Abstract: This work presents a study on the applicability of radial base function (RBF) neural networks for prediction of Roughness Average (R"a) in the turning process of SAE 52100 hardened steel, with the use of Taguchi's orthogonal arrays as a tool to design parameters of the network. Experiments were conducted with training sets of different sizes to make possible to compare the performance of the best network obtained from each experiment. The following design factors were considered: (i) number of radial units, (ii) algorithm for selection of radial centers and (iii) algorithm for selection of the spread factor of the radial function. Artificial neural networks (ANN) models obtained proved capable to predict surface roughness in accurate, precise and affordable way. Results pointed significant factors for network design have significant influence on network performance for the task proposed. The work concludes that the design of experiments (DOE) methodology constitutes a better approach to the design of RBF networks for roughness prediction than the most common trial and error approach.

Abstract: This paper presents an alternative method to optimize process parameters of resistance spot welding (RSW) towards weld zone development. The optimization approach attempts to consider simultaneously the multiple quality characteristics, namely weld nugget and heat affected zone (HAZ), using multi-objective Taguchi method (MTM). The experimental study was conducted for plate thickness of 1.5 mm under different welding current, weld time and hold time. The optimum welding parameters were investigated using the Taguchi method with L9 orthogonal array. The optimum value was analyzed by means of MTM, which involved the calculation of total normalized quality loss (TNQL) and multi signal to noise ratio (MSNR). A significant level of the welding parameters was further obtained by using analysis of variance (ANOVA). Furthermore, the first order model for predicting the weld zone development is derived by using response surface methodology (RSM). Based on the experimental confirmation test, the proposed method can be effectively applied to estimate the size of weld zone, which can be used to enhance and optimized the welding performance in RSW or other application.

Abstract: Al-7075 alloy-base matrix, reinforced with mixtures of silicon carbide (SiC) and boron carbide (B4C) particles, know as hybrid composites have been fabricated by stir casting technique (liquid metallurgy route) and optimized at different parameters like sliding speed, applied load, sliding time, and percentage of reinforcement by Taguchi method. The specimens were examined by Rockwell hardness test machine, Pin on Disc, Scanning Electron Microscope (SEM) and Optical Microscope. A plan of experiment generated through Taguchi’s technique is used to conduct experiments based on L27 orthogonal array. The developed ANOVA and the regression equations were used to find the optimum wear as well as co-efficient of friction under the influence of sliding speed, applied load, sliding time and percentage of reinforcement. The dry sliding wear resistance was analyzed on the basis of “smaller the best”. Finally, confirmation tests were carried out to verify the experimental results.

Abstract: In this research work an attempt has been made to minimize flank wear of uncoated carbide inserts while machining AISI 1045 steel by finite element analysis. Tool wear is the predominant factor that causes poor surface finish and is responsible for the dimensional accuracy of the machined surface. The quality of component produced decides the effectiveness and competitiveness of any manufacturing industry. In this analysis, the effect of tool geometries on performance measures of flank wear, surface roughness and cutting forces generated are evaluated. Three levels of cutting insert shape, relief angle and nose radius are chosen. Taguchi’s Design of experiment (DOE) is used to design the experiments. For three parameters and three levels a suitable L9 Orthogonal array is selected. Based on the designed experiment, simulation analysis is carried out using DEFORM-3D, a machining simulation and analysis software and the output quality characteristics are analysed by statistical techniques like Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA). A validation finite element simulation is conducted with the obtained optimum tool geometry, which is also verified experimentally. It is observed that the performance of the determined tool geometry provides satisfactory results. (Received in August 2011, accepted in November 2011. This paper was with the authors 1 month for 1 revision.)

Abstract: Metallic, diamond-like carbon (Me-DLC) coatings are widely used in the mold industry due to their excellent wear resistance. In this paper, zirconium-containing DLC (Zr-DLC) coatings are prepared using an unbalanced magnetron sputtering process. Factors that affect the wear resistance of coatings consist of friction coefficients, hardness and anti-sticking properties. This paper aims to develop a method that optimizes the multi-objective properties of Zr-DLC coatings. For statistical purposes, the experimental parameters for the Zr-DLC coatings were put in place with a L18(3^5) orthogonal array. In order to optimize these properties, a method combining the grey, fuzzy and Taguchi approaches was established. While using the developed grey-fuzzy Taguchi method (GFTM), the experimental results from four properties can be integrated into a performance index. A comparison of the integrated performance index between the initial and optimal conditions shows that the magnitude increases from 0.46 to 0.81. The gain for each property by the GFTM from the initial condition is reported as 35% positive.

Abstract: We present a new method for constructing nearly orthogonal Latin hypercubes that greatly expands their availability to experimenters. Latin hypercube designs have proven useful for exploring complex, high-dimensional computational models, but can be plagued with unacceptable correlations among input variables. To improve upon their effectiveness, many researchers have developed algorithms that generate orthogonal and nearly orthogonal Latin hypercubes. Unfortunately, these methodologies can have strict limitations on the feasible number of experimental runs and variables. To overcome these restrictions, we develop a mixed integer programming algorithm that generates Latin hypercubes with little or no correlation among their columns for most any determinate run-variable combination—including fully saturated designs. Moreover, many designs can be constructed for a specified number of runs and factors—thereby providing experimenters with a choice of several designs. In addition, our algorithm can be used to quickly adapt to changing experimental conditions by augmenting existing designs by adding new variables or generating new designs to accommodate a change in runs.

Abstract: When using the Taguchi method, an L18 or L27 orthogonal array is usually adopted. However, this requires many experiments (18 or 27 runs, respectively), consuming time, and resources. This study proposes a progressive Taguchi neural network model, which combines the Taguchi method with the artificial neural network to construct a prediction model for a CO2 laser cutting experiment. During CO2 laser cutting, energy from the moving laser is accumulative. The paper develops an integral equation of energy density during laser beam movement and lets it determine the sliding level of control factor. Meanwhile, the paper proposes that in Stage 1, only less number of experiments is required to be conducted by L9 orthogonal array. After the crucial supplementary experimental training samples proposed in Stage 2 are also included, high-accuracy prediction of artificial neural network can be completed. Based on analysis from the progressive Taguchi neural network, the Stage 1 preliminary network—with only a few available experimental examples—has achieved good predictive ability from regions near the Taguchi control points. For regions further out, the predictions have been increasingly unreliable. Nevertheless, the high precision of Stage 2 Taguchi network has good predictive results for all regions.

Abstract: The evolving concept of minimum quantity of lubrication (MQL) in machining is considered as one of the solutions to reduce the amount of lubricant to address the environmental, economical and ecological issues. This paper investigates the influence of cutting speed, feed rate and different amount of MQL on machining performance during turning of brass using K10 cemented carbide tool. The experiments have been planned as per Taguchi's orthogonal array and the second order surface roughness model in terms of machining parameters was developed using response surface methodology (RSM). The parametric analysis has been carried out to analyze the interaction effects of process parameters on surface roughness. The optimization is then carried out with genetic algorithms (GA) using surface roughness model for the selection of optimal MQL and cutting conditions. The GA program gives the minimum values of surface roughness and the corresponding optimal machining parameters.

Abstract: Plastic injection molding is an important process to produce thin-shell parts However, the difficulty in adjusting optimum process conditions may cause defects of the injected-molded parts such as shrinkage This study investigates on the optimum combinations of process conditions on shrinkage of an injected-molded part of the DVD-ROM cover based on Taguchi method In doing this, a series of Moldflow analyses have been performed as per L27 orthogonal array design with each analysis by means of the process conditions of mold temperature, melt temperature, injection pressure, injection time, and cooling time In the meantime, signal-to-noise (S/N) ratio is utilized to determine the optimum combinations of the process conditions for shrinkage through analysis of variance (ANOVA) ANOVA is further used to find which of the process conditions are statistically significant Finally, confirmation tests at the optimum combinations of the process conditions were executed to verify the robustness and the effectiveness of Taguchi method within 95% confidence interval From the findings, it can be stated that Taguchi method is a powerful tool for evaluating the defect of shrinkage in the plastic injection molding

Abstract: The purpose of this paper is to optimize the sand casting process parameters of the castings manufactured in iron foundry by maximizing the signal to noise ratios and minimizing the noise factors using Taguchi method. A Taguchi approach is used to capture the effects of signal to noise ratio of the experiments depending upon the orthogonal arrays used, an analysis of variance and optimum conditions are found. This paper demonstrates a robust method for formulating a strategy to find optimum factors of process and interactions with a small number of experiments. The process parameters considered are moisture, sand particle size, green compression strength, mould hardness, permeability, pouring temperature, pouring time and pressure test. The results indicated that the selected process parameters significantly affect the casting defects in the foundry. The improvement expected in reduction of casting defects is found to be 37.66 percent.

Abstract: Present investigation applied the designs of experiments and grey relational analysis (GRA) approach to optimise parameters for electrical discharge machining process of 6061Al/Al2O3p/20P aluminium metal matrix composites. Planning of experiments was based on an L18 (2^1 × 3^5) orthogonal array to determine an optimal setting. The process parameters included one noise factor, aspect ratio having two levels and five control factors, viz. pulse current, pulse ON time, duty cycle, gap voltage and tool electrode lift time with three levels each. The material removal rate, tool wear rate and surface roughness were selected as the evaluation criteria, in this study. Optimal combination of process parameters is determined by the grey relational grade (GRG) obtained through GRA for multiple performance characteristics. Analysis of variance for the GRG is also implemented. It is shown that through GRA, the optimization of the multiple performance characteristics can be greatly simplified.

Abstract: We applied combined response surface methodology (RSM) and Taguchi methodology (TM) to determine optimum parameters for minimum surface roughness (Ra) and vibration (Vb) in external cylindrical grinding. First, an experiment was conducted in a CNC cylindrical grinding machine. The TM using L27 orthogonal array was applied to the design of the experiment. The three input parameters were workpiece revolution, feed rate and depth of cut; the outputs were vibrations and surface roughness. Second, to minimize wheel vibration and surface roughness, two optimized models were developed using computer-aided single-objective optimization. The experimental and statistical results revealed that the most significant grinding parameter for surface roughness and vibration is workpiece revolution followed by the depth of cut. The predicted values and measured values were fairly close, which indicates (RRa2=94.99 and RVb2=92.73) that the developed models can be effectively used to predict surface roughness and vibration in the grinding. The established model for determination of optimal operating conditions shows that a hybrid approach can lead to success of a robust process.

Abstract: This paper describes the development of response models such as surface roughness and flank wear for machining Inconel 718. Several experiments are conducted by varying the cutting speed, feed, and depth of cut as machining parameters based on the design of experiments. The surface roughness and flank wear are measured as responses against these parameters. Response optimisation has been presented showing the global solutions for the factors cutting speed, feed and depth of cut and their predicted responses along with the composite desirability of the machining process. Contour plots and surface plots for the responses are also presented. Also this paper is an attempt to Taguchi optimisation technique to study the machinability performances of Inconel 718. Taguchi approach is an efficient and effective experimental method in which a response variable can be optimised, given various control and noise factors, using fewer experiments than a factorial design. An orthogonal array of L27 was used. Signal-to-noise ratio and ANOVA analyses were carried out to identify the significant factors.

Abstract: Nowadays, so as to adapt to the global market, where competition is getting tougher, firms producing through the modern production approach need to bring not the only performance of the system designed both during the research and development phase and the production phase but also the performance of the product to be developed as well as the process to be improved to the highest level. The Taguchi method is an experimental design technique seeking to minimize the effect of uncontrollable factors, using orthogonal arrays. It can also be designed as a set of plans showing the way data are collected through experiments. Experiments are carried out using factors defined at different levels and a solution model generated in ARENA 3.0 program using SIMAN, which is a simulation language. Many experimental investigations reveal that the speed and capacity of automated-guided vehicle, the capacities of local depots, and the mean time between shipping from the main depot are the major influential parameters that affect the performance criteria of the storage system. For the evaluation of experiment results and effects of related factors, variance analysis and signal/noise ratio are used and the experiments are carried out in MINITAB15 according to Taguchi L16 scheme. The purpose of this study is to prove that experimental design is an utilizable method not only for product development and process improvement but it can also be used effectively in the design of material handling–transfer systems and performance optimization of automation technologies, which are to be integrated to the firms.

Abstract: This article discusses the application of Taguchi's robust parameter design RPD approach in the design of a motor in a large electrical company in India. There used to be specific customer requirements related to temperature rise and low efficiency of the existing model of motor, which the organisation was unable to meet. Taguchi's parameter design approach was successfully applied to derive the optimum design. Orthogonal arrays were used to design the experiments with 13 control factors, each at 3 levels and 2 noise factors. The experimentation was carried out by a computer simulation and the data were analysed using signal-to-noise ratio method. From the analysis of variance along with main effect plots, the optimum factor level combination for the new product was reached. As per the optimum design, prototype was made and tested with respect to the customer requirements and was found to give satisfactory results for all performance characteristics. This approach has given the result in just 10 weeks' time, whereas the traditional design approach used to take 12 to 15 months to arrive at the optimum design values.

Abstract: This paper deals with an investigation of the effect and optimization of control parameters on the system performance in waste heat recovery application using mechanical heat pump (MHP). The experimental studies have been conducted under varying compressor speed, wastewater temperature and flow rate. The experiments have been planned based on Taguchi’s L27 orthogonal array with each trial performed under different conditions of compressor’s speed, wastewater temperature and flow rate. The optimum parameter combination has been obtained by using the analysis of signal-to-noise (S/N) ratio. The level of importance of the control parameters on the system performance has been determined by using analysis of variance (ANOVA). Main effects plots and interaction effects plots have been utilized to optimize and analyze the relation between the control parameters and the system performance. The results obtained from Taguchi method were also compared with ANN results. The experimental study indicated that it is possible to increase system performance significantly in the waste heat recovery application using MHP.

Abstract: The paper will help practitioners to select strength 3 designs that are useful for screening both main effects and two-factor interactions. We calculated word length patterns, correlations of four-factor interaction contrast vectors with the intercept and ranks of the two-factor interaction matrices for all non-equivalent two-level orthogonal arrays of strength 3 and run sizes up to 48. On the basis of these characteristics, there are a limited number of designs that can be recommended for practical use. © 2011 Royal Statistical Society.

Abstract: Friction welding of tube-to-tube plate using an external tool (FWTPET) process with filler plate was successfully applied and optimized for joining commercially pure aluminum tube and tube plate. Taguchi approach was applied to determine the most influential control factors which will yield better joint strength. L9 orthogonal array was used in this study. Through the Taguchi parametric design approach, the optimum levels of process parameters were determined. The percentage of contribution of each process parameter was determined by Analysis of variance. The predicted optimal value of joint strength was found to be 83.26 MPa. The results were confirmed by further experiments.

Abstract: Micro-machining is the basic technology of micro-engineering for the production of micro-sized parts and components. Microend milling is the most important micromachining process, widely used for the manufacturing industries due to its capability of producing tedious geometric surfaces with good accuracy and surface finish. In micro end milling material removal rate is one of the important aspects, which require attention both from industry personnel as well as in Research and development. In modern industry one of the trends is to manufacture low cost product in short time. MRR which indicates processing time of the work piece and it is an important factor that greatly influences production rate and cost. MRR greatly vary with the change of cutting process parameters. This paper focuses the taguchi technique for the optimization in micro-end milling operation to achieve maximum metal removal rate (MRR) considering the spindle speed, feed rate and depth of cut as the cutting parameters. An orthogonal array, signal-to-noise (S/N) ratio and Pareto analysis of variance (ANOVA) are employed to analyze the effect of these milling parameters. The analysis of the result shows that the optimal combination for higher metal removal rate (MRR) is medium cutting speed, high feed rate and high depth of cut. Using Taguchi method for design of experiment (DOE), other significant effects such as the interaction among milling parameters are also investigated. The study shows that the Taguchi method is suitable to solve the stated problem. Based on the verification experiment it is concluded that the percentage of error of response was less.

Abstract: Here, we applied the Taguchi method, an engineering optimization process, to successfully determine the optimal conditions for three SYBR Green I-based quantitative PCR assays. This method balanced the effects of all factors and their associated levels by using an orthogonal array rather than a factorial array. Instead of running 27 experiments with the conventional factorial method, the Taguchi method achieved the same optimal conditions using only nine experiments, saving valuable resources.

Abstract: An orthogonal genetic algorithm (OGA) is applied to optimize the planar thinned array with a minimum peak sidelobe level. The method is a genetic algorithm based on orthogonal design. A crossover operator formed by the orthogonal array and the factor analysis is employed to enhance the genetic algorithm for optimization. In order to evaluate the performance of the OGA, 20×10-element planar thinned arrays have been designed to minimize peak sidelobe level. The optimization results by the OGA are better than the previously published results.

Abstract: In this paper, we define a class of almost orthogonal rational functions of Legendre type in a new manner. Relations of these functions with classical exponentional functions orthogonal over interval (0, ∞), as well as classical polynomials orthogonal over (0, 1) are explained. Defining relations of these functions can be used for designing almost orthogonal filters. These filters are generators of orthogonal signals and can be successfully applied in finding the best signal approximation in the sense of the mean square error. The filters orthogonal property enables building of physical (in this case electrical) models of dynamical systems (the sources of signals to be approximated) either with less components for the same model accuracy or higher accuracy for the same number of components than the other known models. New filters represent further improvement of previously designed filters, by the same authors, in the sense of simplicity, higher accuracy, lesser approximation time and even a possibility to approximate signals generated by systems with built-in imperfections. Series of experiments were performed to analyze the dependence of approximation accuracy and the number of filters sections.

Abstract: This study presents a systematic approach to determine effect of process parameters on indentation as a primary & initial measure of weld quality and subsequently tensile strength, nugget diameter and penetration. To achieve the objective an attempt has been made to select important welding parameters like welding current, weld cycle, hold time & cool cycle using quality tools, available literature and on scientific reasons. On the selected parameters, Experiment have been conducted as per Taguchi method and fixed the levels for the parameters. The experiment has four factors and all factors are at two levels. To have wide spectrum of analysis and variability with time, L32 Orthogonal Array (OA) experiments are conducted. Optimum welding parameters determined by Taguchi method improved indentation which in turn confirms the value of nugget size, tensile strength and penetration. Analysis of variance (ANOVA) and F-test has been used for determining most significant parameters affecting the spot weld parameters. Keywords: Welding parameters; Taguchi Method; Resistance spot welding (RSW); Orthogonal array; ANOVA

Abstract: The demand for closely controlling both dimensional and geometrical accuracy of engineering components made up of difficult-to-shape material is increasing continuously. The wider and newer application requirements are very demanding. To attain the closer tolerances with required surface finish, the most acceptable abrasive machining process is grinding process. Cylindrical grinding is one of the important metal cutting processes used extensively in the finishing operations. Metal removal rate and surface finish are the important output responses in the production with respect to quantity and quality respectively. The main objective of this paper is to arrive at the optimal grinding conditions that will minimize surface roughness and maximize metal removal rate when grinding AISI 5120 steel. Empirical models were developed using design of experiments by Taguchi L9 Orthogonal Array and the adequacy of the developed model is tested with ANOVA. The developed model can be used by the different manufacturing firms to select appropriate combination of machining parameters to achieve an optimal metal removal rate (MRR) and surface roughness (R a). The input parameters considered are: wheel speed, work speed, number of passes and depth of cut and the responses are metal removal rate (MRR) and surface roughness (R a). The results were further validated by conducting confirmation experiments.

Abstract: This study investigated the multi-response optimization of turning process for an optimal parametric combination to yield minimum cutting forces and surface roughness with maximum material removal rate (MRR) using the combination of Grey relational analysis (GRA) and Taguchi method. Nine experimental runs based on an orthogonal array of Taguchi method were performed to derive objective functions to be optimized within experimental domain. The objective functions have been selected in relation to parameters of cutting process: cutting force, surface roughness and MRR. The Taguchi approach followed by Grey relational analysis to solve the multi-response optimization problem. The significance of factors on overall quality characteristics of the cutting process has also been evaluated quantitatively by the analysis of variance method (ANOVA). Optimal results have been verified through additional experiments. This shows proper selection of the cutting parameters produces, high material removal rate with better surface roughness and lower cutting force.