation of palm kernel oil-crude oleic acid was carried out to produce epoxidized oleic acid. Performic acid was formed by mixing formic acid (oxygen carrier) and hydrogen peroxide (oxygen donor) in various ratios of oleic acid, formic acid, and hydrogen peroxide. The signal-to-noise ratio and the analysis of variance are employed to investigate optimal conditions for the epoxidation based on Taguchi orthogonal array method. The optimum conditions based on two responses are the highest relative conversion to oxirane and stability occurred at moderate temperature of 55°C, agitation speed 200 rpm, molar ratio of formic acid:unsaturated oleic acid of 1:1 and molar ratio hydrogen peroxide:unsaturated oleic acid mole ratio of 1:1.5. In this study, the sulfuric acid was found to be the most efficient catalyst. Then, reaction rate for epoxidation of palm oleic acid was in the range of 0.0351–0.0941 min−1 calculated at various temperatures.

Enhancing morphology and compression properties of halloysite reinforced polyurethane nanocomposites using injection-moulding technique

The traditional method of enforcing thermoplastic polyurethane (TPU) by halloysite nanotubes (HNTs) to create HNTs-TPU nanocomposite material has been modified aiming at producing better quality nanocomposite using compression injection techniques. This technique adds more options of using control parameters and much better estimation to the corresponding levels of these parameters. In this study, six controlled parameters of injection temperature, injection pressure, mould temperature, injection time, HNTs loading, and function HNTs at three levels were considered. Under such huge number of parameters and their corresponding levels, the number of required experiments is enormous; however, with the help of Taguchi method of orthogonal arrays, the number of experiments is reduced to only 27. These experiments are then used to examine the optimized conditions of modulus Young’s, compression strain, and compression extension (known as responses). In this study, Taguchi method is fortified by ANOVA since Taguchi method is not enough to provide a clear and full analysis. The responses of modulus Young, compression strain, and compression extension have shown maximum absolute variation based on the original and untreated material by 30%, 25%, and 37%, respectively. Further, the optimized modulus Young is optimized at 1 wt% HNTs, 4 bar of injection pressure, 28 °C of mould temperature, and 4 min of injection time. These results were confirmed statistically by ANOVA and experimentally by field emission scanning electron microscopy (FESEM) images where the agglomeration of HNTs was seen as an important factor of the absolute variation of the responses. This study serves another purpose where Taguchi method was tested for reliability in a very big scale of such control parameters.

Experimental investigation on the ultrasonically assisted single-sided lapping of monocrystalline SiC substrate

This paper studied the effect and optimization of ultrasonically assisted single-sided lapping for monocrystalline SiC wafer using grey relational analysis method. 27 experiments based on the Taguchi method of orthogonal arrays were performed to determine the best factor level condition. Besides, the comparative experiments using three lapping plates (cast iron, copper, and aluminum) were also performed under ultrasonic lapping and non-ultrasonic lapping, respectively. Material removal rate (MRR) and surface roughness (Ra, Rmax) were selected as the output indexes. The degree of influence that the controllable process factors exert on the indexes was studied by investigating the correlation between them. By analyzing the signal-to-noise ratio and grey relational grade, the most influential process factor is the interaction item of normal pressure and rotating speed. Ultrasonically assisted vibration has a positive correlation with the MRR, while simultaneously increases the surface roughness, but the higher ultrasonic power is beneficial to inhibit the increase of surface roughness. The lower hardness of lapping plate can obtain the better surface at the cost of decreasing MRR, but much too low hardness may destroy the machined surface.

Experimental Researching of Thermal - Assisted Milling with Induction on Surface Roughness of SKD11 Steel

This paper presents experimental studied results about surface roughness during end milling SKD11 steel under room temperature and work-piece preheated condition. Conventional samples were first performed. The samples which are same technical parameters were then performed at elevated temperatures to evaluate effective of heating process on the surface roughness. Orthogonal array Taguchi method was used to experimental design. The results showed that the surface quality of product was significantly improved under thermal - assisted milling. The surface roughness model during machining at room and elevated temperatures were evaluated and showed a good agreement with result of experiments.

Statistical evaluation and performance analysis of electrical discharge machining (EDM) characteristics of hard Ti-6Al-2Sn-4Zr-2Mo alloy

Nowadays, electrical discharge machining process is successfully employed to machining hard titanium alloys compared to other non-conventional machining processes. The generation high temperature is utilized to melt and vaporize the hard titanium alloy during electrical discharge machining. The process parameters are highly influenced on the machining performance and need to be studied for optimum results. In the present research, the hard Ti-6Al-2Sn-4Zr-2Mo alloy was machined by EDM process and machining characteristics such as material removal rate, tool wear rate and surface roughness were analyzed statistically to get the optimum performance. The experiments were carried out based on the Taguchi orthogonal array method. From the statistical analysis of experimental results, the most significant parameters were identified as peak current, pulse on time and voltage. In addition to that SEM analysis was used to characterize the machined surface. The results of SEM analysis indicated that craters, surface cracks, globules and recast layer present on the machined surface.

Development of high biomass and lipid yielding medium for newly isolated Rhodotorula mucilaginosa

Conversion of plant-based biomass into biofuels has been singled out as a way to achieve economically viable production chains. Over past few decades development in yeast oil production have been witnessed, which includes isolation of high lipid accumulating strains, understanding the metabolic pathways for oil production, genetic engineering strategies for overproduction of lipids and optimization of cultivation processes for converting lignocellulose biomass to oil. In the present investigation, screening, isolation and characterization of novel oleaginous yeast from oil refinery was carried out. The strain was identified as Rhodotorula mucilaginosa by 26s rRNA sequencing (Accession Number: KX533469). Glucose and peptone were identified as best carbon and nitrogen source for high biomass induction. Further, two-stage optimization using taguchi orthogonal array method and multi objective optimization using genetic algorithm was applied for the development of an optimized medium. Malt extract was found to be a key influencing factor in both biomass and lipid induction with high S/N ratio, followed by peptone and glucose. Batch bioreactor studies revealed that the lipid productivity follows mixed growth associated pattern with the higher lipid accumulation of 0.25 g/g biomass.

Parametric Analysis of Magnetorheological Strut for Semiactive Suspension System Using Taguchi Method

Magnetorheological (MR) strut is among the leading advanced applications of semi-active suspension systems. The damping force of MR damper is controlled by varying the viscosity of MR fluid. In this work, the viscosity of MR damper varies by changing the current from 0.5A to 0.7A. The design of experiments is taken into account in concert with the product/process development as one completely advanced tool. The parameters used for ride comfort optimization are sprung mass, spring stiffness, tire pressure, current, and cylinder material with two levels of each. Taguchi orthogonal array method is used to select the best results by parameter optimization with a minimum number of test runs. In this paper, from Taguchi L16 array and S/N ratio analysis, it is observed that the cylinder material with Al and CS for damper cylinder is a key parameter for performance measure of semi-active suspension system. From regression analysis, a linear mathematical model is developed for Al and CS as cylinder materials. The interaction of cylinder materials with all four parameters is plotted. The methodology implemented for measurement of acceleration as a ride comfort is as per IS 2631-1997. The more economical model of magnetorheological damper will motivate Indian auto industry to broader applications.

Highly biocompatible chitosan with super paramagnetic calcium ferrite (CaFe2O4) nanoparticle for the release of ampicillin

The CaFe2O4 nanoparticles (CFNP) were synthesized using the solution combustion method. The CFNP-chitosan-ampicillin was prepared by the ionic gelation method using tripolyphosphate (TPP). The CFNP, chitosan-CFNP, chitosan-CFNP-ampicillin materials were characterized by XRD, FT-IR and TGA analysis in order to evaluate the particle nature and size, the presence of functional groups and their thermal stability. The FESEM and EDAX analysis were performed to understand the surface morphology of the materials and the presence of CFNP in the material, respectively. The vibrating sample magnetometer (VSM) analysis was performed to analyze the magnetic property of the chitosan-CFNP material. The squareness value of 0.1733 obtained by VSM measurements indicates the super paramagnetic nature of chitosan-CFNP. Taguchi orthogonal array method was applied to identify the significant impacting parameters for maximizing the drug encapsulation of chitosan-CFNP. The drug release studies showed that the drug was released rapidly in acidic medium as compared to the basic or neutral medium. The drug release kinetic data were fitted with different linear kinetic model equations and the best fit was obtained with Korsmeyer-Peppas model. The model drug ampicillin release from chitosan-CFNP was tested against staphylococcus epidermis bacteria through disc diffusion method for checking biocompatibility and antibacterial activity.

Selection of microemulsion composition via study of phase behavior for synthesis of stable monodisperse platinum nanoparticles and optimization of experimental parameters

ABSTRACTMonodisperse platinum nanoparticles were synthesized by microemulsion technique. Feasibility of formation of microemulsion with chosen proportions of components is a common problem with this method. Here, prior to preparation of microemulsion for synthesis purpose, systematic study was carried to check the suitability of selected microemulsion system by establishing phase diagram for ternary system at constant temperature on triangular coordinates. Temperature dependency of microemulsion was studied by preparing phase diagram of temperature against mass fraction of aqueous phase in ternary mixture. Both these triangular coordinate diagram at constant temperature and temperature dependency plots helped to choose proper concentrations of components in the system. Effects of molar concentration of water-to-surfactant ratio, platinum salt concentration, continuous oil phase concentration, and presence of cosurfactant with surfactant on particle size were investigated for selected system of components. Synthesized platinum nanoparticles were characterized by dynamic light scattering and transmission electron microscope. Light backscattering profiles obtained by Turbiscan were used to judge the stability of microemulsions. Further, partial weightage of affecting parameters on size of synthesized particle were studied by Taguchi orthogonal array method.