Optimal Combination Of Process Parameters Research Articles

Application of Taguchi Method for Optimization of Parameters in Turning Operation

AbstractCutting tool vibration analysis is the effective way to understand the machining characteristics of any material. In the present work, the effect of process parameters on cutting tool vibration is estimated using Taguchi method in turning of EN25 steel. Taguchi method uses Signal-to-Noise ratio (S/N) and Analysis of Variance (ANOVA) to determine the optimum level of process parameters and significant parameters. The results showed that cutting speed of 215 m/min, feed rate of 0.07 mm/rev and depth of cut of 0.5 mm are the optimum combination of process parameters. Cutting speed and depth of cut are the influencing parameters on cutting tool vibration. The results are experimentally verified and the results based on turning process response can be effectively improved.

A split-optimization approach for obtaining multiple solutions in single-objective process parameter optimization.

It can be observed from the experimental data of different processes that different process parameter combinations can lead to the same performance indicators, but during the optimization of process parameters, using current techniques, only one of these combinations can be found when a given objective function is specified. The combination of process parameters obtained after optimization may not always be applicable in actual production or may lead to undesired experimental conditions. In this paper, a split-optimization approach is proposed for obtaining multiple solutions in a single-objective process parameter optimization problem. This is accomplished by splitting the original search space into smaller sub-search spaces and using GA in each sub-search space to optimize the process parameters. Two different methods, i.e., cluster centers and hill and valley splitting strategy, were used to split the original search space, and their efficiency was measured against a method in which the original search space is split into equal smaller sub-search spaces. The proposed approach was used to obtain multiple optimal process parameter combinations for electrochemical micro-machining. The result obtained from the case study showed that the cluster centers and hill and valley splitting strategies were more efficient in splitting the original search space than the method in which the original search space is divided into smaller equal sub-search spaces.

Mechanical property parametric appraisal of fused deposition modeling parts based on the gray Taguchi method

The mechanical properties of a fused deposition modeling (FDM) process product are greatly influenced by many process parameters. The identified parameters namely deposition orientation, layer thickness and deposition style, raster width, and raster gap are more significant factors contributing to the strength of a FDM product. In this paper, tensile strength, flexural strength, and impact strength are considered as three evaluation indexes to characterize the mechanical properties of a FDM part. An experimental research approach based on the Taguchi method was presented and some special specimens were designed. The influences of the five parameters on the three evaluation indexes were analyzed by the use of analysis of variance (ANOVA). Finally, based on the gray relational analysis, a set of optimal process parameter combination was obtained to optimize comprehensive mechanical properties of FDM parts.

Optimization of Mechanical Properties of Green Coconut Fiber / HDPE Composites

Natural fibers have become alternative to researcher as an alternative reinforcement for fiber reinforced polymer (FRP) composites. The main objective of this investigation is to evaluate the optimum combination of process parameters to maximize the mechanical characteristics viz., Tensile strength, Flexural strength and Impact strength respectively using Taguchi method and utility concept. In fact the traditional Taguchi method cannot solve a multi-objective optimization problem; to overcome this limitation utility concept has been coupled with Taguchi method. Test specimens are prepared by injection molding technique as per L9 orthogonal array in Taguchi’s Design of experiments, the process parameters considered are percentage fiber weight fraction (% wtf) and fiber length (Fl). The individual performance characteristic of the composite material has been transformed to corresponding utility values. Individual utility values have been aggregated to compute the overall utility, which serves as representative objective function for optimization using Taguchi method. Based on the Taghuchi’s Signal-to-Noise ratio (S/N), analysis has been made on the overall utility degree and optimal process parameters has been selected finally which corresponding to highest S/N ratio. Optimal results have been verified through confirmatory test.

Multi-objective optimization in WEDM process of nanostructured hardfacing materials through hybrid techniques

Abstract Hardfacing is one of the most efficient and cost-effective ways to scale down operating expense leading to improved performance and reliability of the equipment. Presence of nano-particles in hard facing metal matrix dramatically enhanced surface area to volume ratio resulting in magnificent improvement in conductivity, hardness, heat and wear resistant properties. This paper presents an application of nanostructured hardfacing material for the development of turning tool insert through welding and machining by WEDM process. In order to simultaneously optimize performance characteristics (MRR, machining time and surface roughness), a novel hybrid approach combining grey relational analysis with principal component analysis has been proposed to identify the optimal combination of process parameters in WEDM for machining nanostructured hardfacing materials. The grey relational analysis manifests discharge pulse time a most important parameter for both brass and zinc coated brass wires. Further, mathematical models are developed using response surface methodology to investigate the effects of the WEDM parameters on grey relational grade. As subsequent comparison made in terms of performance characteristics amongst brass and zinc coated brass wire, it is observed that zinc coated brass wire is highly worthy of being chosen especially for machining of nanostructured hardfacing material.

Study on reducing sink mark depth of a microcellular injection molded part with many reinforcing ribs

As a novel injection molding process, microcellular injection molding process has the characteristics of saving material, decreasing warpage and surface sink mark, improving dimensional accuracy, etc. But for the plastic part with thick reinforcing ribs, if selection of process parameters are not reasonable, foaming quality of melt will be affected and obvious sink mark defects will appear on the surface of plastic part. This paper selected a medical appliance shell with many reinforcing ribs as research object. Simulation experiments of microcellular injection molding process were performed by using orthogonal experiment method. The influence of different process parameters, such as mold cavity surface temperature, melt temperature, injection rate, cooling time, weight reduction ratio and supercritical fluid level, on the surface sink mark of microcellular injection molding part was studied by using signal-to-noise ratio analysis and analysis of variance . The results showed that mold cavity surface temperature was the most important influence factor on surface sink mark depth of microcellular injection molding part, followed by weight reduction ratio, cooling time, supercritical fluid level, injection rate and melt temperature. Meanwhile, the optimal combination of process parameters was obtained for minimizing sink mark depth of microcellular injection molding part. The average surface sink mark depth of microcellular injection molding part molded by using the optimized process parameters was only 2.62 µm, compared to 4.87 µm of average surface sink mark depth of microcellular injection molding part molded by using the process parameters before optimization, the average sink mark depth of microcellular injection molding part was reduced by 46.2%. Finally, the forming mechanism of sink mark of microcellular injection molding part at locations of reinforcing ribs was discussed, and the influence mechanism of different process parameters on surface sink mark defects of microcellular injection molding part was also analyzed.

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.

Fabrication of PCD micro cutting tool and experimental investigation on machining of copper grating

This paper presents an investigation on machining of copper grating. Ultra-hard polycrystalline diamond (PCD) micro cutting tools were designed and machined, especially focused on fabricating micro channel arrays characterized by excellent quality with high efficiency. Micro cutting experiments of copper grating were carried out using the self-developed PCD micro tools, and the effect of width of cut, feed per tooth, and spindle speed on dimensional accuracy and burr formation was investigated. Additionally, optimum combination of processing parameters was obtained. As a result, a complete copper grating with superior dimensional accuracy and minimum top burrs was machined by employing the self-developed micro cutting tools under the optimal parameters.

SU‐F‐J‐185: Detection of Low Contrast Objects: Optimization of CT Simulation Reconstruction Protocol Parameters

Purpose:CT simulation has become an integral component of modern RT planning and therefore must be continually optimized. We evaluated the detection of small and low‐contrast regions in images obtained during CT simulation.Methods:A CT phantom containing a contrast detail modulus for detection of low‐contrast structures was used to optimize the CT reconstruction protocol for abdomen. The parameters (A) Pitch, (B) Reconstruction Filter, and (C) Rotation Time type were varied for assessment of image quality.Three factors, three levels, and nine experiments were identified. According to the Taguchi approach an L9 orthogonal array was selected. The reconstruction parameters of the CT scanner (Brilliance Big Bore), Pitch, Reconstruction Filter type, and Rotation Time, were iteratively scanned according to the orthogonal array. A Catphan 604 CT phantom was used to characterize low‐contrast resolution (CPT730 module). All CT scan images were analyzed by IMAGE‐OWL software. The objective of the study was to identify parameters that maximize the low‐contrast resolution of the images. The ANOVA and F‐tests were used to analyze results using JMP statistical software.Results:The optimal settings and predicted optimal values for low‐contrast resolution were determined. The ANOVA was used to determine the optimum combination of process parameters more accurately by investigating the relative importance of each process parameter. We determined that Pitch (61.4%) had the most significant influence on low contrast resolution, followed by the Reconstruction Filter type (29.7%). The optimal setting level is A1‐B1‐C3, 0.68 pitch, smooth filter, and gantry rotation time 1.5sec., respectively. Additional measurements were made to confirm the prediction error model is justified and the results are validated.Conclusion:These experiments have several implications for CT imaging, especially for clinical detection of small, low‐contrast lesions in liver or pancreas. In the phantom model of this study, optimal Contrast Detail Values were determined to be: 1% contrast, 2mm; 0.5% contrast, 4mm; 0.3% contrast, 7mm.

Effect and Optimization of EDM Process Parameters on Surface Roughness for En41 Steel

Unconventional machining is gaining more and more importance in today’s manufacturing methods because of its applications over conventional machining. Machining of Complex shapes, high dimensional accuracy and good surface finish can be achieved by unconventional machining processes. Surface Finish is an important quality characteristic for machined parts. In the present work, an investigation has been done to find the effect of EDM process parameters on Surface Roughness in machining of medium carbon steel EN41. For the experimentation, Pulse on time (PON) and Pulse off time (POFF), wire tension (WT) and wire speed or wire feed (WF) are selected as input parameters and Surface Roughness (Ra) is considered as a response. The experiments were performed on CNC- EDM machine as per Taguchi’s standard L27 (3level*4factors) Orthogonal array. Taguchi’s single objective optimization method is used to find the optimal combination of process parameters affecting the Surface Roughness. From the results, the optimal combination of process parameters is found at PON (level 2, value 123 μs), POFF (level 2, value 58 μs), WT (level 1, value 2 Kg-f) and WF (level 1, value 4 m/min). From Analysis of variance (ANOVA) results, Wire Feed rate has high influence (F = 61.94, P = 0.000) in effecting the Surface Roughness and Pulse ON time has the least influence (F = 1.99, P = 0.166) among all the process parameters. A Mathematical model was developed for Surface Roughness by using MINITAB-16 software. The model is a good fit and it can be used for the prediction of Surface Roughness as it has low variance (S = 0.608144) and high Coefficient of determination value (R-Sq = 82.4%). The model values are compared with experimental values and they found very close to each other.

Multiresponse Optimization of Laser Cladding Steel + VC Using Grey Relational Analysis in the Taguchi Method

Laser cladding of metal matrix composite coatings (MMCs) has become an effective and economic method to improve the wear resistance of mechanical components. The clad quality characteristics such as clad height, carbide fraction, carbide dissolution, and matrix hardness in MMCs determine the wear resistance of the coatings. These clad quality characteristics are influenced greatly by the laser cladding processing parameters. In this study, American Iron and Steel Institute (AISI) 420 + 20% vanadium carbide (VC) was deposited on mild steel with a high powder direct diode laser. The Taguchi-based Grey relational method was used to optimize the laser cladding processing parameters (laser power, scanning speed, and powder feed rate) with the consideration of multiple clad characteristics related to wear resistance (clad height, carbide volume fraction, and Fe-matrix hardness). A Taguchi L9 orthogonal array was designed to study the effects of processing parameters on each response. The contribution and significance of each processing parameter on each clad characteristic were investigated by the analysis of variance (ANOVA). The Grey relational grade acquired from Grey relational analysis was used as the performance characteristic to obtain the optimal combination of processing parameters. Based on the optimal processing parameters, the phases and microstructure of the laser-cladded coating were characterized by using x-ray diffraction (XRD) and scanning electron microscopy (SEM) with energy-dispersive spectroscopy (EDS).

Multi objective optimization of clinching joints quality using Grey-based Taguchi method

Clinching joint quality and functionality may have undesirable features because of the choice of the forming process parameters. In fact, there are different factors controlling the mechanical connection strength such as the tools’ geometry and the joint final shape. This paper presents the implementation of the Taguchi-based Grey optimization of the mechanical clinching with fixed dies for dissimilar materials (Aluminum alloy 7075 and Mild Steel) to derive the optimal process parameters combination that leads to a high strength connection subjected to multiple characteristics, namely, the bottom thickness, the interlock length, and the neck thickness of the joint. LS-DYNA explicit and implicit finite element (FE) software was used to simulate the process in order to evaluate the joint strength by loading the sheets vertically. Taguchi’s L27 orthogonal array design and the notion of signal-to-noise (S/N) ratio were utilized to obtain the objective function. Analysis of variance (ANOVA) showed the importance of factors on overall output. The output of the study provided the optimal geometrical parameters of the punch, die, and blank holder. Indeed, the die groove height, die diameter, punch diameter, punch corner radius, and clearance between punch and blank holder were found to be the most influential parameters on the bottom and neck thicknesses. In addition, the output indicated that when bottom thickness or neck thickness increased, the interlock decreased.

Process Parameter Optimization for Wobbling Laser Spot Welding of Ti6Al4V Alloy

Laser beam welding (LBW) coupled with “wobble effect” (fast oscillation of the laser beam) is very promising for high precision micro-joining industry. For this process, similarly to the conventional LBW, the laser welding process parameters play a very significant role in determining the quality of a weld joint. Consequently, four process parameters (laser power, wobble frequency, number of rotations within a single laser pulse and focused position) and 5 responses (penetration, width, heat affected zone (HAZ), area of the fusion zone, area of HAZ and hardness) were investigated for spot welding of Ti6Al4V alloy (grade 5) using a design of experiments (DoE) approach.This paper presents experimental results showing the effects of variating the considered most important process parameters on the spot weld quality of Ti6Al4V alloy. Semi-empirical mathematical models were developed to correlate laser welding parameters to each of the measured weld responses. Adequacies of the models were then examined by various methods such as ANOVA. These models not only allows a better understanding of the wobble laser welding process and predict the process performance but also determines optimal process parameters. Therefore, optimal combination of process parameters was determined considering certain quality criteria set.

Optimization of TiO2 Based Henna Dye Sensitized Solar Cell using Grey-Taguchi Technique

Low efficiency is a major drawback associated with Dye Sensitized Solar Cells (DSSCs). However, the efficiency can be enhanced by multi-objective optimization based on process parameters. In this work, four process variables have been identified as important parameters for influencing DSSC responses (efficiency, shunt and series resistance). These are thickness of the working electrode (A), annealing temperature (B), annealing time (C) and dye loading time (D). An optimal combination of the response parameters of the resulting DSSC was obtained by simultaneously adjusting these input parameters. With three different levels for each process variable, FTO glasses as components and henna leave extract as sensitizer, 9 unique DSSCs were fabricated following Taguchi Design of experiment. Each cell was illuminated with constant light intensity of 100 mW/cm 2 to measure the photovoltaic parameters. The optimal combination of process parameters was determined by applying Grey Relational Analysis (GRA). The experimental best condition (A 3 B 1 C 3 D 2 ) obtained from Taguchi array corresponded to average thickness of 9.67 µm for TiO 2 film , annealing temperature of 300 °C, annealing time of 6 hours and dye loading time of 4 hours. With optimization, the annealing time is reduced by ~67% with other responses remain the same. The global best DSSC has higher efficiency, higher shunt resistance and lower series resistance of 0.66 %, 24844.44 Ω and 8.4281 Ω, respectively. This translates to 1.3% higher efficiency, 12.4% higher shunt resistance and 10.8% lower series resistance. These results indicate that solar cell responses can be optimized significantly.

Multi-response optimisation of surface texturing using artificial bee colony algorithm

Determination of the optimal combination of process parameters plays a pivotal role in reducing manufacturing costs while enhancing rate of productivity and standard of quality of the product. This paper deals with fabrication of arrayed structures consisting of cylindrical pillars using reverse electro discharge machining (R-EDM) process, followed by optimisation of the process using artificial bee colony (ABC) algorithm. The influence of various machining parameters such as peak current (Ip), pulse-on time (Ton) and flushing pressure (Fp) on multiple performance measures in R-EDM like material removal rate (MRR), surface roughness (SR), taper and cylindricity error (CE) has been investigated using response surface methodology (RSM) based approach. In the course of this paper, the optimal parameters have been found to be Ip = 10 A; Ton = 179.091 µs; Fp = 0.2 kg/cm2. The fast convergence and the high degree of closeness with the experimental data under optimal condition establishes the efficiency and robustness of the algorithm.

Analysis and Optimization of Surface Roughness in Rotary Ultrasonic Burnishing of Titanium Alloy Ti-6Al-4V

The purpose of the paper is to investigate the influence of the processing parameters on the surface roughness in rotary ultrasonic burnishing of titanium alloy Ti-6Al-4V plane. A Taguchi orthogonal array for three levels and four factors, which include burnishing depth, feed fate, spindle speed and ultrasonic frequency, are designed. The optimal combination of ultrasonic burnishing process parameters is obtained. Analysis of variance (ANOVA) is applied to determine the most significant processing parameter and to obtain the optimal combination level of processing parameters for the lowest surface roughness. The results show that burnishing depth has the most predominant effect on surface roughness, and spindle speed is the secondary one. Feed rate and ultrasonic frequency are then followed and have no distinct effect on surface roughness in rotary burnishing of Ti-6Al-4V.

Uniform design for the optimization of Al2O3 nanofilms produced by electrophoretic deposition

Surface modification by means of nanostructures is of interest to enhance boiling heat transfer in various applications including the organic Rankine cycle (ORC). With the goal of obtaining rough and dense aluminum oxide (Al2O3) nanofilms, the optimal combination of process parameters for electrophoretic deposition (EPD) based on the uniform design (UD) method is explored in this paper. The detailed procedures for the EPD process and UD method are presented. Four main influencing conditions controlling the EPD process were identified as nanofluid concentration, deposition time, applied voltage and suspension pH. A series of tests were carried out based on the UD experimental design. A regression model and statistical analysis were applied to the results. Sensitivity analyses of the effect of the four main parameters on the roughness and deposited mass of Al2O3 films were also carried out. The results showed that Al2O3 nanofilms were deposited compactly and uniformly on the substrate. Within the range of the experiments, the preferred combination of process parameters was determined to be nanofluid concentration of 2 wt.%, deposition time of 15 min, applied voltage of 23 V and suspension pH of 3, yielding roughness and deposited mass of 520.9 nm and 161.6 × 10− 4 g/cm2, respectively. A verification experiment was carried out at these conditions and gave values of roughness and deposited mass within 8% error of the expected ones as determined from the UD approach. It is concluded that uniform design is useful for the optimization of electrophoretic deposition requiring only 7 tests compared to 49 using the orthogonal design method.

Studies on Parametric Optimization for Plasma Sprayed Fly Ash - Al<sub>2</sub>O<sub>3</sub> Composite Coatings

Present investigation deals with the effect of varying process parameters on the characterization of plasma sprayed fly ash - Al2O3 composite coatings using Taguchi’s experimental design method to conduct experiments and optimization of process parameters. Parameters such as standoff distance, powder feed rate and current density were considered for the optimization of bond strength, porosity and hardness. The significance of the parameters and their optimum level is determined by using ANOVA. Experiments were carried out to validate the effect of optimum process parameters on response characteristics and found that selected optimal combination of process parameters is able to achieve the best results.

Optimization of Process Parameters in Injection Moulding of FR Lever Using GRA and DFA and Validated by Ann

This study deals with the optimization of the injection moulding process parameters in the production of the FR (Forward Reverse) Lever, using the Grey Relational Analysis (GRA) and Desirability Function Approach (DFA) and the results are validated by ANN. The FR lever is used to control the direction of the rotation of spindles in conventional machines. Parameters such as injection pressure, injection speed and injection temperature, which influence the quality of the final product of the injection moulding process, are called the input parameters. Parameters such as Shrinkage and Surface Roughness, which are considered as the quality characteristics of this product, are called the output parameters. FR levers are produced using a fabricated Injection moulding tool, according to Taguchi’s experimental design and the response data are recorded. The recorded experimental data are analyzed and the optimum process parameters combinations have been found, by using the GRA and DFA. An ANN has been developed using the experimental data and the responses (output data) are predicted for the corresponding optimal parameters combination. Finally, the obtained optimum parameter combinations are tested by both ANN and the experiment and the results are found to be satisfactory.

Effect of roller burnishing process parameters on the surface roughness and microhardness for TA2 alloy

Rolling burnishing is an effective method to improve the surface integrity of the machined part. It not only increases the hardness of the machined surface but also reduces the surface roughness. In this paper, experimental studies are performed to investigate the influence of roller burnishing parameters (i.e., spindle speed, burnishing depth, and burnishing feed) on the surface roughness and microhardness of TA2 alloy. The aim is to model the relations between some relevant process parameters and the surface performances of surface roughness and microhardness after roller burnishing, which can give an optimum combination of process parameters to produce desired surface roughness and microhardness. To achieve this goal, by utilizing response surface methodology and Box-Behnken experimental design techniques, workable empirical models are developed to predict surface roughness and microhardness. Analysis of variance is applied to investigate the relationship between process parameters and the output responses. The validation tests are performed to evaluate the effectiveness of the model and the response surface optimization techniques. The results indicate that the prediction values of surface roughness and microhardness have good agreement with the experimental ones. Among the process parameters, the spindle speed and burnishing depth are the significant parameters for reducing the surface roughness and raising the surface microhardness. Meanwhile, the experimental results also indicate that the roller burnishing process can obviously enhance the surface performances, which can lead to the reduction of surface roughness by 63 % and the increase of microhardness by 28 % compared to pre-machined surfaces.