Taguchi Method Research Articles

Statistical Assessment of Counterflow Ranque-Hilsch Vortex Tube Performance

The vortex tube, which consists of a simple tube, is a device that can simultaneously heat and cool thanks to environmentally friendly pressurized fluids (air, oxygen, nitrogen, etc.). Many studies have been included in the literature to evaluate the Ranque-Hilsch Vortex tube's performance and to reveal influential factors. Variance analysis, linear regression analysis, and the Taguchi method are primarily used in practice. This study aimed to compare the strengths and weaknesses of the factorial experimental design and Taguchi orthogonal array design in the statistical evaluation of the factors affecting the heat exchange of the Ranque-Hilsch Vortex tube. For this purpose, a detailed theory was created for the appropriate factorial ANOVA model to the data set (4 × 5 × 12 = 240 experiments) containing the Ranque-Hilsch Vortex tube and effective material type (polyamide, steel, brass, and aluminum), nozzle number (2,3,4,5 and 6), and input pressure parameters (1,5-7 bar). Following the factorial ANOVA solution, including all binary interactions, the findings were obtained according to the most suitable L16 Taguchi Orthogonal array, considering the four levels for each material, nozzle, and pressure. As a result of the ANOVA, all parameters were statistically significant on heat change (p < 0.001). On the other hand, the pressure was obtained as the only statistically significant factor according to the Taguchi analysis (F = 35.17, p = 0.008). The advantages and disadvantages of the two methods were compared regarding the test findings and graphical performances.

Experimental and statistical damage analysis in milling of S2‐glass fiber/epoxy and basalt fiber/epoxy composites

AbstractS2‐glass fiber reinforced plastics (S2‐GFRP) and basalt fiber reinforced plastics (BFRP) have emerged as crucial materials due to their exceptional mechanical properties, and milling of composite materials plays an important role in achieving desired properties. However, they have proven challenges due to relative inhomogeneity compared with metals, resulting unpredictability in quality of milling operations. The objective of this work is to investigate the effect of cutting parameters, tool geometry and tool surface materials on the surface quality of composites using burrs as a metric. S2‐GFRP and BFRP composites were produced by the vacuum infusion method. Helical and straight flute end mills were manufactured from high‐speed steel (HSS) and carbide rounds, and half of them were coated with titanium nitride using reactive magnetron sputtering technique. Taguchi L18 orthogonal array is used to determine the effect of tool material, tool angle, coating, cutting direction, spindle speed, and feed rate on the machining quality of S2‐GFRPs and BFRPs with respect to burr formations. Milling experiments were conducted under dry conditions and then the burrs were imaged to calculate the total area and length. Statistical analysis was also performed to optimize the machining parameters and tool type for ensuring the structural integrity and performance of the final composite parts. The results showed that the selection of tool material has the most significant impact on the burr area and length of the machined surface. The novel image analysis allows to analyze the extent of the burr size with a desirable operation speed for industrial applications.Highlights Aerospace grade S2‐Glass (S2‐GFRP) and basalt fiber reinforced plastics (BFRP) were manufactured. Carbide and HSS end mills were fabricated and coated with titanium nitride protective layer. FRPs were machined at various process parameters designed by Taguchi method. Distinctive image processing was firstly used to compute milling induced Burr area and length. Statistical analysis was performed to quantify the contribution of parameters and optimize milling.

Optimization of Processing Parameters and Wear Performance of B4C Reinforced AA6061 Composites Through Taguchi Methodology

Optimization of Processing Parameters and Wear Performance of B4C Reinforced AA6061 Composites Through Taguchi Methodology

Diesel Engine Performance and Emission Parameters Optimization Using Taguchi and Response Surface Methodology

In present study, the ideal engine functioning condition for pollutants as well as functionality was determined using RSM. The L16 Orthogonal Array experiment table was designed using Minitab 16 software with Taguchi's design of experiments methodology with Three variables—fuel type, engine speed, and engine load, each of which was varied across four distinct levels. After a comprehensive model examination, the R2 and modified R2 values are close, indicating a low risk of including unimportant components. The model found that an engine load of 6.85 kgf, an engine speed of 2000 rpm, and the 20% OPB blended fuel (OPB20) would optimise BTE, EE, BSFC, and NO, HC, and CO emissions. The model's maximum desirability was 86.79%, indicating that the predicted optimum answers and experimental responses were similar. The utilisation of RSM optimisation in conjunction with OPB fuel has the potential to enhance engine performance and mitigate emissions.

Reduction in Porosity in GMAW-P Welds of CP780 Galvanized Steel with ER70S-3 Electrode Using the Taguchi Methodology

Reduction in Porosity in GMAW-P Welds of CP780 Galvanized Steel with ER70S-3 Electrode Using the Taguchi Methodology

Multi-objective optimization for minimize cutting force and power consumption in corn stalk chopping processes

This study was on optimization of the cutting processes for corn stalks, which serve as significant sources of biomass and forage. The reduction of cutting force is crucial for enhancing energy efficiency. Cutting velocity rises, which can lead to significant power usage with minimal shear forces. Therefore, the objective is to minimize both the cutting force and power consumption. To address this multi-objective optimization problem, a modified Taguchi method was employed. Chauvenet's criterion was used to assess the validity of statistical scatter in repeated test data. The test samples had an 81 % moisture content. Through analysis of variance (ANOVA), the optimal chopping process parameters were identified as velocity of 4.4 m/s, approach angle of 30°, and feeding angle of 50°. The refined empirical relationships indicated that the cutting force ranges from 180.55 N to 393.37 N, while the cutting power ranges from 16.81 W to 44.05 W. In a single test, the output responses for the optimal parameter set were 26.32 W for power consumption and 242.60 N for cutting force, both are within the estimated range. The considerable scatter observed in repeated test data is likely due to variations in corn stalk thickness. These findings are valuable for the operation of chopping machines, ensuring minimal cutting force and power consumption when handling corn stalks residues.

Enhancing the functionality of sugar palm (Arenga Pinnata) fibre reinforced polylactic acid composite filament of fused deposition modelling through Taguchi method

Constructing functional components using Fused Deposition Modelling (FDM) is challenging due to various processing factors that influence the quality of the final product. The main reason for this is the many processing parameters involved, which have the ability to impact the quality of the produced components. The aim of this research is to use the Taguchi technique in attempt to improve the printing variables for attaining the best possible mechanical and physical qualities in the three-dimensional (3D) printed product made from sugar palm fibre reinforced polylactic acid (SPF/PLA). The layer thickness, infill density, and printing speed are characteristics that directly affect the mechanical qualities, surface roughness, and dimensional accuracy of FDM products. The research applied Taguchi’s L9 array, consisting of 9 experimental trials, with each trial including 5 duplicated specimens. Thus, a total of 45 specimens were generated by altering various processing settings. The most effective printing settings for FDM using SPF and PLA were found to be a layer thickness of 0.1 mm, infill density set to 100%, and a printing speed of 25 mm s−1. The microscopic images reveal a significant rise in the number of voids as the layer thickness is raised. Additionally, the printing speed has a substantial impact on the nead structure, making it more resilient. Overall, the results will provide a significant collection of data in the area of 3D printing, improving the utilization of indigenous plant fibres in additive manufacturing technology.

Rheological modelling of carbonyl-iron particles (CIP) paraffin oil-based magneto-rheological fluids

New types of magneto-rheological fluids are increasingly being developed lately, but there is a dearth of information on the performance of commonly used rheological models for emerging MRFs such as carbonyl-iron particles (CIP) paraffin-oil-based MRF. This work aims to investigate the performance of some rheological models for application in predicting shear stress and yield strength in an emerging MRF suitable for flow-mode applications. CIP, low viscosity paraffin oil, and lithium grease were used as magnetic particles, carrier fluid, and additives, respectively, to prepare the MRF. Based on different mixing proportions determined with the Taguchi method of experimental design, sixteen samples were prepared following a standard procedure. For each sample, the values of viscosity and shear stress were determined using a viscometer and rheometer, respectively, with an incorporated self-developed magnetic device. By fitting the data and using the multi-objective nonlinear programming solver in Micro-soft Excel to determine optimum parameters for each model, the Bingham Model, Herschel–Buckley Model, Casson Model, Cross models, and Power-law were used to model the experimental data. Predicted shear stress values and yield strength were then analyzed using ANOVA at a 5% confidence level. The relative errors were determined using RMSE, Mean Square Error, and Mean Absolute Error. There was a significant variation in the predicted outcomes of all the models. Overall, all the models gave relatively acceptable results. However, the Herschel-Buckley model gave the best results, while the Casson model gave the worst results, judging by their values of errors. It is shown that the Herschel-Buckley model should be best used for predicting the rheological characteristics of CIP and paraffin oil-based MRF.

Functional post-processing of extrusion-based 3D printed parts: polyaniline (PAni) as a coating for thermoplastics components

PurposeThis study aims to evaluate in situ oxidative polymerization of aniline (Ani) as a post-processing method to promote extrusion-based 3D printed parts, made from insulating polymers, to components with functional properties, including electrical conductivity and chemical sensitivity.Design/methodology/approachExtrusion-based 3D printed parts of polyethylene terephthalate modified with glycol (PETG) and polypropylene (PP) were coated in an aqueous acid solution via in situ oxidative polymerization of Ani. First, the feedstocks were characterized. Densely printed samples were then used to assess the adhesion of polyaniline (PAni) and electrical conductivity on printed parts. The best feedstock candidate for PAni coating was selected for further analysis. Last, a Taguchi methodology was used to evaluate the influence of printing parameters on the coating of porous samples. Analysis of variance and Tukey post hoc test were used to identify the best levels for each parameter.FindingsColorimetry measurements showed significant color shifts in PP samples and no shifts in PETG samples upon pullout testing. The incorporation of PAni content and electrical conductivity were, respectively, 41% and 571% higher for PETG in comparison to PP. Upon coating, the surface energy of both materials decreased. Additionally, the dynamic mechanical analysis test showed minimal influence of PAni over the dynamic mechanical properties of PETG. The parametric study indicated that only layer thickness and infill pattern had a significant influence on PAni incorporation and electrical conductivity of coated porous samples.Originality/valueCurrent literature reports difficulties in incorporating PAni without affecting dimensional precision and feedstock stability. In situ, oxidative polymerization of Ani could overcome these limitations. However, its use as a functional post-processing of extrusion-based printed parts is a novelty.

The Disperse Dyeing of Polyetherimide Fibers Using Orthogonal Array (Taguchi) Design

Polyetherimide (PEI) fibers are classified as high-performance fibers due to their notable characteristics, including chemical resistance, heat resistance, and flame resistance. However, the amorphous structure and intrinsic dyeability of polyetherimide (PEI) fibers set them apart from other high-performance fibers. The fibers possess considerable potential due to their remarkable performance features and are utilized in a wide range of industries, containing fashion and technical textiles, for varied purposes. The present work utilized the Orthogonal Array Taguchi method to systematically improve the dyeing process parameters for fabric samples made of polyetherimide (PEI). The use of a systematic methodology enabled effective experimentation and enabled the determination of the most favorable values of factors, while simultaneously reducing the utilization of resources. The study involved conducting rigorous experiments to evaluate the influence of several parameters on the color strength, tensile qualities, and washing fastness properties of the fabric samples. Furthermore, the utilization of the Taguchi approach facilitated the anticipation of these pivotal fabric properties by considering certain parameters. The objectives of this research encompass not only the progression of textile industry, but also the provision of beneficial perspectives for augmenting the caliber and efficacy of PEI fabrics in various applications.

Development, modelling and optimization of process parameters on the tensile strength of aluminum, reinforced with pumice and carbonated coal hybrid composites for brake disc application

This study focuses on optimizing double stir casting process parameters to enhance the tensile strength of hybrid composites comprising aluminum alloy, brown pumice, and coal ash, intended for brake disc applications. Analytical techniques including X-ray fluorescence, X-ray diffraction, thermogravimetric analysis, and scanning electron microscopy were employed to characterize the composite constituents. The Taguchi method was utilized for experimental design and optimization to determine the optimal weight compositions of brown pumice and coal ash, as well as stir casting parameters (stirrer speed, pouring temperature, and stirring duration). Regression analysis was employed to develop a predictive mathematical model for the tensile strength of the hybrid composites and to assess the significance of process parameters. The optimized composite achieved a predicted tensile strength of 186.81 MPa and an experimental strength of 190.67 MPa using 7.5 vol% brown pumice, 2.5 vol% coal ash, a pouring temperature of 700 °C, stirrer speed of 500 rpm, and stirring duration of 10 min. This represents a 52.23% improvement over the as-cast aluminum alloy’s tensile strength. Characterization results revealed that brown pumice and coal ash contain robust minerals (SiO2, Fe2O3, Al2O3) suitable for reinforcing metal matrices like aluminum, titanium, and magnesium. Thermogravimetric and differential thermal analyses demonstrated thermal stability up to 614.01 °C for the optimized composite, making it suitable for brake disc applications.

Optimization of geotechnical characteristics of clayey soils using fly ash and granulated blast furnace slag-based geopolymer

In this study, the effects of fly ash and granulated blast furnace slag based geopolymer on the mechanical properties of high plasticity clayey soils were investigated. For this purpose, experimental studies were carried out using the Taguchi Method. The Taguchi L16 orthogonal array was used with various amounts of class F fly ash (12 %, 16 %, 20 %, and 24 %), granulated blast furnace slag (8 %, 10 %, 12 %, and 14 %), and alkaline hydroxide solution NaOH molarity (6, 8, 10, and 12). After 7 and 28 days of curing, unconfined compressive strength (UCS) and California bearing ratio (CBR) were carried out. Permeability test was carried out as well after 28 days of curing. The effects of the variables on the experimental results were determined using S/N and variance analyses (ANOVA). The microstructure and phase composition of geopolymer samples were identified via scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS). The findings indicate that the strength of geopolymer-stabilized soil is significantly affected by the stabilizer content, fly ash–slag ratio, and molarity of alkaline activator (M). The optimal mix proportions for geopolymer-stabilized high plasticity clayey soil were found to be as follow: 38 % geopolymer content (24 % fly ash, 14 % slag) and an alkaline activator content of 25.75 % with a molarity of 12 M.This study concluded that fly ash and granulated blast furnace slag based geopolymer can serve as a feasible alternative material to cement, being sustainable and applicable. It could be utilized to enhance the strength characteristics of high-plasticity clay soil, while simultaneously, reducing permeability.

Optimisation of pervious concrete performance by varying aggregate shape, size, aggregate-to-cement ratio, and compaction effort by using the Taguchi method

ABSTRACT The porosity and compressive strength of pervious concrete are critical determinants of its suitability for various applications. Therefore, it is necessary to recognise the factors influencing the performance and its ranks to balance porosity and compressive strength ideally. This study evaluates the impact of aggregate shape, size, aggregate-to-cement ratio and compaction effort on previous concrete performance. The research involved varying aggregate sizes (5–12 mm, 12–18 mm and 18–25 mm), aggregate-to-cement ratios (3.0, 4.0 and 5.0), compaction efforts (0, 30 and 60 blows) and aggregates underwent revolutions in a ball mill (0, 200 and 1000) to change their morphological characteristics. A total of 81 mix designs were tested, resulting in 486 cubes for compressive strength and porosity testing. The acquired data underwent analysis using the statistical analysis and Taguchi method to discern the most influential factors and establish their ranking. The results indicate that revolutions, compaction, aggregate-to-cement ratio and aggregate size contribute 29.42%, 26.19%, 29.13% and 0.96%, respectively, to the compressive strength performance. Regarding porosity performance, revolutions and compaction emerge as significant factors, accounting for 39.95% and 26.91%, respectively. The influence of the aggregate-to-cement ratio and aggregate size on porosity performance appears less pronounced.

Investigating the effect of underlying angle, width, and number of spray rails on the performance of planing hull and their optimization using the Taguchi method

Investigating the effect of underlying angle, width, and number of spray rails on the performance of planing hull and their optimization using the Taguchi method

An OGSM-based multi-objective optimization model for partner selection in fresh produce supply chain considering carbon emissions

Incorporating partner selection with environmental commitment is recognized as a crucial aspect of green development in fresh produce supply chains. This paper presents a multi-objective programming (MOP) model for partner selection considering carbon emissions based on the ‘Objectives, Goals, Strategies, Measures’ (OGSM) framework. The OGSM serves as a strategic scheme to identify the long-term green development vision of a supply chain, ensuring that the activities of supply chain partners are aligned with common goals. Driven by the OGSM design, the MOP model is formulated with three conflicting objective functions to maximize profit, minimize carbon emission, and maximize the quality of fresh produce. The model helps decision-makers address decisions on partner selection with determined logistics volumes, transportation modes and packaging types under carbon emission constraints. To tackle the NP-hard problem, we develop an effective hybrid meta-heuristic algorithm called ɛ-NSGA, which complements the advantages of the ɛ-constraint method and NSGA-II (Non-dominated Sorting Genetic Algorithm-II). The experimental results based on parameter calibration of the Taguchi method and the Kruskal–Wallis test demonstrate that the proposed ɛ-NSGA outperforms other four heuristic algorithms in terms of the performance indices of GD (Generational Distance), spacing, IGD (Inverted Generational Distance), and HV (Hyper Volume). The implementation of the OGSM-MOP together with ɛ-NSGA in a real-world apple supply chain illustrates the effectiveness and practicality of the model. Finally, managerial insights into the utilization of the model are discussed and suggestions for decision-making to fulfill corporate environmental obligations are provided.

Validation of DOE Factorial/Taguchi/Surface Response Models of Mechanical Properties of Synthetic and Natural Fiber Reinforced Epoxy Matrix Hybrid Material.

A validation of the factorial, Taguchi and response surface methodology (RSM) statistical models is developed for the analysis of mechanical tests of hybrid materials, with an epoxy matrix reinforced with natural Chambira fiber and synthetic fibers of glass, carbon and Kevlar. These materials present variability in their properties, so for the validation of the models a research methodology with a quantitative approach based on the statistical process of the design of experiments (DOE) was adopted; for which the sampling is in relation to the design matrix using 90 treatments with three replicates for each of the study variables. The analysis of the models reveals that the greatest pressure is obtained by considering only the source elements that are significant; this is reflected in the increase in the coefficient of determination and in the predictive capacity. The modified factorial model is best suited for the research, since it has an R2 higher than 90% in almost all the evaluated mechanical properties of the material; with respect to the combined optimization of the variables, the model showed an overall contribution of 99.73% and global desirability of 0.7537. These results highlight the effectiveness of the modified factorial model in the analysis of hybrid materials.

Utilizing Taguchi method and Regression Analysis for Optimizing Sand Mould Flowability

Utilizing Taguchi method and Regression Analysis for Optimizing Sand Mould Flowability

Optimization of machining parameters for turning operation of heat-treated Ti-6Al-3Mo-2Nb-2Sn-2Zr-1.5Cr alloy by Taguchi method

TC21 alloy is a high-strength titanium alloy that has been gaining attention in various industries for its excellent combination of strength, toughness, and corrosion resistance. Given that this alloy is hard to cut material, therefore this study aims to optimize the process parameters of Turing this alloy under different conditions (i.e. as-received alloy, and heat-treated alloy). The L9 Taguchi approach-base orthogonal array is used to determine the optimum cutting parameters and the least number of experimental trials required. The achievement of this target, three different cutting parameters are used in the experimental work; each cutting parameter has three levels. The cutting speeds are chosen as 120, 100, and 80 m/min. The feed rates’ values are 0.15, 0.1, and 0.05, mm/rev, and the depth of cut values are 0.6, 0.4, and 0.2 mm. After applying three steps of heat treatment (First step: is heating the sample to 920 °C for 1 h then decreasing to 820 °C also for 1 h, second step: cooling the sample to room temperature by water quenching (WQ), the third step: holding the sample at 600 °C for 4 h (Aging process)). The results revealed that the triple heat treatment led to the change in the microstructure from (α + β) to (α + β) with secondary α platelets (αs) formed in residual β matrix leading to a decreased surface roughness by 56.25% and tool wear by 24.18%. The two most critical factors that affect the tool insert wear and surface roughness are the death of cut and cutting speed, which contribute 46.6% and 46.7% of the total, respectively. Feed rate, on the other hand, has the least importance, contributing 20.2% and 31.9% respectively.

Multivariable optimization based on the Taguchi method to study the cutting conditions in aluminum turning

Multivariable optimization based on the Taguchi method to study the cutting conditions in aluminum turning

Design optimization of two-blade Savonius wind turbines for hydrogen generation

This paper presents a Taguchi optimization study aimed at enhancing the efficiency of a two bladed Savonius wind turbine by optimizing inner blade parameters. An L9 orthogonal design was created, and one-way analysis of variance (ANOVA) was conducted to assess the impact of each parameter on wind turbine performance. Optimal blades configuration was determined using the Taguchi method and power curve of the wind generator was created. Furthermore, a MATLAB – Simulink model was developed to simulate a hydrogen production system based on an alkaline electrolyser fuelled with the electrical energy produced by the optimized wind turbine. Wind speeds data of Vieste, a small town located in the Gargano promontory of Puglia region, South of Italy, were chosen for yearly based simulations. The ANOVA analysis shows that the most effective parameter on the performance of the optimized turbine was determined as the inner blade angle by 91.85 % and the least important parameter was calculated as the number of inner blades, by 0.98 %. Furthermore, the potential annual hydrogen generation for different numbers of wind turbines was calculated through the MATLAB – Simulink model: 2.423 kg for a single turbine, 25.93 kg for five turbines, and 57.58 kg for ten turbines.