Showing papers on "Taguchi methods published in 2017"

Optimization of surface roughness and cutting temperature in high-pressure coolant-assisted hard turning using Taguchi method

Abstract: In this article, the effects of material hardness and high-pressure coolant jet over dry machining are evaluated in respect of surface roughness and cutting temperature using Taguchi L36 orthogonal array. The experimental data was analyzed using empirical cumulative distribution function and box plot with respect to material hardness and machining environment. Afterward, optimization of the quality responses is performed using signal-to-noise ratio. As part of Taguchi optimization, the “smaller is better” was adopted as optimization principle; the design of experiment was used for parameters orientation, and the analysis of variance was used for determining the effects of control factors. For the present experimental studies, three types of hardened steels (40 HRC, 48 HRC, and 56 HRC) were turned by coated carbide insert at industrial speed–feed combinations under both dry and high-pressure coolant jet. Depth of cut, being a less significant parameter, was kept fixed. The high-pressure coolant jet was found successful in reducing cutting temperature, surface roughness, and tool wear. The statistical analysis showed that work material hardness is the most significant factor for both cutting temperature and surface roughness. However, for surface roughness, other variables exerted somewhat similar contribution, while in determining the cutting temperature, the environment demonstrated crucial role. The confirmation tests showed 15.85 and 0.28 % error in predicting surface roughness and cutting temperature, respectively.

Optimization of MQL flow rate for minimum cutting force and surface roughness in end milling of hardened steel (HRC 40)

Abstract: The present work focuses on the performance modeling of hard milling to attain an optimum parameter setting for the minimum cutting force and surface roughness. Furthermore, it was attempted to compute the minimum quantity lubricant flow rate precisely, besides the cutting speed and table feed rate, by adopting Grey-based Taguchi method and composite desirability function. The experimental data was collected by end milling of hardened AISI 4140 steel using carbide cutter under dry and minimum quantity lubrication conditions according to Taguchi L 16 orthogonal array. The predictive model of the responses was formulated by using response surface methodology. The analysis of variance revealed that the table feed has the maximum influence on cutting force, and the flow rate of lubricant has the highest effect on surface roughness. The parameter setting at lower table feed, higher cutting speed, and 150-ml/h lubricant flow yield the minimum value of the responses. Finally, the results of confirmation test verified the adequacy and supremacy of the optimization models; however, Grey-based Taguchi method induced a better optimization.

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

Abstract: 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.

Advances in 3D Printing & Additive Manufacturing Technologies

Abstract: Influence of Process Parameters on Tensile Strength of Additive Manufactured Polymer Parts using Taguchi Method -- Determination and Comparison of the Anisotropic Strengths of Fused Deposition Modeling P400 ABS -- Estimating the Effect of Process Parameters on Build Time and Model Material Volume for FDM Process Optimization by Response Surface Methodology and Grey Relational Analysis -- Current Trends of Additive Manufacturing in the Aerospace Industry -- Influence of Oxygen Partial Pressure on Hydroxyapatite Coating of Additive Manufactured component by Pulsed Laser Deposition -- Electro Discharge Machining of Ti-alloy(Ti6Al4V) and 316LStainless Steel and Optimization of Process Parameters by Grey Relational Analysis (GRA) Method -- Multi-Objective Optimization of Mechanical Properties of Aluminium 7075 Based Hybrid Metal Matrix Composite using Genetic Algorithm -- A Review on Status of Research in Metal Additive Manufacturing -- Multi Response Optimization of Nd: YAG Laser for Micro Drilling of 304Stainless Steel using Grey Relational Analysis -- Additive Manufacturing at French Space Agency with Industry Partnership -- Wear Characterization of Direct Steel –H20 Specimens Produced by Additive Manufacturing Techniques -- Rapid Manufacturing of Customized Surgical Cutting Guide for the Accurate Resection of Malignant Tumor in the Mandible -- Implant Analysis on the Lumbar-Sacrum Vertebrae using Finite Element Method -- An Automated Acupressure Glove For Stress & Pain Relief Using 3D Printing -- Development and Optimization of Dental Crown using Rapid Prototyping Integrated with CAD.

Optimization of Binder Jetting Using Taguchi Method

Abstract: Among several additive manufacturing (AM) methods, binder-jetting has undergone a recent advancement in its ability to process metal powders through selective deposition of binders on a powder bed followed by curing, sintering, and infiltration. This study analyzes the impact of various process parameters in binder jetting on mechanical properties of sintered AM metal parts. The Taguchi optimization method has been employed to determine the optimum AM parameters to improve transverse rupture strength (TRS), specifically: binder saturation, layer thickness, roll speed, and feed-to-powder ratio. The effects of the selected process parameters on the TRS performance of sintered SS 316L samples are studied with the American Society of Testing Materials (ASTM) standard test method. It was found that binder saturation and feed-to-powder ratio were the most critical parameters, which reflects the strong influence of binder powder interaction and density of powder bed on resulting mechanical properties. This article serves as an aid in understanding the optimum process parameters for binder jetting of SS 316L.

Study of surface roughness and cutting forces using ANN, RSM, and ANOVA in turning of Ti-6Al-4V under cryogenic jets applied at flank and rake faces of coated WC tool

Abstract: This paper presents the analysis of average surface roughness, cutting force, and feed force in turning of difficult-to-machine Ti-6Al-4V alloy by experimental investigation and performance modeling. Based on knowledge of the literature, to pacify the elevated temperature in machining Ti-6Al-4V and to ensure a clean environment, the experiments are carried out in cryogenic (liquid nitrogen) condition by following the Taguchi L18 mixed-level orthogonal array. Afterward, the models of responses have been formulated by the response surface methodology (RSM) and artificial neural network (ANN). The higher values of correlation coefficient (≥96%) and lower values of error determined the adequacy of the developed models. Comparative study of both models revealed that the RSM-based model revealed greater accuracy for the testing data and hence recommended. Analysis of variance (ANOVA) determined the effects of cutting speed, feed rate, and insert configuration on the quality characteristics. The results revealed that a cutting speed not exceeding 110 m/min is likely to generate favorable machining responses. In addition, the higher feed rate was found to ensure better machining performances. Moreover, the desirability-based multi-response optimization determined that a cutting speed of 78 m/min, a feed rate of 0.16 mm/rev, and use of the SNMM tool insert are capable of minimizing surface roughness at 1.05 μm, main cutting force at 315 N, and feed force at 208 N.

Experimentation investigation of abrasive water jet machining parameters using Taguchi and Evolutionary optimization techniques

Abstract: In the last decade, numerous new materials are rapidly emerging and developed; it creates considerable interest in the researcher to search out the optimum combination of machining parameters during machining of these materials using advanced machining processes (AMP). In this work, an experimental investigation is carried out on abrasive water jet machining (AWJM) process for the machining of material AA631-T6 using the Taguchi methodology. Parameters such as transverse speed, standoff distance and mass flow rate are considered to obtain the influence of these parameters on kerf top width and taper angle . Regression models have been developed to correlate the data generated using experimental results. Seven advanced optimization techniques, i.e., particle swarm optimization, firefly algorithm, artificial bee colony, simulated annealing, black hole, biogeography based and non-dominated sorting genetic algorithm are attempted for the considered AWJM process. The effectiveness of these algorithms is compared and found that bio-geography algorithm is performing better compared to other algorithms. Furthermore, a non-dominated set of solution is obtained to have diversity in the solutions for the AWJM process. The result obtained using the Taguchi method and optimization techniques are confirmed using confirmation experiments. Confirmatory experiments show that both the optimization techniques and Taguchi method are the effective tools in optimizing the process parameters of the AWJM process.

Optimization of laccase production from Marasmiellus palmivorus LA1 by Taguchi method of Design of experiments.

Abstract: Fungal laccase has profound applications in different fields of biotechnology due to its broad specificity and high redox potential. Any successful application of the enzyme requires large scale production. As laccase production is highly dependent on medium components and cultural conditions, optimization of the same is essential for efficient product production. Production of laccase by fungal strain Marasmiellus palmivorus LA1 under solid state fermentation was optimized by the Taguchi design of experiments (DOE) methodology. An orthogonal array (L8) was designed using Qualitek-4 software to study the interactions and relative influence of the seven selected factors by one factor at a time approach. The optimum condition formulated was temperature (28 °C), pH (5), galactose (0.8%w/v), cupric sulphate (3 mM), inoculum concentration (number of mycelial agar pieces) (6Nos.) and substrate length (0.05 m). Overall yield increase of 17.6 fold was obtained after optimization. Statistical optimization leads to the elimination of an insignificant medium component ammonium dihydrogen phosphate from the process and contributes to a 1.06 fold increase in enzyme production. A final production of 667.4 ± 13 IU/mL laccase activity paves way for the application of this strain for industrial applications. Study optimized lignin degrading laccases from Marasmiellus palmivorus LA1. This laccases can thus be used for further applications in different scales of production after analyzing the properties of the enzyme. Study also confirmed the use of taguchi method for optimizations of product production.

Mono-objective and multi-objective optimization of performance parameters in high pressure coolant assisted turning of Ti-6Al-4V

Abstract: This paper presents the optimization of cutting forces, average surface roughness, cutting temperature, and chip reduction coefficient in turning of Ti-6Al-4V alloy under dry and high pressure coolant (HPC) that is applied at the rake and flank surfaces simultaneously. The experimental design plan was conducted by the full factorial parameter orientation. The optimization has been conducted in two ways: firstly, by using signal-to-noise ratio-based Taguchi method as mono-objective optimization; secondly, by using gray relational analysis integrated with Taguchi method as multi-objective optimization. In either method, the cutting speed, feed rate, and cutting condition were considered as the inputs to the optimization. The mono-objective optimization concluded that the 156 m/min cutting speed and 0.12 mm/rev feed rate when run under HPC optimized the cutting forces and roughness, and when operated under dry optimized chip reduction coefficient, the cutting temperature was minimized at 78 m/min and 0.12 mm/rev feed rate. The multi-objective optimization concluded that Ti alloy turning system is optimized at 156 m/min cutting speed and 0.12 mm/rev feed rate under HPC.

Optimization of machining parameters during micro-milling of Ti6Al4V titanium alloy and Inconel 718 materials using Taguchi method

Abstract: This study focused on the optimization of micro-milling parameters for two extensively used aerospace materials (titanium and nickel-based superalloy). The experiments were planned using Taguchi ex...

Parameter optimization and experimental study of the sprocket repairing using laser cladding

Abstract: In order to achieve the restoration of the sprocket, it is significant to repair or modify the damaged sprocket by using an advanced surface treatment technique, such as the laser cladding process. In this paper, the Taguchi method was applied to conduct the experiment to optimize the process parameters for repairing a sprocket in the laser cladding process. The dilution was chosen to evaluate the quality of the cladding layer and the effect of the process parameters, such as the laser power, scanning speed, and powder feeding rate, with respect to the cladding layer geometry, and the dilution was investigated systematically. Then, using the optimized parameters, the sprocket was remanufactured and its surface profile characteristics, microstructure, and microhardness of the repaired sprocket were analyzed. The results show that the optimal process parameters (1000 W, 2.81 g/min, 1200 mm/min) obtained by the Taguchi method could realize the lower dilution. With the optimal parameters, the repair accuracy of the sprocket could reach 2.973 mm, which offers the machining allowance for machining of the sprocket. A white bright band observed at the interface shows that the metallurgical bonding was realized between the cladding zone and base metal. The microhardness of the cladding zone is higher than that of the heat-affected zone and base metal. Furthermore, the results reveal that the Taguchi method can effectively acquire the optimal combination of process parameters, and the laser cladding process exhibits good feasibility and effectiveness for repairing the machinery components with complex shapes.

Multi-objective Taguchi approach for optimal DG integration in distribution systems

Abstract: This study presents a new multi-objective Taguchi approach for optimal integration of distributed generations (DGs) in small and large scale distribution networks. The Taguchi method (TM) is a statistical method and employs orthogonal arrays (OAs) to estimate the output response in less number of computations. In every cycle, OA is updated according to mean response of each parameter at its respective levels in the previous cycle. A new node priority list is proposed to guide TM to select promising nodes. For multi-objective problems, a trade-off is developed between various objectives using the technique for order of preference by similarity to ideal solution that reduces Euclidean distances of various objectives from their best solutions and increases Euclidean distances from their worst solutions. A multi-objective DG integration problem is formulated to demonstrate the applicability of the proposed approach and tested on IEEE 33-bus, 118-bus and a practical 201-bus radial distribution systems. The simulation results are compared with existing multi-objective optimisation techniques used for optimal DG integration problems in the literature and found to be promising.

Multi-attribute decision-making of cryogenically cooled micro-EDM drilling process parameters using TOPSIS method

Abstract: The geometrical characteristics of the micro-holes along with the performance measures are matter of critical concern in micro-electrical discharge machining (μEDM) process. This paper presents the multi-attribute decision-making of cryogenically cooled micro-EDM (CμEDM) drilling process. Current (Ip), pulse on duration (Ton), pulse off duration (Toff), and gap voltage (Vg) were the input process parameters preferred to optimize the multiple responses of geometrical characterization including taper angle (TA), overcut (OC), circularity at the entry and exit (Cent and Cexit), and performance measures including material removal rate (MRR), tool wear rate (TWR), and average roughness (Ra). The Taguchi-based L27 orthogonal array (OA) is used to carry out the experimental runs, and technique for order of preference by similarity ideal solution (TOPSIS) approach is used for the identification of optimal parameters on AISI 304 stainless steel. The optimized result achieved from this approach suggests imp...

Optimal design of permanent magnet linear synchronous motors based on Taguchi method

Abstract: This study focuses on optimisation design of permanent magnet linear synchronous motors that are applied in laser engraving machines with no cutting force. Traditional analytical optimisation method based on magnetic field with particle swarm optimisation algorithm was introduced to obtain the best combination of motor structure parameters. By contrast, the novel optimisation design method - Taguchi method based on orthogonal array was proposed to optimise the thrust and thrust ripple. After the design of experiments using finite-element analysis, the relative importance of each design parameter was estimated in detail. Experimental results of prototype can certify the superiority and validity of Taguchi optimisation method.

Optimization of fused deposition modeling process parameters using a fuzzy inference system coupled with Taguchi philosophy

Abstract: Fused deposition modeling (FDM) is an additive manufacturing technique used to fabricate intricate parts in 3D, within the shortest possible time without using tools, dies, fixtures, or human intervention. This article empirically reports the effects of the process parameters, i.e., the layer thickness, raster angle, raster width, air gap, part orientation, and their interactions on the accuracy of the length, width, and thickness, of acrylonitrile-butadiene-styrene (ABSP 400) parts fabricated using the FDM technique. It was found that contraction prevailed along the direction of the length and width, whereas the thickness increased from the desired value of the fabricated part. Optimum parameter settings to minimize the responses, such as the change in length, width, and thickness of the test specimen, have been determined using Taguchi’s parameter design. Because Taguchi’s philosophy fails to obtain uniform optimal factor settings for each response, in this study, a fuzzy inference system combined with the Taguchi philosophy has been adopted to generate a single response from three responses, to reach the specific target values with the overall optimum factor level settings. Further, Taguchi and artificial neural network predictive models are also presented in this study for an accuracy evaluation within the dimensions of the FDM fabricated parts, subjected to various operating conditions. The predicted values obtained from both models are in good agreement with the values from the experiment data, with mean absolute percentage errors of 3.16 and 0.15, respectively. Finally, the confirmatory test results showed an improvement in the multi-response performance index of 0.454 when using the optimal FDM parameters over the initial values.

Design optimization for minimum technological parameters when dry turning of AISI D3 steel using Taguchi method

Abstract: The development in the manufacturing flied requires the continuous optimization using various methods. In order to minimize some technological output (such as surface roughness, tangential force, specific cutting force, and cutting power) characterizing material machinability, it is intended in the present paper to perform an optimizing approach of cutting parameters based on Taguchi method. Selected input cutting parameters are major cutting edge angle, cutting insert nose radius, cutting speed, feed rate, and depth of cut. The tests were performed on AISI D3 steel using mixed ceramic inserts under dry cutting conditions. A Taguchi L18 orthogonal array is used to design the optimization experiment. The analysis of variance (ANOVA) is exploited to evaluate the foremost effects on the output parameters. The results indicate that both feed rate and cutting insert nose radius are the mainly influencing factors on surface roughness while both tangential force and specific cutting force are affected principally by depth of cut followed by feed rate. The most significant parameter affecting cutting power is depth of cut followed by cutting speed and feed rate. Regression equations are formulated for estimating predicted values of technological parameters. Optimal cutting parameters are determined using the signal-to-noise (S/N) ratio which was calculated for the precited technological output according to the “the smaller-the-better” approach. Based on the confirmation experiments and laboratory results, it is concluded that the Taguchi method is successfully adapted to describe the optimization of cutting parameters (inputs) for improved technological ones (output).

An inverse model for injection molding of optical lens using artificial neural network coupled with genetic algorithm

Abstract: This study combined the artificial neural network (ANN) with a genetic algorithm (GA) to establish an inverse model of injection molding for optical lens form accuracy. The Taguchi parameter design was used for screening experiments of the injection molding parameters, and the significant factors influencing lens form accuracy were found to be mold temperature, cooling time, packing pressure, and packing time. These significant factors were used for full factorial experiments, and the experimental data then were used as training and checking data sets for the ANN prediction model. Finally, the ANN prediction model was combined with the GA to construct an inverse model of injection molding. Lens form accuracies of 0.5, 0.7, and $$1\,\upmu \hbox {m}$$1μm were taken as examples for validation, and when the error of the set lens form accuracy target value was within 2 % there were 26, 17, and six sets of the injection molding parameters, respectively, that met the desired form accuracy obtained by using the inverse model. The result indicated that the proposed strategy was successful in identifying process parameters for products with reliable accuracy. In addition, using the GA as a global search algorithm for the optimal solution could further optimize the Taguchi optimal process parameters. The validation experiments revealed that the form accuracy of the lens was improved.