Optimization of machining parameters in rotary EDM process by using the Taguchi method

Electrical discharge machining (EDM) is one of the advanced methods of machining. Most publications on the EDM process are directed towards non-rotational tools. But rotation of the tool provides a good flushing in the machining zone. In this study, the optimal setting of the process parameters on rotary EDM was determined. A total of three variables of peak current, pulse on time, and rotational speed of the tool with three types of electrode were considered as machining parameters. Then some experiments have been performed by using Taguchi's method to evaluate the effects of input parameters on material removal rate, electrode wear rate, surface roughness, and overcut. Moreover, the optimal setting of the parameters was determined through experiments planned, conducted, and analyzed using the Taguchi method. Results indicate that the model has an acceptable performance to optimize the rotary EDM process.     

Optimization of EDM process for multiple performance characteristics using Taguchi method and Grey relational analysis

Electrical discharge machining (EDM) is one of the most extensively used non-conventional material removal processes. The Taguchi method has been utilized to determine the optimal EDM conditions in several industrial fields. The method, however, was designed to optimize only a single performance characteristic. To remove that limitation, the Grey relational analysis theory has been used to resolve the complicated interrelationships among the multiple performance characteristics. In the present study, we attempted to find the optimal machining conditions under which the micro-hole can be formed to a minimum diameter and a maximum aspect ratio. The Taguchi method was used to determine the relations between machining parameters and process characteristics. It was found that electrode wear and the entrance and exit clearances had a significant effect on the diameter of the micro-hole when the diameter of the electrode was identical. Grey relational analysis was used to determine the optimal machining parameters, among which the input voltage and the capacitance were found to be the most significant. The obtained optimal machining conditions were an input voltage of 60V, a capacitance of 680pF, a resistance of 500Ω, the feed rate of 1.5μm/s and a spindle speed of 1500rpm. Under these conditions, a micro-hole of 40μm average diameter and 10 aspect ratio could be machined.     

Geometric optimization and performance analysis of radial MR valve using Taguchi orthogonal experiment method

Aiming at the problems of increasing external dimensions and deteriorating key performance indicators in the design process of magnetorheological (MR) valve by using structural optimization method, a geometric optimization design methodology for the optimal design of a MR valve structure under specific volume constraints is proposed in this article. The optimization methodology couples the finite element model (FEM) constructed in COMSOL software with the Taguchi orthogonal experiment and response surface technology to build an approximate response surface function for the identified independent variables. Suitable optimization algorithms are then utilized to determine the optimal geometry of the MR valve, thereby maximizing the valve performance. Firstly, a radial MR valve with a single excitation coil was presented, and its structure and working principle were also elaborated. A mathematical model of the pressure drop was derived on the basis of the Bingham-Papanastasiou non-Newtonian constitutive model of MR fluid and the magnetic circuit had been analyzed with the FE analysis methodology. Then, a second-order response surface model (RSM) had been fitted for the magnetic flux density in the radial flow channel and spool region of the radial MR valve based on the Taguchi orthogonal experimental design. The fitted model was a function of the four independent variables of the radial MR valve, and the accuracy of the developed response surface function over the entire design space had also been estimated. Meanwhile, predictions made by the RSM and FE models were evaluated by analysis of variance and it was exhibited that the RSM model’s results agree with FE result fairly. Subsequently, the geometric optimization problem had been formulated for the constructed RSM exploiting the genetic algorithm to find the global optimum geometrical parameters of the radial MR valve. Furthermore, the experimental test rig was setup to explore the pressure drop and the response time characteristics of the initial and optimal radial MR valve as well as the dynamic performance of the MR valve controlled cylinder system under different excitation conditions. The experimental results show that under the applied current of 2 A, the pressure drop and adjustable coefficient of the optimal radial MR valve observably increased with values of 3.15 MPa and 5.40, respectively, when compared to 2.11 MPa and 4.22 of their respective initial values. Also, at the applied current of 1.25 A, the damping force of the MR valve controlled cylinder system enlarged by 46 %, with its optimal value being 3.65 kN and initial value as 2.50 kN, which was an excellent verification of the correctness of the RSM and the effectiveness of the optimal design.

     

Tolerance design of robot parameters using Taguchi method

A robotic arm must be able to manipulate objects with high accuracy and repeatability. As with every physical system, there are number of noise factors cause uncertainty in the performance. A probabilistic approach has been used to model, the otherwise difficult to model, noise effects. This paper presents the approach utilised in selection of tolerance specification of robot kinematic and dynamic parameters using experimental design technique for reduction of performance variations. The concept of inner and outer orthogonal arrays proposed by Taguchi is employed to identify the significant parameters and select the optimal tolerance range. The performance measure, i.e. signal-to-noise ratio is utilised to validate by Monte Carlo simulations and to complement above study individual parameter tolerance sensitivity are investigated. To provide insight to investigation, parameter sensitivity maps are plotted. The tolerance specification selection methodology of a manipulator is illustrated by taking 2-DOF RR planar manipulator with payload.     

Multi-objective optimization of process parameters for the helical gear precision forging by using Taguchi method

Precision forging of the helical gear is a complex metal forming process under coupled effects with multi-factors. The various process parameters such as deformation temperature, punch velocity and friction conditions affect the forming process differently, thus the optimization design of process parameters is necessary to obtain a good product. In this paper, an optimization method for the helical gear precision forging is proposed based on the finite element method (FEM) and Taguchi method with multi-objective design. The maximum forging force and the die-fill quality are considered as the optimal objectives. The optimal parameters combination is obtained through S/N analysis and the analysis of variance (ANOVA). It is shown that, for helical gears precision forging, the most significant parameters affecting the maximum forging force and the die-fill quality are deformation temperature and friction coefficient. The verified experimental result agrees with the predictive value well, which demonstrates the effectiveness of the proposed optimization method.     

Roughness optimization of flow-formed tubes using the Taguchi method

The present study reports the effect of various flow-forming process parameters and roller geometry on the roughness of flow-formed tubes of commercial pure copper UNS C11000. Thickness reduction ratio, feed rate, angular speed of mandrel, attack angle of roller, roller tip radius, and smooth angle of roller were considered as variable parameters. The effects of these input parameters on the roughness have been critically analyzed using the Taguchi method. Through ANOVA analysis, it has been found that the roller tip radius is the most important parameter affecting roughness followed by thickness reduction ratio. Selection of an optimum combination of variable parameters was performed based on “average of results.” The minimum roughness of 1.37 μm was achieved when the process parameters were set at their optimum values.     

Surface roughness optimization of cold-sprayed coatings using Taguchi method

In this paper, Taguchi L 18 orthogonal array have been employed for depositing the electro-conductive coatings by varying various process parameters, i.e., substrate material, type of powder feeding arrangement, stagnation gas temperature, stagnation gas pressure, and stand-off distance. The response parameter of the coatings so produced is measured in terms of surface roughness. The optimum process parameters are predicted on the basis of analyses (ANOVA) of the raw data and signal to noise ratio. The significant process parameters in order of their decreasing percentage contribution are: stagnation pressure, stand-off distance, substrate material, stagnation temperature of the carrier gas, and feed arrangement of the powder particles, respectively.     

An optimization method for radial forging process using ANN and Taguchi method

In this study, the artificial neural network (ANN) and the Taguchi method are employed to optimize the radial force and strain inhomogeneity in radial forging process. The finite element analysis of the process verified by the microhardness test (to confirm the predicted strain distribution) and the experimental forging load published by the previous researcher are used to predict the strain distribution in the final product and the radial force. At first, a combination of process parameters are selected by orthogonal array for numerical experimenting by Taguchi method and then simulated by FEM. Then the optimum conditions are predicted via the Taguchi method. After that, by using the FEM results, an ANN model was trained and the optimum conditions are predicted by means of ANN (using genetic algorithm as global optimization procedure) and compared with those achieved by the Taguchi method. The optimum conditions are verified by FEM, and good agreement is found between the two sets of results.     

基于灰色关联分析的电火花加工不锈钢小孔工艺参数优化

采用DS307A高速穿孔机,开展在6mm厚不锈钢板上加工直径为1.2 mm小孔的试验研究。运用正交试验法,研究电火花加工电参数对加工时间、电极损耗和加工间隙的影响,并对试验结果进行灰色关联分析,得出最优加工参数。结果表明,经参数优化后,减少了加工时间、降低了电极损耗,以及表面粗糙度得以明显改善,满足快速精加工的技术要求。     

Multi-objective optimization of forming parameters for tube hydroforming process based on the Taguchi method

Tube hydroforming is an attractive manufacturing technology which is now widely used in many industries, especially the automobile industry. The purpose of this study is to develop a method to analyze the effects of the forming parameters on the quality of part formability and determine the optimal combination of the forming parameters for the process. The effects of the forming parameters on the tube hydroforming process are studied by finite element analysis and the Taguchi method. The Taguchi method is applied to design an orthogonal experimental array, and the virtual experiments are analyzed by the use of the finite element method (FEM). The predicted results are then analyzed by the use of the Taguchi method from which the effect of each parameter on the hydroformed tube is given. In this work, a free bulging tube hydroforming process is employed to find the optimal forming parameters combination for the highest bulge ratio and the lowest thinning ratio. A multi-objective optimization approach is proposed by simultaneously maximizing the bulge ratio and minimizing the thinning ratio. The optimization problem is solved by using a goal attainment method. An example is given to illustrate the practicality of this approach and ease of use by the designers and process engineers.     

Simultaneous optimization of multi-response problems in the Taguchi method using genetic algorithm

The optimization of multiple responses (or performance characteristics) has received increasing attention over the last few years in many manufacturing organizations. Most previous applications of the Taguchi method only emphasize the single-response problems, while the multi-response problems have received relatively little attention. Many Taguchi practitioners have employed past experience and engineering knowledge or judgement when dealing with multiple responses. The approach presented in this paper takes advantage of both the Taguchi method and genetic algorithm, which forms a robust and practical methodology in tackling multiple response optimization problems. The paper also presents a case study to illustrate the potential of this powerful integrated approach for tackling multiple response optimization problems. The variance analysis is also an integral part of the study, which identifies the most critical and statistically significant parameters.     

Taguchi and Gauss elimination method: A dual response approach for parametric optimization of CNC wire cut EDM of PRAlSiCMMC

Machining parameters tables provided by the machine tool manufacturers often do not meet the operator requirements and sometimes even do not provide efficient guidelines to manufacturing engineers. Hence, a suitable selection of machining parameters of CNC wire cut electrical discharge machining (EDM) process is necessary. This paper present a reliable set of parameters that demonstrate versatility, and numerous and diverse range based on experience and technology. We offer an experimental investigation to determine the parameters setting during the machining of aluminium-reinforced silicon carbide metal matrix composite (Al/SiC-MMC). The Taguchi method, a powerful tool for experimental design, is used to optimize the CNC-wire cut-EDM parameters. According to the Taguchi quality design Concept, a L₁₈ (2¹×3⁷) mixed orthogonal array was used to determine the S/N ratio, and an analysis of variance (ANOVA) and the F-test values were used to indicate the significant machining parameters affecting the machining performance. From experimental results and through ANOVA and F-test values, the significant factors are determined for each machining performance criteria, such as the metal removal rate, surface roughness, gap current and spark gap (gap width). Considering these significant CNC wire cut-EDM parameters, verification of the improvement in the quality characteristics for machining Al/SiC-MMC was made with a confirmation test with respect to the chosen initial or reference parameter setting. Mathematical models relating to the machining performance are established using the Gauss elimination method for the effective machining of Al/SiC-MMC. Yet again, confirmation test results also show that the developed mathematical models are appropriate for the effective machining of Al/SiC-MMC. The determined optimal combination of CNC-wire cut-EDM parameters obtained from the study satisfy the real requirement of quality machining of Al/SiC MMC in practice.     

Multi-objective optimization of injection molding process parameters in two stages for multiple quality characteristics and energy efficiency using Taguchi method and NSGA-II

In this paper, the parameters optimization of plastic injection molding (PIM) process was obtained in systematic optimization methodologies by two stages. In the first stage, the parameters, such as melt temperature, injection velocity, packing pressure, packing time, and cooling time, were selected by simulation method in widely range. The simulation experiment was performed under Taguchi method, and the quality characteristics (product length and warpage) of PIM process were obtained by the computer aided engineering (CAE) method. Then, the Taguchi method was utilized for the simulation experiments and data analysis, followed by the S/N ratio method and ANOVA, which were used to identify the most significant process parameters for the initial optimal combinations. Therefore, the range of these parameters can be narrowed for the second stage by this analysis. The Taguchi orthogonal array table was also arranged in the second stage. And, the Taguchi method was utilized for the experiments and data analysis. The experimental data formed the basis for the RSM analysis via the multi regression models and combined with NSGS-II to determine the optimal process parameter combinations in compliance with multi-objective product quality characteristics and energy efficiency. The confirmation results show that the proposed model not only enhances the stability in the injection molding process, including the quality in product length deviation, but also reduces the product weight and energy consuming in the PIM process. It is an emerging trend that the multi-objective optimization of product length deviation and warpage, product weight, and energy efficiency should be emphasized for green manufacturing.     

Optimization of green sand casting process parameters by using Taguchi’s method

This paper analyses various significant process parameters of the green sand casting process. An attempt has been made to obtain optimal settings of the green sand casting process in order to yield the optimum quality characteristics of the spheroidal graphite (SG) cast iron rigid coupling castings. The process parameters considered are: green strength, moisture content, permeability and mould hardness. The effect of selected process parameters and its levels on the casting defects and the subsequent optimal settings of the parameters have been accomplished using Taguchi’s parameter design approach. The result indicates that the selected process parameters significantly affect the casting defects of SG cast iron rigid coupling castings. The estimation of the optimum performance characteristics of green sand casting at the optimum levels of parameters is done in this paper and the results are verified by confirming with practical experiments.     

Multi-response optimization of Micro-EDM process parameters on AISI304 steel using TOPSIS

The Technique for order preference by similarity to ideal solution (TOPSIS) method of optimization is used to analyze the process parameters of the micro-Electrical discharge machining (micro-EDM) of an AISI 304 steel with multi-performance characteristics. The Taguchi method of experimental design L27 is performed to obtain the optimal parameters for inputs, including feed rate, current, pulse on time, and gap voltage. Several output responses, such as the material removal rate, electrode wear rate, overcut, taper angle, and circularity at entry and exit points, are analyzed for the optimal conditions. Among all the investigated parameters, feed rate exerts a greater influence on the hole quality. ANOVA is employed to identify the contribution of each experiment. The optimal level of parameter setting is maintained at a feed rate of 4 μm/s, a current of 10 A, a pulse on time of 10 μs, and a gap voltage of 10 V. Scanning electron microscope analysis is conducted to examine the hole quality. The experimental results indicate that the optimal level of the process parameter setting over the overall performance of the micro-EDM is improved through TOPSIS.     

Parametric optimization for tumour identification: bioheat equation using ANOVA and the Taguchi method

Breast cancer is the number one killer disease among women. It is known that early detection of a tumour ensures better prognosis and higher survival rate. In this paper an intelligent, inexpensive and non-invasive diagnostic tool is developed for aiding breast cancer detection objectively. This tool is based on thermographic scanning of the breast surface in conjunction with numerical simulation of the breast using the bioheat equation. The medical applications of thermographic scanning make use of the skin temperature as an indication of an underlying pathological process. The thermal pattern over a breast tumour reflects the vascular reaction to the abnormality. Hence an abnormal temperature pattern may be an indicator of an underlying tumour. Seven important parameters are identified and analysis of variance (ANOVA) is performed using a 2n design (n = number of parameters, 7). The effect and importance of the various parameters are analysed. Based on the above 2(7) design, the Taguchi method is used to optimize the parameters in order to ensure the signal from the tumour maximized compared with the noise from the other factors. The model predicts that the ideal setting for capturing the signal from the tumour is when the patient is at basal metabolic activity with a correspondingly lower subcutaneous perfusion in a low temperature environment.     

Multi response optimization of machining parameters of drilling Al/SiC metal matrix composite using grey relational analysis in the Taguchi method

This paper presents a new approach for the optimization of drilling parameters on drilling Al/SiC metal matrix composite with multiple responses based on orthogonal array with grey relational analysis. Experiments are conducted on LM25-based aluminium alloy reinforced with green bonded silicon carbide of size 25 μm (10% volume fraction). Drilling tests are carried out using TiN coated HSS twist drills of 10 mm diameter under dry condition. In this study, drilling parameters namely cutting speed, feed and point angle are optimized with the considerations of multi responses such as surface roughness, cutting force and torque. A grey relational grade is obtained from the grey analysis. Based on the grey relational grade, optimum levels of parameters have been identified and significant contribution of parameters is determined by ANOVA. Confirmation test is conducted to validate the test result. Experimental results have shown that the responses in drilling process can be improved effectively through the new approach.     

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

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.