Abstract: In this study, it is attempted to give an insight into the injection processability of three self-prepared polymers from A to Z. This work presents material analysis, injection molding simulation, design of experiments alongside considering all interaction effects of controlling parameters carefully for green biodegradable polymeric systems, including polylactic acid(PLA), polylactic acid-thermoplastic polyurethane(PLA-TPU) and polylactic acid-thermoplastic starch(PLA-TPS). The experiments were carried out using injection molding simulation software Autodesk Moldflow?in order to minimize warpage and volumetric shrinkage for each of the mentioned systems. The analysis was conducted by changing five significant processing parameters, including coolant temperature, packing time, packing pressure, mold temperature and melt temperature. Taguchi’s L27(35) orthogonal array was selected as an efficient method for design of simulations in order to consider the interaction effects of the parameters and reduce spurious simulations. Meanwhile, artificial neural network(ANN) was also used for pattern recognition and optimization through modifying the processing conditions. The Taguchi coupled analysis of variance(ANOVA) and ANN analysis resulted in definition of optimum levels for each factor by two completely different methods. According to the results, melting temperature, coolant temperature and packing time had significant influence on the shrinkage and warpage. The ANN optimal level selection for minimization of shrinkage and/or warpage is in good agreement with ANOVA optimal level selection results. This investigation indicates that PLA-TPU compound exhibits the highest resistance to warpage and shrinkage defects compared to the other studied compounds.

Abstract: This paper reports the effect of process parameters on material removal rate (MRR) and surface roughness (Ra) in wire electro discharge machining of AISI D2 steel. The wire electro discharge machining characteristics of AISI D2 steel have been investigated using an orthogonal array of design. The pulse on time and servo voltage are the most significant parameter affecting MRR and surface roughness during WEDM process. The simultaneous performance characteristics MRR and surface roughness was optimized by Taguchi based utility approach. The machined surface hardness is higher than the bulk material hardness due to the repetitive quenching effect and contained various oxides in the surface recast layer. The experiments were performed by different cutting conditions of pulse on time (T on ), pulse off time (T off ), servo voltage (SV) and wire feed (WF) by keeping work piece thickness constant. Taguchi L27 orthogonal array of experimental design is employed to conduct the experiments. Multi-objective optimization was performed using Taguchi based utility approach to optimize MRR and Ra. Analysis of means and variance on to signal to noise ratio was performed for determining the optimal parameters. It reveals that the combination of Ton3, Toff1, SV1, WF2 parameter levels is beneficial for maximizing the MRR and minimizing the Ra simultaneously. The results indicated that the pulse on time is the most significant parameter affects the MRR and Ra. The melted droplets, solidified debris around the craters, cracks and blow holes were observed on the machined surface for a higher pulse on time and lower servo voltage. Recast layer thickness increased with an increase in pulse on time duration. The machined surface hardness of D2 steel is increased due to the repetitive quenching effect and formation oxides on the machined surface.

Abstract: Every manufacturing or production unit should concern about the quality of the product. Apart from quality, there exists other criterion, called productivity which is directly proportional to the profit level. Every manufacturing industry aims at producing a large number of products in relatively lesser time. In any machining process, it is most important to determine the optimal settings of machining parameters aiming at reduction of production costs and achieving the desired product quality. If the problem is related to a single quality attribute then it is called single objective optimization. If more than one attribute comes into consideration it is very difficult to select the optimal setting which can achieve all quality requirements simultaneously. In this work, EN-24 alloy steel work pieces were turned on Computer Numerical Controlled (CNC) lathe by using Cemented carbide tool (coated). The influence of four cutting parameters, cutting speed, feed rate, depth of cut, and tool nose radius on minuscule surface roughness and material removal rate (MRR) were analyzed on the basis of Response Surface Methodology approach. The experimental results were collected by following the Taguchi's L16 mixed Orthogonal Array design.

Abstract: Load flow studies are crucial in investigations of operation and planning problems in the power systems. Traditional methods for determining load flow are based on deterministic approaches. However, the parameters of a power system (such as load and renewable power generation) may be uncertain. An exact probabilistic load flow (PLF) study requires a long CPU time due to many convolution computations involving probability density functions. This paper proposes a novel PLF method that is based on Taguchi's orthogonal arrays. The proposed method utilises a few deterministic load flow solutions that are obtained using Taguchi's method to estimate the means and standard deviations of bus voltages, phase angles, line flows, and other metrics. A load flow calculation corresponds to an experiment in Taguchi's method. An optimal experiment is also specified by considering the largest deviation from the nominal load flow solution. A 25-bus standalone power system and a modified Institute of Electrical and Electronics Engineers (IEEE) 118-bus system are tested. The simulation results show that the proposed method not only requires fewer deterministic load flow solutions to perform PLF analysis than the traditional point-estimate method but also yields accurate means and standard deviations of bus voltages and line flows.

Abstract: WC–Co composite material is highly demanded in manufacturing industries, because of its unique properties such as excellent hardness with toughness, higher mechanical strength, and good dimensional stability The present investigation is aimed at studying the impact of different experimental conditions (by varying cobalt content, thickness of work piece, tool profile, tool material, abrasive grit size, and power rating) on responses of interest (material removal rate and tool wear rate) in ultrasonic drilling of WC–Co composite material The experiments have been planned by using Taguchi's L-36 orthogonal array and grey relation analysis has been applied for optimization of multiple responses Analysis of variance is also employed to find the significant factors Significant effects are observed for process variables such as cobalt content, abrasive grain size, and power level Tools with higher hardness delivered better machining performance

Abstract: In this work, a modified tool design was adopted to drill holes in the dry EDM process. Experiments were conducted on AISI D2 steel using a copper electrode as the tool. Taguchi’s L27 orthogonal array was used to design the experiments. Discharge current (I), pulse on time (T ON), Voltage (V), pressure (P) and tool rotational speed (N) were chosen as the various input parameters. The grey relational analysis was used to determine the optimal level of parameters to achieve better results. The experimental data were also statistically analysed by using the ANOVA test. The current (I) was found to be the most influential parameter followed by the pressure (P). The surface morphology and microstructure of the machined surface were analysed, and it was found that better surface characteristics were exhibited on the surface machined using the optimal level of parameters.

Abstract: This paper discusses the process parameters for fused deposition modelling (FDM). Layer thickness, Orientation angle and shell thickness are the process variables considered for studies. Ultimate tensile strength, dimensional accuracy and manufacturing time are the response parameters. For number of experimental runs the taguchi's L9 orthogonal array is used. Taguchis S/N ratio was used to identify a set of process parameters which give good results for respective response characteristics. Effectiveness of each parameter is investigated by using analysis of variance. The material used for the studies of process parameter is Nylon.

Abstract: As a successful solution applied to hard machining, the minimum quantity lubricant (MQL) has already been established as an alternative to flood coolant processing. The optimization of MQL parameters and cutting parameters under MQL condition are essential and pressing. The study was divided into two parts. In the first part of this study, the Taguchi method was applied to find the optimal values of MQL condition in the hard milling of AISI H13 with consideration of reduced surface roughness. The L9 orthogonal array, the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were employed to analyze the effect of the performance characteristics of MQL parameters (i.e., cutting fluid type, pressure, and fluid flow) on good surface finish. In the results section, lubricant and pressure of MQL condition are determined to be the most influential factors which give a statistically significant effect on machined surfaces. A verifiable experiment was conducted to demonstrate the reliability of the results. In the second section, the optimized MQL parameters were applied in a series of experiments to find out cutting parameters of hard milling. The Taguchi method was also used to optimize the cutting parameters in order to obtain the best surface roughness. The design of the experiment (DOE) was implemented by using the L27 orthogonal array. Based on an analysis of the signal-to-noise response and ANOVA, the optimal values of cutting parameters (i.e., cutting speed, feed rate, depth-of-cut and hardness of workpiece) were introduced. The results of the present work indicate feed rate is the factor having the most effect on surface roughness.

Abstract: Wire-cut electrical discharge machining (WEDM) is one of the important non-traditional machining processes to cut hard and high strength materials. It was observed from the literature that some environmental pollutants had been emitted owing to thermal decomposition of the liquid dielectric mediums used in WEDM. In this near-dry WEDM process, oxygen-mist is used as a dielectric medium which encourages the eco-friendly cutting process owing to minimal usage of liquid-based dielectric medium. In this paper, the experiments have been performed using the compressed oxygen gas mixed with minimum quantity of demineralised water as a dielectric medium. The design of experiments has been performed using Taguchi's L27 orthogonal array. The spark-current, pulse-on-time, oxygen-mist inlet pressure and mixing flow rate are selected as input parameters, and material removal rate and surface roughness are considered as response characteristics. After the experimentation, the regression analysis has been employed to develop the best mathematical models for the multi-objective optimisation purpose. Multi-objective artificial bee colony (MOABC) algorithm is introduced to predict the optimal set of input and output parameters using non-dominated Pareto-optimal-front solutions.

Abstract: A large displacement and a high first natural frequency are two main concerns for any flexure-based positioning system. A two-degree-of-freedom (DOF) flexure-based mechanism (FBM) with a modified double-lever amplification mechanism is first designed. This study then proposes a multi-objective optimal design of the 2-DOF FBM using the hybrid approach of grey-Taguchi coupled response surface methodology and entropy measurement. The design variables of the 2-DOF FBM include the thickness of the flexure hinges and the length of lever amplification, both of which play vital roles in determining quality responses. The quality responses of the 2-DOF FBM are assessed by measuring the displacement and first natural frequency. The experimental plan is carried out using the Taguchi $${L_{25}}$$ orthogonal array. An integrated approach of grey-Taguchi- based response surface methodology and entropy measurement is then applied for the multi-objective optimization of the 2-DOF FBM. To illustrate the relation between the design variables and the output responses, mathematical regression models are developed. The entropy measurement technique is applied to calculate the weight factor corresponding to each response. Then, an analysis of variance (ANOVA) is conducted to determine the significant parameters affecting the responses. In addition, the ANOVA and experimental validations are conducted to validate the statistical adequacy and the prediction accuracy of the developed mathematical models, respectively. The results reveal that the regression models have good statistical adequacy and excellent prediction accuracy. The confirmation results of the grey relational grade fall within 95 % of the confidence interval. It is strongly believed that the proposed approach has great potential for the optimal design of related flexure-based mechanisms.

Abstract: This paper presents a case study on comparison of Design of Experiments (DOE) via traditional and Taguchi methods in terms of efficiency. First, a three-level, four-parameter, full factorial DOE was conducted for finding the effects of machining parameters on the surface roughness (arithmetic average) of parts produced by turning operation. The results were analyzed applying average response, Taguchi’s S/N ratio, and Pareto ANOVA. Subsequently, the same data was analyzed applying Taguchi’s L9 orthogonal array. The comparison of two results revealed that despite an 88.9% savings of experimental runs with the Taguchi method, both methods produced similar results.

Abstract: The effects of various deep drawing process parameters were determined by experimental study with the use of Taguchi fractional factorial design and analysis of variance for AA6111 Aluminum alloy. The optimum process parameters were determined based on their influence on the thickness variation at different regions of the blank material. Three important process parameters i.e., punch nose radius, die shoulder radius and blankholder force were investigated in this study. Plan of experiments based on Taguchi’s technique were used for acquiring the data. An orthogonal array, the signal to noise ratio and the analysis of variance were employed to investigate the deep drawability characteristics. Influence on thickness due to variation of these parameters was individually evaluated in terms of percentage. The results showed that the blankholder force (56.98%) was the most significant parameter followed by punch nose radius (30.12%) and the least influence (12.90%) was with die profile radius. Keywords : Axisymmetric deep drawing, Taguchi method, orthogonal array, S/N ratio, anova

Abstract: Design space exploration (DSE) has become a notoriously difficult problem due to the exponentially increasing size of design space of microprocessors and time-consuming simulations. To address this issue, machine learning techniques have been widely employed to build predictive models. However, most previous approaches randomly sample the training set leading to considerable simulation cost and low prediction accuracy. In this paper, we propose an efficient and precise DSE methodology by combining statistical sampling and Adaboost learning technique. The proposed method includes three phases. (1) Firstly, orthogonal design based feature selection is employed to prune design space. (2) Sencondly, an orthogonal array based training data sampling method is introduced to select the representative configurations for simulation. (3) Finally, a new active learning approach ActBoost is proposed to build predictive model. Evaluations demonstrate that the proposed framework is more efficient and precise than state-of-art DSE techniques.

Abstract: Laser brazing (LB) provides a promising way to join the galvanized steels in automotive industry. The process parameters of LB have significant effects on the bead profile and hence the quality of joint. Since the relationships between the process parameters and bead profiles cannot be expressed explicitly, it is impractical to determine the optimal process parameters intuitively. This paper proposes an optimization methodology by combining Kriging surrogate and particle swarm optimization (PSO) to address the process parameters optimization of the bead profiles in LB with crimping butt of 0.8-mm-thick galvanized steel. Firstly, an experiment using Taguchi L 25 orthogonal array is conducted where welding speed (WS), wire speed rate (WF), and gap (GAP) are taken into consideration as the input parameters, while the bead profiles are the output responses. Secondly, the relationships between the inputs and outputs are established using the Kriging model. Thirdly, the effects of the input parameters on the bead profiles are analyzed, and the global process parameters are obtained by the presented Kriging-PSO approach. At last, the verification experiments were conducted to verify the effectiveness of the optimal values. On the whole, the proposed hybrid method, Kriging-PSO, shows great promise for improving the effectiveness and stability of LB welding process.

Abstract: Ball-burnishing process has been commonly used to improve the quality of finished surfaces. However, the treatments of small-sized (submillimeter) surfaces using this technique are rarely considered. In this research, a load-cell-embedded ball-burnishing tool, clamping a 0.5-mm-diameter ball, has been newly developed and manufactured to function on a machining center. Oxygen-free copper (OFC) specimens were used as the tested samples for the tool. The effects of several process parameters can be investigated by conducting the experiments designed using the Taguchi’s orthogonal array. The experimental works were divided into two rounds. The first round experiments are used to determine the significance of factors and the levels of insignificant factors. The second round experiments are carried out to determine the levels of the significant factors. The optimal burnishing condition for plane surface then was applied to burnish the cylindrical convex-plano lens model.

Abstract: Multi-objective optimization method is used to simultaneously maximize and minimize the various criteria involved in complex industrial problems. In the present work, the optimum combination of cutting parameters is estimated in the turning of EN25 steel with coated carbide tools by performing desirability function analysis and utility concept. The experiments were designed as per L18 Taguchi mixed level orthogonal array with each trial performed under different conditions. These methods are employed for minimization of cutting force, surface roughness and maximization of material removal rate. The optimized results are compared and utility concept gave good combination of input and output parameters. Finally, Analysis of Variance (ANOVA) on overall desirability and utility value was employed to identify the relative significance of factors in terms of their percentage contribution to the responses.

Abstract: In the fabrication industry, metal inert gas (MIG) welding is a very important process and Fe410WA is the most commonly used material for the manufacturing of fabricated structures. During the preparation of butt welded joints, angular distortion is a major concern. Angular distortion can be minimized by optimizing the input parameters. In this paper, a study of the optimization of controllable input parameters such as current, voltage and gas flow rate by using the Taguchi method is performed. Butt welding samples were prepared by using three levels and three factors. An orthogonal array of nine trials is considered for the design of the experiment. After measuring the distortion angle, observed readings were verified by using analysis of variance (ANOVA) technique and it was found that the p-values were less than 0.05. Theoretical calculations were performed to optimize the process parameters to achieve the minimum distortion angle. A confirmation test was taken for validation purposes and to confirm th...

Abstract: This paper explains the effect of turning parameters such as cutting speed, feed rate, depth of cut and cutting tool nose radius on surface roughness of hybrid metal matrix (Al-SiCp-Fly ash) composite. Experiments have been conducted based on the orthogonal array L16(4)5 and surface roughness was tested on the composites turned by an high speed CNC centre lathe. Analysis of variance (ANOVA) was performed to predict the significant parameters and their contribution towards surface finish of the composite. A mathematical model was developed using non-linear regression analysis. Taguchi method and Genetic algorithm have been employed to optimize the turning parameters for optimum surface roughness of the composite. The optimum turning parametric conditions have been checked with the confirmation experiments. It has been noted that the optimum condition of genetic algorithm exhibited better results than the experimental results based on the orthogonal array and the optimum condition of Taguchi method.

Abstract: The optimization technique of machining parameters considering multiple performance characteristics of non conventional machining EDM process using Taguchi method combined with grey relational analysis (GRA) is presented in this study. ST 42 steel was chosen as material work piece and graphite as electrode during this experiment. Performance characteristics such as material removal rate and overcut are selected to evaluated the effect of machining parameters. Current, pulse on time, pulse off time and discharging time/ Z down were selected as machining parameters. The experiments was conducted by varying that machining parameters in three different levels. Based on the Taguchi quality design concept, a L27 orthogonal array table was chosen for the experiments. By using the combination of GRA and Taguchi, the optimization of complicated multiple performance characteristics was transformed into the optimization of a single response performance index. Optimal levels of machining parameters were identified by...

Abstract: Face milling is an important and common machining operation because of its versatility and capability to produce various surfaces. Face milling is a machining process of removing material by the relative motion between a work piece and rotating cutter with multiple cutting edges. It is an interrupted cutting operation in which the teeth of the milling cutter enter and exit the work piece during each revolution. This paper is concerned with the experimental and numerical study of face milling of AISI1045. The proposed approach is based on statistical analysis on the experimental data gathered using Taguchi design matrix. Surface roughness is the most important performance characteristics of the face milling process. In this study the effect of input face milling process parameters on surface roughness of AISI1045 steel milled parts have been studied. The input parameters are cutting speed (v), feed rate (f z ) and depth of cut (a p ). The experimental data are gathered using Taguchi L9 design matrix. In order to establish the relations between the input and the output parameters, various regression functions have been fitted on the data based on output characteristics. The significance of the process parameters on the quality characteristics of the process was also evaluated quantitatively using the analysis of variance method. Then, statistical analysis and validation experiments have been carried out to compare and select the best and most fitted models. In the last section of this research, mathematical model has been developed for surface roughness prediction using particle swarm optimization (PSO) on the basis of experimental results. The model developed for optimization has been validated by confirmation experiments. It has been found that the predicted roughness using PSO is in good agreement with the actual surface roughness.

Abstract: Fuzzy logic Taguchi method (FLTM) is used to optimize parameters for wire bonding process. The proposed FLTM integrates orthogonal arrays, signal-to-noise ratios, response tables, analysis of variance (ANOVA), fuzzy logic, and multiple performance characteristics index. The main process parameters for wire bonding are ultrasonication time, ultrasonication power, bond force, bond force time, and search force. The output responses include ball shear and ball size. The orthogonal arrays, signal-to-noise ratios, and response tables reduce the number of experiments needed to find the best factor-level combinations. The significant control factors are determined by ANOVA. In engineering practice, ball size increases as ball shear increases, but an excessively large ball size causes a short circuit, whereas an excessively small ball size cannot provide enough ball shear. Due to the two contradictory output responses, the FLTM is used to find the best process parameters. The experimental results show that the process parameters obtained by the FLTM result in a smaller ball size and a larger ball shear compared with those obtained by statistical methods, artificial intelligence techniques, and previous designs.

Abstract: This article aims to develop a method that optimize the multi-performance characteristics, that is, micro-hardness and surface roughness of powder mixed electric discharge machining process. For experimentation, four input parameters—(a) pulse-on time, (b) pulse-off time, (c) current and (d) powder—are considered to investigate the improvement in multi-performance characteristics using Taguchi’s L27 orthogonal array design. Furthermore, to optimize these parameters and to handle the element of uncertainty associated with multi-input and discrete data, a method combining the grey and Taguchi experimental design was established. Theoretical prediction of results obtained from grey relational grade approach shows that the proposed approach proved useful for optimizing surface roughness and micro-hardness. In addition, analysis of variance is used to find the percentage contribution of process parameters. Finally, from analytical and experimental results, it is concluded that the pulse-on, powder and current ...

Abstract: This paper aims to develop the multi response optimization technique for predict and select the optimal setting of machining parameters while machining AISI 4340 steel using utility concept. The experimental studies in machining were carried out under varying conditions of process parameters, such as cutting speed (v), feed (f) and different cooling conditions (i.e. dry, wet and cryogenic in which liquid nitrogen used as a coolant) by using uncoated tungsten carbide insert tool. Experiments were carried out as per Taguchi’s L9 orthogonal array with the utility concept and multi response optimization were performed for minimization of specific cutting force (K S ) and surface roughness (R a ). Further statistical analysis of variation (ANOVA) and analysis of mean (ANOM) were used to determine the effect of process parameters on responses K S and R a based on their P value and F value at 95 % confidence level. The optimization results proved that, cutting speed 57 m/min, feed 0.248 mm/min and cryogenic cooling is required for minimizes K S and R a .