Showing papers on "Orthogonal array published in 2014"

A comparison of central composite design and Taguchi method for optimizing Fenton process.

Abstract: In the present study, a comparison of central composite design (CCD) and Taguchi method was established for Fenton oxidation. [Dye]ini, Dye:Fe(+2), H2O2:Fe(+2), and pH were identified control variables while COD and decolorization efficiency were selected responses. L 9 orthogonal array and face-centered CCD were used for the experimental design. Maximum 99% decolorization and 80% COD removal efficiency were obtained under optimum conditions. R squared values of 0.97 and 0.95 for CCD and Taguchi method, respectively, indicate that both models are statistically significant and are in well agreement with each other. Furthermore, Prob > F less than 0.0500 and ANOVA results indicate the good fitting of selected model with experimental results. Nevertheless, possibility of ranking of input variables in terms of percent contribution to the response value has made Taguchi method a suitable approach for scrutinizing the operating parameters. For present case, pH with percent contribution of 87.62% and 66.2% was ranked as the most contributing and significant factor. This finding of Taguchi method was also verified by 3D contour plots of CCD. Therefore, from this comparative study, it is concluded that Taguchi method with 9 experimental runs and simple interaction plots is a suitable alternative to CCD for several chemical engineering applications.

Optimization of process parameters in drilling of GFRP composite using Taguchi method

Abstract: a b s t r a c t The objective of the present work is to optimize process parameters namely, cutting speed, feed, point angle and chisel edge width in drilling of glass fiber reinforced polymer (GFRP) composites. In this work, experiments were carried out as per the Taguchi experimental design and an L9 orthogonal array was used to study the influence of various combinations of process parameters on hole quality. Analysis of variance (ANOVA) test was conducted to determine the significance of each process parameter on drilling. The results indicate that feed rate is the most significant factor influencing the thrust force followed by speed, chisel edge width and point angle; cutting speed is the most significant factor affecting the torque, speed and the circularity of the hole followed by feed, chisel edge width and point angle. This work is useful in selecting optimum values of various process parameters that would not only minimize the thrust force and torque but also reduce the delimitation and improve the quality of the drilled hole.

Application of Taguchi, ANFIS and grey relational analysis for studying, modeling and optimization of wire EDM process while using gaseous media

Abstract: In the dry wire electrical discharge machining (WEDM) process, the liquid dielectric is replaced with gaseous medium to enhance the machining environment safety. Also, this modification improves the surface quality of machined specimen but decreases the material removal rate of the process. In the present work, experimental study of dry WEDM process has been performed while machining of Al/SiC metal matrix composite. At first, a series of exploratory experiments has been conducted to identify appropriate gas and wire material based on their cutting velocity. After selection of the best gas and best wire, they were used for later stage of experiments. At the next stage, experiment were designed and conducted based on L27 Taguchi's orthogonal array to study the effect of pulse on time, pulse off time, gap voltage, discharge current, wire tension and wire feed on cutting velocity (CV) and surface roughness (SR). Analysis of variances (ANOVA) has been performed to identify significant factors. In order to correlate relationship between process inputs and responses, adaptive neuro-fuzzy inference system has been utilized. At the end, a grey relational analysis has been used to maximize CV and minimize SR simultaneously. Results indicated that oxygen gas and brass wire guarantee superior cutting velocity. Also according to ANOVA, pulse on time and current were found to have significant effect on CV and SR.

Optimal design of interior permanent magnet synchronous motor considering the manufacturing tolerances using Taguchi robust design

Abstract: The manufacturing tolerance of the permanent magnets (PMs) is inherent in the produce of the machine. These tolerances influence back electromotive force (EMF), which is an important response of the motor. In order to enhance the quality of the product, the authors need to reduce these tolerances, but it is very difficult and involves a number of costs. Therefore, this study presents a robust design of the EMF characteristic analysis considering the manufacturing tolerances of PM in the interior PM synchronous motor (IPMSM). Among the robust optimisation method, Taguchi robust design based on orthogonal array was applied. Finally, the validity of the analysis result is verified by comparing the optimum design model with present design model (mass production model) ones.

Design and Analysis of Experiments with R

Abstract: Introduction Statistics and Data Collection Beginnings of Statistically Planned Experiments Definitions and Preliminaries Purposes of Experimental Design Types of Experimental Designs Planning Experiments Performing the Experiments Use of R Software Completely Randomized Designs with One Factor Introduction Replication and Randomization A Historical Example Linear Model for Completely Randomized Design (CRD) Verifying Assumptions of the Linear Model Analysis Strategies When Assumptions Are Violated Determining the Number of Replicates Comparison of Treatments after the F-Test Factorial Designs Introduction Classical One at a Time versus Factorial Plans Interpreting Interactions Creating a Two-Factor Factorial Plan in R Analysis of a Two-Factor Factorial in R Factorial Designs with Multiple Factors-Completely Randomized Factorial Design (CRFD) Two-Level Factorials Verifying Assumptions of the Model Randomized Block Designs Introduction Creating a Randomized Complete Block (RCB) Design in R Model for RCB An Example of a RCB Determining the Number of Blocks Factorial Designs in Blocks Generalized Complete Block Design Two Block Factors Latin Square Design (LSD) Designs to Study Variances Introduction Random Sampling Experiments (RSE) One-Factor Sampling Designs Estimating Variance Components Two-Factor Sampling Designs-Factorial RSE Nested SE Staggered Nested SE Designs with Fixed and Random Factors Graphical Methods to Check Model Assumptions Fractional Factorial Designs Introduction to Completely Randomized Fractional Factorial (CRFF) Half Fractions of 2k Designs Quarter and Higher Fractions of 2k Designs Criteria for Choosing Generators for 2k-p Designs Augmenting Fractional Factorials Plackett-Burman (PB) Screening Designs Mixed-Level Fractional Factorials Orthogonal Array (OA) Definitive Screening Designs Incomplete and Confounded Block Designs Introduction Balanced Incomplete Block (BIB) Designs Analysis of Incomplete Block Designs Partially Balanced Incomplete Block (PBIB) Designs-Balanced Treatment Incomplete Block (BTIB) Row Column Designs Confounded 2k and 2k-p Designs Confounding 3 Level and p Level Factorial Designs Blocking Mixed-Level Factorials and OAs Partially CBF Split-Plot Designs Introduction Split-Plot Experiments with CRD in Whole Plots (CRSP) RCB in Whole Plots (RBSP) Analysis Unreplicated 2k Split-Plot Designs 2k-p Fractional Factorials in Split Plots (FFSP) Sample Size and Power Issues for Split-Plot Designs Crossover and Repeated Measures Designs Introduction Crossover Designs (COD) Simple AB, BA Crossover Designs for Two Treatments Crossover Designs for Multiple Treatments Repeated Measures Designs Univariate Analysis of Repeated Measures Design Response Surface Designs Introduction Fundamentals of Response Surface Methodology Standard Designs for Second-Order Models Creating Standard Response Surface Designs in R Non-Standard Response Surface Designs Fitting the Response Surface Model with R Determining Optimum Operating Conditions Blocked Response Surface (BRS) Designs Response Surface Split-Plot (RSSP) Designs Mixture Experiments Introduction Models and Designs for Mixture Experiments Creating Mixture Designs in R Analysis of Mixture Experiment Constrained Mixture Experiments Blocking Mixture Experiments Mixture Experiments with Process Variables Mixture Experiments in Split-Plot Arrangements Robust Parameter Design Experiments Introduction Noise Sources of Functional Variation Product Array Parameter Design Experiments Analysis of Product Array Experiments Single Array Parameter Design Experiments Joint Modeling of Mean and Dispersion Effects Experimental Strategies for Increasing Knowledge Introduction Sequential Experimentation One-Step Screening and Optimization An Example of Sequential Experimentation Evolutionary Operation Concluding Remarks Appendix: Brief Introduction to R Answers to Selected Exercises Bibliography Index A Review and Exercises appear at the end of each chapter.

Simultaneous optimization of surface roughness and material removal rate for turning of X20Cr13 stainless steel

Abstract: The objective of this article is to manufacture low-cost, high-quality products with maximum productivity in short time. In this work, four stages are considered: statistical investigation of the experimental results based on ANOVA, modelling based on regression analysis and mono- and multi-objective optimizations. In the first stage, turning experiments were carried out using an orthogonal array (L16) of Taguchi. Effects of cutting parameters on surface roughness and material removal rate were determined using ANOVA and interaction plots. In the second stage, regression analysis was utilized to formulate second-order models of all data gathered in the experimental works; these models could be used to predict responses in turning of X20Cr13 steel with a minor error. In the third stage, responses were used alone in an optimization study as an objective function. To minimize all responses, Taguchi’s signal-to-noise ratio was used. In the fourth stage, responses were optimized simultaneously using grey relational analysis.

Optimization of Parameters Using Conductive Powder in Dielectric for EDM of Super Co 605 with Multiple Quality Characteristics

Abstract: Experiments were performed using conductive powder-mixed dielectric in electrical discharge machining of Super Co 605 and optimization is carried out by means of Taguchi method. The process input parameters selected are flushing pressure, discharge voltage, pulse on-time, polarity, peak current, and pulse off-time to study the performance characteristics in the form of surface roughness, tool wear, and material removal rate. Experiments based on appropriate orthogonal array are conducted and significant parameters are identified. The optimum process conditions simultaneously leading to a better surface roughness, lower tool wear, and higher material removal rate are then demonstrated by confirmation testing. The experimental results confirm an improvement in surface roughness, tool wear, and material removal rate when Taguchi method is used.

Multi-Objective Optimization of Green Electrical Discharge Machining Ti–6Al–4V in Tap Water via Grey-Taguchi Method

Abstract: Ti–6Al–4V is widely used in manufacturing field for its exceptional merits, but it belongs to difficult-to-cut material. Electrical discharge machining (EDM) became an important machining method for this material. This paper aims to combine grey relational analysis and Taguchi methods to solve the EDM parameters optimization problems of Ti–6Al–4V material. Using tap water as working liquid is good for environment, because it is healthy and safe to the operators. The process parameters include peak current, open circuit voltage, lifting height, pulse width, and pulse intermission. The tool electrode wear rate, workpiece material removal rate, and the workpiece surface roughness are selected to estimate the machining results. Experiments were executed on orthogonal array and grey relational analysis, and then the results were verified through the contrast experiment. The results indicate that the workpiece material removal rate increased from 5.90 mm3/min to 6.02 mm3/min, the tool electrode wear rate reduce...

Comparison between Taguchi Method and Response Surface Methodology (RSM) in Modelling CO2 Laser Machining

Abstract: The applications of Taguchi method and RSM to modelling the laser parameters when machining industrial PVC foams is presented. The influence of cutting speed, laser power, frequency, duty cycle, and gas pressure on kerf width has been considered in this investigation according to Taguchi method using a standard orthogonal array L27 and RSM using a central composite design. Taguchi technique as well as 3D surface plot of RSM revealed that the cutting speed is the most significant factor in minimizing kerf width followed by laser power and etc. A predictive mathematical model was then developed through a regression analysis in both analytical tools to study the response. Though both the techniques predicted near values of average error, the RSM technique seems to be more promising in predicting the response via mathematical modelling over the Taguchi technique.

Optimization of wavelet-ANFIS and wavelet-ANN hybrid models by taguchi method for groundwater level forecasting

Abstract: In the recent years, artificial intelligence techniques have been widely developed for modeling hydrologic processes. Determining the best structures of these models such as Wavelet-ANN and Wavelet-ANFIS still remains a difficult task. In fact, there are several factors in the structure of these models that should be optimized. Selecting the best model structure by testing all of the possible combinations of factors is very time consuming and labor intensive. Using the optimization Taguchi method, this study assessed different factors affecting the performance of Wavelet-ANN and Wavelet-ANFIS hybrid models each of which has several levels. A L18 orthogonal array was selected according to the selected factors and levels and experimental tests were performed accordingly. Analysis of the signal-to-noise (S/N) ratio was used to evaluate the models performance. The optimum structures for both models were determined. For Wavelet-ANN, a model having 14 neurons in the hidden layer and trained with 1,000 epochs using Tangent Sigmoid (TanSig) transfer function in both hidden and output layers, and trained with Levenberg–Marquardt (LM) algorithm, whose input data were decomposed using Reverse Bior 1.5 (rbio1.5) wavelet in level 2, is the optimal Wavelet-ANN model. For Wavelet-ANFIS, a model with 700 iterations, using bell-shaped membership function and 5 membership functions, whose input data were decomposed using Daubechies 4 (db4) wavelet in level 2, is the optimal Wavelet-ANFIS model. Confirmation tests were then conducted using the optimum structures. It is also concluded that the best Wavelet-ANFIS model outperforms the best Wavelet-ANN model.

Multi-objective optimization of single point incremental sheet forming of AA5052 using Taguchi based grey relational analysis coupled with principal component analysis

Abstract: This paper presents a detailed experimental investigation on single point incremental forming (SPIF) of AA5052 sheet. In order to investigate the effects of incremental forming parameters, a straight-groove test was designed using L18 orthogonal array (OA) and groves were performed along the rolling, transverse and 45° (diagonal) directions on the cold-rolled sheets. The sum of major strain and minor strain as a measure of formability and the surface roughness were measured. These multi-objective responses were normalized using grey relational analysis (GRA). Moreover, the principal component analysis (PCA) was applied to evaluate the weighting values corresponding to each performance characteristics. The variability caused by the input parameters was apportioned using analysis of variance (ANOVA). Thus, the Taguchi method (TM) based GRA coupled with PCA was specifically adopted to determine the optimal combination of forming parameters. The confirmation experiment shows an average improved formability of 56.37% and surface roughness of 93.68%.

Metacomposite characteristics and their influential factors of polymer composites containing orthogonal ferromagnetic microwire arrays

Abstract: The microwave properties of glass-fibers reinforced polymer composite embedded with an orthogonal array of Fe77Si10B10C3 microwires have been investigated. The composites containing orthogonal wire arrays display a remarkable transmission window in the frequency band of 1 to 6 GHz under zero external magnetic field indicating an intrinsic double-negative-index characteristic. The polymer matrices have proved to exert a synergistic effect on the microwave properties, which is responsible for the disappearance of the transmission windows when Ek is perpendicular to the glass fiber direction. The plasma frequency of the orthogonal microwire array composite is higher than that of the parallel microwire array with identical wire spacing; this could be attributed to the enhanced microwire-wave interaction induced by the axial electrical components on the additional layer of perpendicular wires. All these features make this new kind of orthogonal microwire composites promising for potential cloaking and sensing applications.

Optimisation of machining and geometrical parameters in turning process using Taguchi method

Abstract: One of the most important factors that adversely affect quality of turning process is flank-wear. The flank-wear influences surface roughness and dimensional accuracy of finished product. Both flank-wear and surface roughness depend upon machining parameters and geometry of cutting tool inserts. Therefore, in order to ensure minimum flank-wear and surface roughness, it is necessary to optimise these machining and geometrical parameters in turning process. In the present work, seven parameters — cutting speed [m/minute], feed rate [mm/rev], depth of cut [mm], material type (hardness value HB), cutting-insert-shape, relief angle [°] and nose radius [mm] — were selected. Experimental layout using Taguchi’s L 18 orthogonal array was employed. Flank-wear and surface roughness were minimised using Taguchi’s signal-to-noise ratio concept with lower-the-better quality characteristic. Experimental results demonstrate the effectiveness of the Taguchi’s optimisation approach. Optimal setting of machining and...

Metacomposite characteristics and their influential factors of polymer composites containing orthogonal ferromagnetic microwire arrays

Abstract: The microwave properties of glass-fibers reinforced polymer composite embedded with an orthogonal array of Fe77Si10B10C3 microwires have been investigated. The composites containing orthogonal wire arrays display a remarkable transmission window in the frequency band of 1 to 6 GHz under zero external magnetic field indicating an intrinsic double-negative-index characteristic. The polymer matrices have proved to exert a synergistic effect on the microwave properties, which is responsible for the disappearance of the transmission windows when Ek is perpendicular to the glass fiber direction. The plasma frequency of the orthogonal microwire array composite is higher than that of the parallel microwire array with identical wire spacing; this could be attributed to the enhanced microwire-wave interaction induced by the axial electrical components on the additional layer of perpendicular wires. All these features make this new kind of orthogonal microwire composites promising for potential cloaking and sensing applications.