Abstract: This paper aims to develop a combination of Taguchi and fuzzy TOPSIS methods to solve multi-response parameter optimization problems in green manufacturing. Electrical Discharge Machining (EDM), a commonly used non-traditional manufacturing process was considered in this study. A decision making model for the selection of process parameters in order to achieve green EDM was developed. An experimental investigation was carried out based on Taguchi L9 orthogonal array to analyze the sensitivity of green manufacturing attributes to the variations in process parameters such as peak current, pulse duration, dielectric level and flushing pressure. Weighing factors for the output responses were determined using triangular fuzzy numbers and the most desirable factor level combinations were selected based on TOPSIS technique. The model developed in this study can be used as a systematic framework for parameter optimization in environmentally conscious manufacturing processes.

Abstract: The aim of this study is to present the methodology of Taguchi optimization technique for minimizing the delamination at the entrance of holes in high speed drilling of carbon fiber-reinforced plastics (CFRPs) The drilling process parameters evaluated are spindle speed, feed, and point angle The experiments were performed as per Taguchi’s L27 orthogonal array using cemented carbide (K20) twist drills The defects observed at the entrance of drilled holes of CFRP plates were measured and the delamination factor was computed for each trial of the orthogonal array The analysis of means (ANOM) and analysis of variance (ANOVA) were employed to determine the optimal process parameter levels and to analyze the effect of parameters on delamination factor The confirmation tests with the optimal levels of parameters were carried out to illustrate the effectiveness of Taguchi design The optimization results indicate that point angle is the most significant factor followed by feed and spindle speed The results

Abstract: In the present work, Taguchi method in combination with grey relational analysis is applied for solving multi-criteria optimization problems in laser transmission welding processes. The welding parameters, namely laser power, welding speed and defocal position are optimized with respect to weld strength and weld width. Using the Taguchi quality design concept, an L16 orthogonal array table is chosen for the experiments. Grey relational analysis is applied to convert the multiple quality characteristics to a single performance characteristic called grey relational grade. Optimal welding parameters are then determined by the Taguchi method using grey relational grade as the quality index. Furthermore, analysis of variance is carried out to identify the most significant factor for the overall output feature of the laser transmission welding process. The results of the confirmation experiment show that the optimal laser transmission welding parameters can be determined effectively so as to improve multiple quality characteristics through this approach.

Abstract: Design of experiments (DOE) is a methodology based on statistics and other disciplines for arriving at an efficient and effective planning of experiments with a view to obtain valid conclusions from the analysis of experimental data. Design of Experiments determines the pattern of observations to be made with a minimum of experimental efforts. DOE process is implemented to FDM process to optimize the processing time. In this study three process parameters at three levels are selected. Using full factorial design totally 27 experiments are required. Using design of experiments and orthogonal array the total number of experiments are reduced to 9. Therefore the optimum processing time will be obtained in these 9 experiments. Thus 9 experiments are conducted and the experimental data obtained from the experimental trails are analyzed using S/N ratio and ANOVA analysis.

Abstract: Achieving robustness in product and process designs is of importance to various stakeholders such as manufacturers, suppliers, and consumers. As variability exists in all operations, it is desirable to create products and processes that are not very sensitive to factors that are not controllable. The Taguchi method is an approach to robust design. Inherent in the Taguchi method is the definition of a loss function. This loss function formulation is influenced by the type of quality characteristic under consideration, that is, smaller-is-better, larger-is-better, or target-is-best. Furthermore, based on the selected type of quality characteristic, a performance measure is defined. Such performance measures, usually called signal-to-noise (S/N) ratios, are used to determine optimal settings of the controllable factors. Typically, a two-step procedure is adopted in the Taguchi method. In the first step, the S/N ratio is maximized, whereas in the second step, using an adjustment factor that does not affect the S/N ratio, the mean response is adjusted to meet the target value, where appropriate. Experimental designs make use of orthogonal arrays to determine factor settings for obtaining data for subsequent analysis. The number of experimental runs is very modest in relation to the number of factors being investigated. WIREs Comp Stat 2011 3 472–480 DOI: 10.1002/wics.169 For further resources related to this article, please visit the WIREs website.

Abstract: This paper presents the application of Taguchi method and the utility concept for optimizing the laser process parameters in laser transformation hardening of commercially pure titanium using a continuous-wave 2-kW, Nd:YAG laser. In this study, a set of optimal laser process parameters were evaluated through the Taguchi method of orthogonal arrays and utility concept. Taguchi method and utility concept, a powerful tool to design optimization for quality, is used to find the set of optimal laser hardening parameters such as laser power (LP), scanning speed (SS), and focused position (FP) on two multiple performance characteristics of hardened bead geometries, namely, hardened bead width (HBW) and hardened depth (HD), developed for laser transformation hardening of commercially pure titanium. The utility concept has been employed for the multi-performance characteristics optimization using Taguchi design. The experiments were planned as per Taguchi’s L9 orthogonal array. A Taguchi L9 orthogonal array methodology was used to optimize the conditions for laser-hardened bead width and hardened depth. Taguchi tools such as analysis of variance (ANOVA), signal-to-noise ratio, and additive model have been used to analyze, obtain the significant parameters, and evaluate the optimum combination levels of laser transformation hardening process parameters. The optimal levels of the laser process parameters were determined through the analysis of means. The relative importance among the process parameters were identified through ANOVA. The ANOVA results indicated that the most significant process parameters are SS followed by LP and FP, which affect the optimization of multiple performance characteristics. The confirmation tests with optimal levels of laser process parameters were carried out to illustrate the effectiveness of Taguchi optimization method. The optimization results revealed that a combination of higher levels of SS and FP, i.e., increase in defocused beam with negative focal length along with LP in the lower level, is an essential laser hardening parameter to simultaneously minimize the HD and maximize the HBW.

Abstract: In the present work, effect of five factors viz., layer thickness, part build orientation, raster angle, raster to raster gap (air gap) and raster width each at three levels together with their interactions is studied on dimensional accuracy of fused deposition modelling (FDM) build part. Four performance characteristics i.e. percentage change in length, width, thickness and diameter considered in this study are converted into an equivalent response known as grey relational grade. Optimum factor levels are determined for maximisation of grey relational grade using grey-based Taguchi method. A fuzzy inference system (FIS) is proposed for prediction of overall dimensional accuracy using Taguchi's orthogonal array for developing inference engine. The results of FIS are compared with prediction values obtained through artificial neural network. It has been demonstrated that fuzzy model is able to predict overall dimensional accuracy at all operating condition to a high degree of accuracy.

Abstract: Numerous advancements have been occurring in the field of materials processing. Friction welding is an important solid-state joining technique. In this research project, friction welding of tube-to-tube plate using an external tool (FWTPET) has been performed, and the process parameters have been prioritized using Taguchi’s L27 orthogonal array. Genetic algorithm (GA) is used to optimize the welding process parameters. The practical significance of applying GA to FWTPET process has been validated by means of computing the deviation between predicted and experimentally obtained welding process parameters.

Abstract: The Taguchi method is an efficient approach for optimizing a single quality response. In practice, however, most products/processes have more than one quality response of main interest. Recently, the multi-response problem in the Taguchi method has gained a considerable research attention. This research, therefore, proposes an efficient approach for solving the multi-response problem in the Taguchi method utilizing benevolent formulation in data envelopment analysis (DEA). Each experiment in Taguchi's orthogonal array (OA) is treated as a decision making unit (DMU) with multiple responses set inputs and/or outputs. Each DMU is evaluated by benevolent formulation. The ordinal value of the DUM's efficiency is then used to decide the optimal factor levels for multi-response problem. Three frequently-investigated case studies are adopted to illustrate the proposed approach. The computational results showed that the proposed approach provides the largest total anticipated improvement among principal component analysis (PCA), DEA based ranking approach (DEAR) and other techniques in literature. In conclusion, the proposed approach may provide a great assistant to practitioners for solving the multi-response problem in manufacturing applications on the Taguchi method.

Abstract: Green composites made from natural fibers, and biopolymers offer a potential alternative to the petroleum-based materials, that are currently being used in many nonstructural applications. In spite of being biodegradable and eco friendly, range of applications is limited due to poor mechanical properties. Hence an attempt is made in this work to improve the mechanical properties of green composites by optimizing the hot press forming process parameters using Taguchi experimental design. Process parameters such as temperature, pressure, heating time, cooling system and recrystallization soak time were chosen for evaluation by Taguchi method. An L16 orthogonal array was chosen for the design of experiments. The optimum combination of process parameters is obtained by using the analysis of the signal-to-noise ratio. The levels of importance of process parameters on mechanical properties were determined by using analysis of variance (ANOVA). The variation of tensile, flexural and impact properties with process parameters were mathematically modeled using the regression analysis. Finally, the presented models are also verified by a set of verification tests.

Abstract: Supersaturated design (SSD) has received much recent interest because of its potential in factor screening experiments. In this paper, we provide equivalent conditions for two columns to be fully aliased and consequently propose methods for constructing E(f NOD )- and χ 2 -optimal mixed-level SSDs without fully aliased columns, via equidistant designs and difference matrices. The methods can be easily performed and many new optimal mixed-level SSDs have been obtained. Furthermore, it is proved that the nonorthogonality between columns of the resulting design is well controlled by the source designs. A rather complete list of newly generated optimal mixed-level SSDs are tabulated for practical use.

Abstract: This paper presents the experimental study, development of mathematical model and parametric optimization for surface roughness in turning D2 steel using TiN coated carbide insert using Taguchi parameter design and response surface methodology. The experimental plan and analysis was based on the Taguchi L27 orthogonal array taking cutting speed (v), feed (f) and depth of cut (d) as important cutting parameters. The influence of the machining parameters on the surface finish has also been investigated and the optimum cutting condition for minimizing the surface roughness is evaluated. The optimal parametric combination for TiN coated cutting insert is found to be v3-f1-d3. The ANOVA result shows that feed the most significant process parameter on surface roughness followed by depth of cut. The cutting speed is found to be insignificant from the study. The RSM model shows good accuracy between predicted values and experimental values with 95% confidence intervals and adequate. It is concluded that the developed RSM model can be effectively utilized to predict the surface roughness in turning D2 steel.

Abstract: This paper examines the influence of cutting parameters, namely cutting speed, feed and depth of cut on the tangential component of cutting force in the rough longitudinal turning operation. Two experimental plans, one based on the common rotatable central composite design and the other based on the Taguchi method with orthogonal arrays and signal-to-noise ratio, have been used to analyse impact of cutting parameters on the tangential component of cutting force and to find optimal level of the cutting parameters. The comparison of results obtained by given experimental plans was performed. Finally, the features, the merits and the limitations of the presented optimisation approaches were discussed. method Centralni kompozicijski plan pokusa nasuprot Taguchijevoj metodi u optimizaciji tokarenja. U radu ,, , ,,

Abstract: Taguchi methods have proved to be successful over the last two decades for improvement of product quality and process performance. This study is carried out to simultaneously optimize the tribological properties: wear rate and frictional force of aluminum metal matrix composite. Al-Cu-Mg alloy reinforced with 6 Wt % of titanium dioxide was prepared using stir casting method. Dry sliding wear test was conducted to understand the tribological behavior of samples. The experiments were conducted as per the Taguchi design of experiment. The wear parameters chosen for the experiment were: sliding speed and load and sliding distance. Each parameter was assigned three levels. The experiment consists of 27 tests according to L27 orthogonal array. Signal to noise ratio analysis has been carried out to determine optimal parametric condition, which yields minimum wear rate and frictional force. Harrington’s desirability functional method is adopted for multifunctional optimization of tribological parameters and the confirmation experiments were conducted to verify the predicted model.

Abstract: Wire electrical discharge machining (WEDM) is a widely accepted non-traditional material removal process used to manufacture components with intricate shapes and profiles. The selection of optimum machining conditions for obtaining higher machining efficiency and increasing the accuracy of products are the most important task when the WEDM process is used for machining new advanced material such as nanocomposite ceramics.In this paper, a series of experiments has been carried out over a wide range of machining conditions. An L32 orthogonal array based on the Taguchi method for design of experiments is used to conduct the experiments. Then, by using a multilayer perceptron neural network, process modelling is performed and the most effective parameters on the process variables (i.e. material removal rate and surface roughness) are determined. Results demonstrate a very good modelling capacity of the proposed neural model. Finally, a genetic algorithm is used to optimize the process performance of WEDM. Add...

Abstract: Nowadays orthogonal arrays play important roles in statistics, computer science, coding theory and cryptography. The usual difference matrices are essential for the construction for many mixed orthogonal arrays. But there are also orthogonal arrays which cannot be obtained by the usual difference matrices, such as mixed orthogonal arrays of run size 60. In order to construct these mixed orthogonal arrays, a class of special so-called generalized difference matrices were discovered by Zhang (1989,1990,1993,2006) from the orthogonal decompositions of projection matrices. In this article, an interesting equivalent relationship between orthogonal arrays and the generalized difference matrices is presented and proved. As an application, a lot of new orthogonal arrays of run size 60 have been constructed.

Abstract: We propose two methods for constructing a new type of design, called a nested orthogonal array-based Latin hypercube design, intended for multi-fidelity computer experiments. Such designs are two nested space-filling designs in which the large design achieves stratification in both bivariate and univariate margins and the small design achieves stratification in univariate margins. These designs have better space-filling properties than nested Latin hypercube designs in which the large design possesses uniformity in univariate margins only. The first method expands an ordinary Latin hypercube design to a larger design that achieves uniformity in any one- or two-dimensional projection. The second method uses an orthogonal array with strength two to simultaneously construct a pair of nested orthogonal array-based Latin hypercube designs. Examples are given to illustrate the proposed methods. Sampling properties of the proposed designs are derived. Copyright 2011, Oxford University Press.

Abstract: Stainless steels (SS) are used for many commercial and industrial applications for their excellent corrosive resistance. SS are generally difficult to machine material due to their high strength and high work hardening tendency. Tool wear (TW) and surface roughness (SR) are widely considered most challenging aspect causing poor quality in machining of SS products. Optimization of cutting parameter is essential for the achievement of high quality and high rate of mass production. In this work, optimum cutting parameters for each performance measure is obtained by employing Taguchi techniques. The orthogonal array, signal to noise ratio and analysis of variance (ANOVA) are employed to study the performance characteristics in turning operation and SR and TW of the multilayer coated cutting tool for CNC turning of austenitic stainless steel (AISI 316) under are taken as responses for analysis. Further the multi layered feed forward artificial neural network (ANN) is developed to predict the SR and TW during turning process. Finally predicted responses were compared with the respective measured values and absolute percentage error was computed.

Abstract: This paper espouses the application of orthogonal array experiment to solve a class of engineering optimization problems encountered in systems engineering and architecting. It also illustrates the applicability of orthogonal array experiment in systems engineering and architecting with two examples: verification and validation of the performance of a bandwidth allocation algorithm and architecting of a system of systems to respond to small boat attacks by terrorists. The orthogonal array experiment approach does not call for linearization of nonlinear engineering optimization problems; using orthogonal arrays, it solves them directly by carrying out the smallest possible number of experiments and determining their solutions from the results of the experiments. The orthogonal array experiment method has been found to be effective and efficient for these problems. The feasibility of applying the orthogonal array experiment approach to these problems suggests its potential application to other optimization problems encountered in systems engineering and architecting. © 2010 Wiley Periodicals, Inc. Syst Eng 14: 208–222, 2011 © 2011 Wiley Periodicals, Inc.

Abstract: The present work attempts to overcome underlying assumptions in traditional Taguchi based optimization techniques highlighted in literature. Taguchi method alone fails to solve multi-response optimization problems. In order to overcome this limitation, exploration of grey relation theory, desirability function approach, utility theory etc. have been found amply applied in literature in combination with Taguchi method. But aforesaid approaches relies on the assumption that individual response features are uncorrelated i.e. independent of each other which are really impossible to happen in practice. The study takes into account this response correlation and proposes an integrated methodology in a case study on optimization of multiple bead geometry parameters of submerged arc weldment. Weighted Principal Component Analysis (WPCA) has been applied to eliminate response correlation and to convert correlated responses into equal or less number of uncorrelated quality indices called principal components. Based on individual principal components a Multi-response Performance Index (MPI) has been introduced to derive an equivalent single objective function which has been optimized (maximized) using Taguchi method. Experiments have been conducted based on Taguchi’s L25 Orthogonal Array design with combinations of process control parameters: voltage, wire feed, welding speed and electrode stick-out. Different bead geometry parameters: bead width, bead height, penetration depth and HAZ dimensions have been optimized. Optimal result has been verified by confirmatory test. The study highlights effectiveness of the proposed method for solving multi-objective optimization of submerged arc weld.

Abstract: This paper introduces a powerful technique that utilizes a hybrid Particle-Swarm Optimization (PSO) method for the design optimization of aperiodic linear phased arrays of tightly packed miniature meander-line dipole elements. Miniaturization is achieved by first introducing a fixed grid of reduced length, and then employing a hybrid PSO to determine the optimum meander-wire shape on the grid and the optimal element spacing. The purpose was to achieve comparable performance in terms of voltage standing-wave ratio (VSWR) and sidelobe levels during scanning to conventional full-size periodic phased arrays of linear half-wave dipoles. This design technique is applicable in cases where the desire for aperture miniaturization takes precedence over the reduction in gain that comes as a consequence. As one of the design criteria, the same number of antenna elements was maintained and tightly packed into a smaller aperture area. This allowed the antenna elements to be driven by lower-power transmitting modules for a given effective radiated power (ERP), compared to a thinned array with the same aperture size. This method also provides flexibility in controlling the self impedance of individual elements and the mutual coupling among array elements. It is hence capable of evolving compact array configurations with meander-line dipole elements that have well-behaved driving-point impedances and low sidelobe levels over a prescribed scan range. In order to overcome the optimization difficulty of arrays with a large number of antenna elements, orthogonal design with quantization (OD/Q) was employed for this mixed-valued optimization problem to generate relatively fit particles at the initialization stage. Several design examples were considered with parallel or planar grids, and with identical or different element configurations. Included among these examples was a design with 32 identical elements that achieved a 42% array-length reduction and a 16% element-size reduction, while providing a relative sidelobe level less than -10 dB and a VSWR less than 2:1 for each element over the scan range of ±30° from broadside.

Abstract: The influence of cutter geometry and cutting parameters during end milling on the surface texture of aluminium (Al) alloy 5083 was experimentally investigated. Eighteen pockets were manufactured having different combination of parameters values according to Taguchi L18 standard orthogonal array. Surface texture parameters (Ra, Ry, and Rz) were measured on three different passes on side surface of pockets and analyzed using statistical techniques. The results reveal that the cutting speed, the peripheral 2 nd relief angle, and the core diameter have significant effect in surface texture parameters. In order to establish a relationship between the performance measures and the process parameters, a set of additive models was produced. Finally, an evaluation (verification) experiment was performed. The acquired experimental values were found to be inside the confidence intervals provided by the additive models. These results confirm the accuracy of the proposed modeling approach.