Papers by Keyword: Taguchi Method

Abstract: Friction surfacing is a solid-state coating technique process in which a mechtrode is rotated against the substrate under pressure, henceforth forming a coat on the substrate. This process not only can be used as coating process but it also provides flexibility in coating different materials as a revamp manufacturing process and it is suitable for getting excellent mechanical properties after the surfaced deposits. Bond strength is very good and these deposits are expected to serve better service life. The present work deals with mechtrode of SS-316, D3-tool steel and aa-2014 are coated on low carbon steel substrate by friction surfacing process and design of experiment were done by using taguchi L9 orthogonal array where the process parameters are mechtrode, rotational speed and traverse speed. The coating thickness, coating width and the SEM-microstructure analysis were studied.

Abstract: In this Paper, the application of Taguchi Method (TM) on the process parameters of Injection Moulding of Polybutylene Terephthalate (PBT) is presented. The influence of process parameters, such as Injection Pressure, Suckback Pressure, Injection Time, Cooling Time, Zone 1 Temperature & Zone 2 Temperature (Barrel Temperatures) on Dark Spots and Short Shots (defects) were investigated using the Orthogonal Array L₁₆ of Taguchi Method for 6 factors at 2 levels each with the response being percent defectives. It was found that Injection Pressure, Injection Time & Zone 1 Temperature had a major effect on the response. After the application of Taguchi Method, the rejection rate dropped down to 5.84% from 11.33%, which is a 48.45% reduction.

Abstract: A comparative study of three different aluminium alloys, Al2618, Al4032 and Al6061 made internal combustion engine pistons is done on their responses under mechanical and thermal loads using finite element methods. In this study, a 3D solid model of piston is created in CATIA and the simulations of the static structural analysis, steady-state thermal analysis and transient thermal analysis are carried out in ANSYS. Stress and temperature distributions on critical areas of piston are pointed out for appropriate modification in piston design. The temperature and heat flux variations with time are presented in transient thermal analysis. Taguchi method and topological optimization are applied to optimize the process parameters and to select the appropriate material for the piston.

Abstract: Polypropylene is a widely used thermoplastic with high impact resistance and strong mechanical properties. Graphene has exhibited in a new generation of electronic component materials owing to its high thermal conductivity and low resistivity. In this study, a composite of graphene and polypropylene for injection molding purposes was created. In Taguchi method, an L9 orthogonal array for injection molding experiments was adopted. The process parameters included injection temperature (A), holding time (B), injection pressure (C), and graphene ratio (D). Optimal parameter combinations were determined according to resistivity, and the results were A3B2C1D3: 2956.333 MΩ by original and A1B2C1D3: 2802 MΩ Taguchi analysis, respectively, where the improvement was 5.2%.

Abstract: This study proposes an intelligent optimization system based on the Taguchi method, back-propagation neural network (BPNN), multilayer perceptron (MLP) and modified PSO-GA to find optimal process parameters in plastic injection molding (PIM). Firstly, the Taguchi method is used to determine the initial combination of parameter settings by calculating the signal-to-noise (S/N) ratios from the experimental data. Significant factors are determined using analysis of variance (ANOVA). The S/N ratio predictors (BPNN_S/N) and quality predictors (BPNN_Q) are constructed using BPNN with the experimental data. In addition, a modified PSO-GA algorithm in conjunction with MLP is used to find initial weights of BPNN and to reduce the training time of BPNN. In the first stage optimization, the S/N ratio predictors are coupled with GA to reduce the variations of the manufacturing process. In the second stage optimization, The combination of S/N ratio predictors and quality predictors with modified PSO-GA is empoyed to search for the optimal parameters. Finally, three confirmation experiments are performed to assess the effectiveness of these approaches. The experimental results show that the proposed system can create the best performance, and optimal process parameter settings which not only enhance the stability in the whole injection molding process but also effectively improve the PIM product quality. Furthermore, experiences of the novel hybrid optimization system can be transferred into the intelligent PIM machines for the coming up internet of things (IoT) and big data environment.

Abstract: Generally, the welding parameters directly affect the weld forming and the joint performance. Because many parameters are involved in the automatic arc welding process, it is not realistic to use traditional experimental methods, such as full factorial design. Therefore, it is important to find out the good experimental design method to determine the welding parameters for optimal joint quality with a minimal number of experiments. Therefore, this study is aimed at investigating the effect of DOE (Design of Experiment) methods on bead width of mild steel parts welded by the automatic GMA (Gas Metal Arc) welding process. In this work, Taguchi method was used for studying the effect of the welding parameters on optimization of bead width, while Box-Behnken method was utilized to develop a mathematical model relating the bead width to welding parameters such as welding voltage, arc current, welding speed and CTWD (Contact Tip to Work Distance). The S/N (Signal-to-Noise) ratio and the ANOVA (Analysis of Variance) were employed to find the optimal bead width. Confirmation tests were carried out to validate the effectiveness of the Taguchi method. The experimental results show that welding current mainly affected the bead width. The predicted bead width of 3.12mm was in good agreement with the confirmation tests. With the regression coefficient analysis in the Box-Behnken design, a relationship between bead width and four significant welding parameters was obtained. A second-order model has also been established between the welding parameters and the bead width as welding quality. The developed model is adequate to navigate the design space.

Abstract: Tensile properties are among the measures that give rubber products value. In this study, the effect of ingredient loading and temperature on the tensile properties of surfactant-loaded natural rubber vulcanizates (NRV) are investigated. Rubber dogbone samples are compounded using an L12 orthogonal array of Taguchi design of experiment, where ingredients are treated as factors varied at low and high loadings. Rubber specimens for each formulation are thermally aged for 20 days in ovens with temperatures of 40, 50, and 60 °C. Results show that zinc oxide (ZnO), paraffin wax, sulfur, mercaptobenzothiazole (MBT), and diphenylguanidine (DPG) significantly have the highest effect on increasing the elastic modulus while decreasing the tensile strength, tensile strain, and tensile set. Used oil has the highest effect on decreasing the elastic modulus but has the highest effect on increasing tensile strength, tensile strain, and tensile set. High loading of cocamide diethanolamide (coca DEA) significantly increases tensile strength at 60 °C. High loading of glycerol monostearate (GMS) significantly decreases tensile strength and strain at 40 °C. Highest elastic modulus, tensile strength, strain, and set are achieved when NRV are thermally aged at 50 °C.

Abstract: Porosity, hardness, and adhesion mainly affect the performance of thermal spray coating and significantly depend on spray parameters. Therefore, determining value of the spray parameters and their effects on the coating properties are always taken into consideration. This paper studies optimization as well as evaluates influences of HVOF spray parameters which include powder feed rate (M), rotational speed of the details per minute (N) and step movement of the nozzle per revolution (S) to the adhesion, porosity, micro-hardness of Cr₃C₂ - 20(80Ni20Cr) coating on 40Cr steel shaft substrate. Taguchi experimental design L9 combined with analysis of variance (ANOVA) was used to determine optimum spray parameters and percentage of effect of each spray parameter on properties of the coating. From obtained results, the optimal spray parameters are m = 35 g.min^-1, n = 130 rpm, S = 6 mm for the highest hardness coating of 658.2 HV; with m = 45g.min^-1, n = 130rpm, S = 3 mm for the smallest porosity of 1.27%; with m = 35g.min^-1, n = 130 rpm, S = 3 mm for the coating with a maximum adhesion of 44.07 MPa. The percent effects of the parameters m, n, S to adhesion, porosity and hardness were (2.8%, 33.6%, 63.6%), (0.1%, 1.3%, 98.6%), (32.7%, 43.3%, 24%), respectively. The percent effects of spray parameters on corresponding coating property allows adjustment of spray parameters to obtain the desired coating. Verified experiment results shows that the results are reliable. Taguchi method and ANOVA can find optimal parameters of the HVOF spray to acquire high-performance coating.

Abstract: Laser deposition is an advanced manufacturing technology capable of enhancing service life of engineering components by hard-facing their functional surfaces. There are quite a number of parameters involved in the process and also desirable output characteristics. These output characteristics are often independently optimised and which may lead to poor outcome for other characteristics, hence the need for multi-objective optimisation of all the output characteristics. In this study, a laser deposition of Ti-6Al-4V wire and tungsten carbide powder was made on a Ti-6Al-4V substrate with a view to achieve a metallurgical bonded metal matrix composite on the substrate. Single clads were deposited with a desire to optimise the composite clad characteristics (height, width and reinforcement fraction) for the purpose of surface coating. Processing parameters (laser power, traverse speed, wire feed rate, powder feed rate) were varied, the experiment was planned using Taguchi method and output characteristics were analysed using principal component analysis approach. The results indicated that the parameters required for optimised clad height, width, and reinforcement fraction necessary for surface coating is laser power of 1800 W, traverse speed of 200 mm/min, wire feed rate 700 mm/min and powder feed rate of 30 g/min. The powder feed rate was found to most significantly contribute 43.99%, followed by traverse speed 39.77%, laser power 15.87% with wire feed rate having the least contribution towards the multi-objective optimisation. Confirmation results showed that clad width and reinforcement fraction were significantly improved by the optimised parameters. The multi-objective optimisation procedure is a useful tool necessary to identify the process factors required to enhance output characteristics in laser processing.

Abstract: Metal Inert Gas (MIG) welding process is a common welding process for carbon steels. During the cooling after welding, non-uniform cooling cause tensile residual stress on the surface of welded joint and, in most cases, in Heat Affected Zone (HAZ) also. The tensile residual stress is undesirable because it affects the strength and shorten the workpiece fatigue life. In order to convert the tensile residual stresses to desirable compressive residual stresses, the mechanical surface treatment like deep rolling process was used in this research. The surface residual stresses were measured by XRD machine with the sin2ψ method. For statistical analysis of significant factors used in deep rolling process, there are three factors each factor has two levels: rolling pressure, rolling speed and number of passes. Taguchi experimental design was used in conjunction with a deep rolling process to determine factors affected the surface residual stresses and surface microhardness. The results of the research showed that the most significant factors that affect the surface residual stress and surface microhardness were the number of passes, followed by the rolling pressure and the rolling speed, respectively. The maximum compressive residual stress measured at the welded joint was -521.5 MPa. The highest measured surface microhardness was 266.2 HV at the welded joint. The appropriated factors of deep rolling process for JIS SS400 MIG welding were rolling pressure 270 MPa, rolling speed 1,500 mm/min and number of passes 3 times.