Taguchi Orthogonal Experiment Research Articles

Discrete element simulation study on the screening effect of composite vibrating screen for coal particles

ABSTRACT To strengthen the layering effect of coal particles on the screen surface and improve the screening efficiency, a composite vibrating screen was proposed based on the void filling effect of mixed particles under vibration and the Lissajous vibration synthesis theory, and the theoretical basis and working principle of the composite vibrating screen were described. The Taguchi orthogonal experiment was designed with the composite, linear, elliptical, and circular vibrating screens as the object, and frequency, amplitude, and vibration direction angle as the variables, wherein the discrete element simulation of the traditional vibrating screen and the composite vibrating screen was conducted, and the comparison results showed that the composite vibrating screen was of great advantage in both screening efficiency and material processing. On the basis of the traditional vibrating screen, the composite vibrating screen further imposed on the particles an exciting force along the width of the screen surface, so that the particles were subject to the effect of exciting force in the xyz three directions; as a result, more diversified force to the particles, more loose mixed particle system, greater activity degree and better layering effect were realized, and then the composite vibrating screen can achieve a more ideal screening effect.

Construction of Six Sigma-based control chart for interval-valued data

Construction of control charts is straightforward if the data are real-valued. However, there are situations where data are essentially interval-valued in which each observation is represented by minimum and maximum values. While there are only few attempts to develop control charts for interval-valued data, there have been no simple-to-use approaches developed to deal with such type of data. In this article, we propose to make use of the popular Taguchi orthogonal array experiment to first redefine the data for experimental setup and then use Six Sigma control limits to determine overall control limits for interval-valued data. The resulting multiple control limits have inner and outer control limits for simultaneously monitoring minimum and maximum values of the averages of interval-valued data. The proposed control chart is then illustrated using a data set, and conclusions are drawn based on the results. It is observed that the proposed Six Sigma-based control chart for interval-valued data is, in fact, easy-to-use, and it performs better in detecting the out-of-control situations. We have established this using average run length comparisons as well with the traditional charts.

Microstructure and Mechanical Properties of Refill Friction Stir Spot-Welded Joints of 2A12Al and 7B04Al: Effects of Tool Size and Welding Parameters.

To solve problems in dissimilarly light metal joints, refilled friction stir spot welding (RFSSW) is proposed instead of resistance spot welding. However, rotation speed, dwell time, plunge depth, and the diameter of welding tools all have a great influence on joints, which brings great challenges in optimizing welding parameters to ensure their mechanical properties. In this study, the 1.5 mm thick 2A12Al and 2 mm thick 7B04Al lap joints were prepared by Taguchi orthogonal experiment design and RFSSW. The welding tool (shoulder) diameters were 5 mm and 7 mm, respectively. The macro/microstructures of the cross-section, the geometrical characteristics of the effective welding depth (EWD), the stir zone area (SZA), and the stir zone volume (SZV) were characterized. The shear strength and failure mode of the lap joint were analyzed using an optical microscope. It was found that EWD, SZA, and SZV had a good correlation with tensile-shear force. The optimal welding parameters of 5 mm diameter joints are 1500 rpm of rotation speed, 2.5 mm of plunge depth, and 0 s of dwell time, which for 7 mm joints are 1200 rpm, 1.5 mm, and 2 s. The tensile-shear force of 5 mm and 7 mm joints welded with these optical parameters was 4965 N and 5920 N, respectively. At the same time, the 5 mm diameter joints had better strength and strength stability.

Coordination of protective relays in distribution systems considering uncertainty caused by renewables and demands based on orthogonal experiments

The operations of distribution systems are more challenging than in past decades because of the penetration of distributed generation (DG). Several serious problems may be caused by DG, such as bi-directional power flow in a distribution line, different levels of fault currents and uncertainty in power generation. This paper investigates the coordination of inverse-time overcurrent relays (OCRs) in distribution systems with uncertain distributed power generation and loads. A novel method is presented in this work, considering different scenarios along with two levels of uncertainty caused by DGs (photovoltaics and wind) and bus loads, to determine fault currents using Taguchi orthogonal experiments. Nonlinear optimization is then employed to find the optimal settings of inverse-time OCRs in distribution systems and to identify infeasible current transformer ratios. Simulation results obtained from a 9-bus system and a modified IEEE 33-bus system show that the proposed method outperforms the traditional point-estimation method (PEM). For the 33-bus system, the mean values of similarity indices based on the probability density function are obtained by the proposed method, and they are 0.979 and 0.975, which are closer to unity, for time multiplier setting (TMS) and pick-up setting (PS), respectively, than those (0.953 and 0.951 for TMS and PS, respectively) obtained by the PEM. The mean values of error indices based on the cumulative distribution function are obtained by the proposed method, and they are only 0.0007 and 0.0085 for TMS and PS, respectively, while those obtained by the PEM are 0.0011 and 0.0110 for TMS and PS, respectively.

Triazine Herbicides Risk Management Strategies on Environmental and Human Health Aspects Using In-Silico Methods

As an effective herbicide, 1, 3, 5-Triazine herbicides (S-THs) are used widely in the pesticide market. However, due to their chemical properties, S-THs severely threaten the environment and human health (e.g., human lung cytotoxicity). In this study, molecular docking, Analytic Hierarchy Process-Technique for Order Preference by Similarity to the Ideal Solution (AHP-TOPSIS), and a three-dimensional quantitative structure-active relationship (3D-QSAR) model were used to design S-TH substitutes with high herbicidal functionality, high microbial degradability, and low human lung cytotoxicity. We discovered a substitute, Derivative-5, with excellent overall performance. Furthermore, Taguchi orthogonal experiments, full factorial design of experiments, and the molecular dynamics method were used to identify three chemicals (namely, the coexistence of aspartic acid, alanine, and glycine) that could promote the degradation of S-THs in maize cropping fields. Finally, density functional theory (DFT), Estimation Programs Interface (EPI), pharmacokinetic, and toxicokinetic methods were used to further verify the high microbial degradability, favorable aquatic environment, and human health friendliness of Derivative 5. This study provided a new direction for further optimizations of novel pesticide chemicals.

Multi-criteria optimization of TIG welding process parameters on AISI 409M stainless steel by Grey Taguchi method

AISI 409M ferritic stainless steel materials were examined in this study. TIG welding was utilized for the creation of butt welded joints in the construction of the L9 Taguchi orthogonal array experiment. A visual and X-ray examination of the joints followed the procedure. After the butt-joining, a slew of experiments were run to figure out the material’s specific properties. There has been an evaluation of the weld quality in terms of the specimens’ ultimate tensile strength (UTS) and percentage elongation (PE). Grey-Taguchi methodology was used to interpret, discuss and analyse the collected data. It appears that the investigation has led to some conclusive results.

Modeling and Prediction of Water-Jet-Guided Laser Cutting Depth for Inconel 718 Material Using Response Surface Methodology

In this study, the water-jet-guided laser (WJGL) method was used to cut Inconel 718 alloy with high temperature resistance. The effect of critical parameters of the water-jet-guided laser machining method on the cutting depth was studied by a Taguchi orthogonal experiment. Furthermore, the mathematical prediction model of cutting depth was established by the response surface method (RSM). The validation experiments showed that the mathematical model had a high predictive ability for cutting depth. The optimal cutting depth was obtained by model prediction, and the error was 5.5% compared with the experimental results. Compared with the traditional dry laser cutting, the water conducting laser method reduced the thermal damage and improved the cutting quality. This study provides a reference for the precision machining of Inconel 718 with a water-jet-guided laser.

Aquatic toxicity of tire microplastics on marine and freshwater organisms: An in silico approach

Tire wear particles are a notable source of tire microplastics (TMPs) in the environment. However, only a few reports have focused on the aquatic toxicity effects of composite TMPs and their additives and the mechanistic analysis at the microscopic level. Therefore, this paper study the toxic effects of tire microplastics and their additives on zebrafish based on theoretical chemical calculation method (Taguchi orthogonal experiment method, full factorial experimental design, molecular docking, and molecular dynamics computational technique). We designed five kinds of proportioning schemes of tire rubber polymers and additive components (64 groups in each). The compound toxicity effects of the tire rubber polymers and their additives on zebrafish were simulated and calculated. The simulation results indicated styrene butadiene rubber had the most significant toxic effect on zebrafish. Subsequently, taking the composition ratio scheme of styrene butadiene rubber with the lowest biotoxicity effect as an example, we analyzed the main effects, second-order interactions, and third-order interactions of styrene butadiene rubber polymer and its additive combination in terms of biotoxicity using the fixed effects model. The toxic effects (developmental toxicity, neurotoxicity, and reproductive toxicity) of styrene butadiene rubber on marine and freshwater organisms could be drastically alleviated by adjusting the ratio of rubber additives. The analysis of the interaction between amino acid residues and non-bonds during the docking process of styrene butadiene rubber and toxic receptors revealed the interaction mechanisms between the styrene butadiene rubber polymer and its additives and between the additive molecules. Hydrophobic interaction was found to be the key factor for the binding of styrene butadiene rubber additives to nonpolar amino acids in the receptor proteins. Our findings are expected to provide theoretical support for identifying and regulating the toxicity characteristics of rubber TMPs and to aid in proposing a strategy to alleviate the toxic effects on aquatic organisms.

Geometric optimization and performance analysis of radial MR valve using Taguchi orthogonal experiment method

Geometric optimization and performance analysis of radial MR valve using Taguchi orthogonal experiment method

Optimization of High-speed Dry Milling Process Parameters Based on Improved ELM and Genetic Algorithm

High-speed dry grinding has the characteristics of high processing efficiency and clean environment. The high-speed dry grinding method meets the requirements of the green and efficient development of the national manufacturing industry. However, inappropriate cutting parameters seriously affect the surface quality of the workpiece and cause the workpiece to be scrapped. Therefore, this paper proposed an optimization method based on the combination of the improved extreme learning machine neural network (ELM) for high-speed dry milling surface roughness prediction model and genetic algorithm (GA). The Taguchi orthogonal experiment results show that the surface roughness of high-speed dry milling can be accurately predicted by the improved ELM and thereafter the optimal cutting parameter combination can be determined by GA.

The Sintering Process and Vibration Characteristics for Leadless Package Structure of Pressure Sensors

A key factor restricting the development of high-temperature pressure sensors is the packaging structure. The traditional lead package with silicone oil as the medium is difficult to meet the performance requirements in high-temperature environments. In this article, the anodic bonding method is used to bond the SOI pressure-sensitive chip and the borosilicate glass to form a vacuum chamber, which avoids the use of silicone oil. The glass hole is filled with high-temperature nanosilver paste, and the glass paste is printed on the surface. After being butted with the pins of the Kovar base, the sensor is sintered under a vacuum to realize the package of the sensor. Taking the shear strength of joint and porosity of silver paste as evaluation indexes, the optimal process parameters of silver paste and glass paste integrated sintering are studied by the Taguchi orthogonal experiment. Finite element simulation was used to analyze the vibration characteristics of the sensor, and its short-term vibration reliability was verified through vibration tests. The static output of the sensor shows that this packaging process can make it maintain good nonlinearity at high and low temperatures.

Hot filament chemical vapor deposition temperature field optimization for diamond films deposited on silicon nitride substrates

The influence of some key parameters of hot filament chemical vapor deposition (HFCVD) on the temperature distribution during the deposition of diamond coatings on silicon nitride (Si3N4) substrates was assessed with the help of the finite element method. Solid heat transfer, fluid heat transfer and surface radiation heat transfer mechanisms were used to calculate the substrate temperature in the steady state during the deposition process. The accuracy of the model was verified by comparing the simulation model with experimental measurements. The comparison shows that the deviation between the model and the actual substrate temperature measurements is within 3%. Furthermore, a Taguchi orthogonal experiment was designed (3 factors, 3 levels, L9). By changing the number of hot filaments, the distance between the filaments and the substrate, and the separation between two adjacent hot filaments, the influence trend of these parameters on the substrate temperature was assessed, leading to an optimal hot filament arrangement. A deposition experiment was carried out using the optimized parameters, and the results showed that the substrate surface temperature obtained by numerical simulation is highly consistent with the temperature measured by the infrared thermometer. The optimized deposition parameters contributed to a more suitable temperature range and more uniform temperature distribution on the Si3N4 ceramic substrate. The deposited diamond film exhibited uniform crystal quality and grain morphology, thus verifying the validity of the simulation results.

The influences of gas diffusion layer material models and parameters on mechanical analysis of proton exchange membrane fuel cell

AbstractThe deformation of gas diffusion layer (GDL) under compacting pressure has a close relationship with transport properties, and electrical and thermal conductivity of proton exchange membrane fuel cell (PEMFC). In this paper, two kinds of GDL material models with different material parameters are studied with the finite element method (FEM). Taguchi orthogonal experiments and analysis of variance (ANOVA) are performed to determine their effects on mechanical analysis of GDL deformation in PEMFC. Finally, the effects of material parameters on GDL diffusion and electrical performance are discussed. The results reveal that elastic modulus (E) is the only factor affecting the maximum displacement for GDL with isotropic model when the Poisson's ratio (ν) is in the range of 0–0.1. For orthotropic model, the through‐plane elastic modulus (Ez) has a great impact on both the deformation and contact pressure. In‐plane elastic modulus (Ex) and through‐plane shear modulus (Gxz) have significant influences on contact pressure. Ez has a great impact on diffusion and electrical performance of GDL, while the effects of Ex, Gxz and ν are negligible. In addition, orthotropic GDL material model and the parameters utilized are effective in analyzing the deformation of GDL.

Molecular Modifications and Control of Processes to Facilitate the Synergistic Degradation of Polybrominated Diphenyl Ethers in Soil by Plants and Microorganisms Based on Queuing Scoring Method.

In this paper, a combination of modification of the source and regulation of the process was used to control the degradation of PBDEs by plants and microorganisms. First, the key proteins that can degrade PBDEs in plants and microorganisms were searched in the PDB (Protein Data Bank), and a molecular docking method was used to characterize the binding ability of PBDEs to two key proteins. Next, the synergistic binding ability of PBDEs to the two key proteins was evaluated based on the queuing integral method. Based on this, three groups of three-dimensional quantitative structure-activity relationship (3D-QSAR) models of plant-microbial synergistic degradation were constructed. A total of 30 PBDE derivatives were designed using BDE-3 as the template molecule. Among them, the effect on the synergistic degradation of six PBDE derivatives, including BDE-3-4, was significantly improved (increased by more than 20%) and the environment-friendly and functional evaluation parameters were improved. Subsequently, studies on the synergistic degradation of PBDEs and their derivatives by plants and microorganisms, based on the molecular docking method, found that the addition of lipophilic groups by modification is beneficial to enhance the efficiency of synergistic degradation of PBDEs by plants and microorganisms. Further, while docking PBDEs, the number of amino acids was increased and the binding bond length was decreased compared to the template molecules, i.e., PBDE derivatives could be naturally degraded more efficiently. Finally, molecular dynamics simulation by the Taguchi orthogonal experiment and a full factorial experimental design were used to simulate the effects of various regulatory schemes on the synergistic degradation of PBDEs by plants and microorganisms. It was found that optimal regulation occurred when the appropriate amount of carbon dioxide was supplied to the plant and microbial systems. This paper aims to provide theoretical support for enhancing the synergistic degradation of PBDEs by plants and microorganisms in e-waste dismantling sites and their surrounding polluted areas, as well as, realize the research and development of green alternatives to PBDE flame retardants.

Optimization of explosion puffing drying for browning control in Muskmelon (Cucumis melo L.) using Taguchi orthogonal arrays

The present study aimed at optimizing explosion puffing drying (EPD) method for browning control in muskmelon (Cucumis melo L.) using Taguchi design approach. Results of the pre-study of the EPD process showed that the following steps including color fixation, pre-drying temperature, and drying temperature/time of puffed samples, have the most effects on browning. According to the Taguchi orthogonal experiments design, 0.6% sodium chloride, 0.15% calcium chloride, 0.10% l-cysteine and 0.6% citric acid for color fixative solution, 65 °C for pre-drying and 70 °C during 150 min for drying of puffed samples considered as the optimized condition (OP) to minimize browning during the EPD process. Results of related indexes to browning indicated that OP condition can significantly protect protein, reducing sugars, and phenolic compounds degradation; maintain the pH stability; prevent polyphenol oxidases and peroxidase enzymes activities, control of 5-HMF formation and control of changes in color related parameters (L*, a*, b and ΔE∗). This work provides promising results for developing effective drying of muskmelon using EPD.

Effect of Process Parameters on Repeatability Precision of Weight for Microinjection Molding Products

The repeatability precision of weight for injection molded products is important technical parameter to measure the quality and accuracy of injection molded products and evaluate the performance of injection molding machine. The influence of mold temperature, melt temperature, packing pressure, and packing time on the weight of microinjection molding products was studied by Taguchi orthogonal experiment. The influence of peak cavity pressure on the weight of products also was analysed. The experimental results show that the packing pressure is the most important process parameter affecting both the weight of the tensile and the impact specimens. With the increase of the packing pressure, the weight of the tensile and the impact specimens increases. When the peak cavity pressure reaches a certain value, the pressure value of the tensile specimen is 65 MPa, and the pressure value of the impact specimen is 68 MPa, the weight of the product increases quickly. The packing pressure increased from 85 MPa to 100 MPa, the weight of the tensile specimen increased from 0.544g to 0.559g, an increase of 2.7%, and the weight of the impact specimen increased from 0.418g to 0.425g, an increase of 1.7%.

Multi-objective machining parameter optimisation of aluminium alloy 6063 by the Taguchi-artificial neural network/genetic algorithm approach

This study investigates the turning of aluminium alloy 6063 to optimise the material removal rate (MRR) and surface roughness (Ra) simultaneously. L27 Taguchi's orthogonal experiments were conducted by incorporating machining parameters of speed (260, 470, 840 rev/min), feed (0.2, 0.3, 0.4 mm/rev) and depth of cut (0.5, 1.0, 1.5). Analysis of variance (ANOVA) and signal-to-noise ratio were applied to determine the optimal control settings and validated by confirmatory tests. The performance characteristics were modelled by second-order regression, artificial neural network (ANN) and genetic algorithm (GA). The results indicate that the optimal conditions for MRR (375 mm3/min) and Ra (1.298 μm) were in agreement with the confirmatory tests. Regression models showed that the optimal points for MRR and Ra can be enhanced by the effect of interactions, but the ANN predicted the experimental data with better accuracy. The GA further elicited a set of optimal solutions for improving machining performance.

Multi-objective machining parameter optimisation of aluminium alloy 6063 by the Taguchi-artificial neural network/genetic algorithm approach

This study investigates the turning of aluminium alloy 6063 to optimise the material removal rate (MRR) and surface roughness (Ra) simultaneously. L27 Taguchi's orthogonal experiments were conducted by incorporating machining parameters of speed (260, 470, 840 rev/min), feed (0.2, 0.3, 0.4 mm/rev) and depth of cut (0.5, 1.0, 1.5). Analysis of variance (ANOVA) and signal-to-noise ratio were applied to determine the optimal control settings and validated by confirmatory tests. The performance characteristics were modelled by second-order regression, artificial neural network (ANN) and genetic algorithm (GA). The results indicate that the optimal conditions for MRR (375 mm3/min) and Ra (1.298 μm) were in agreement with the confirmatory tests. Regression models showed that the optimal points for MRR and Ra can be enhanced by the effect of interactions, but the ANN predicted the experimental data with better accuracy. The GA further elicited a set of optimal solutions for improving machining performance.

Selection of optimal parameters in V-bending of Ti-Grade 2 sheet to minimize springback

Springback is a geometrical defect that occurs due to the removal of the bending force acting on the component the end of the forming process. In the present study, springback behavior of Ti-Grade 2 sheets is studied by finite element method and experimentation. The process parameters considered are punch radius, die opening and sheet thickness. Based on Taguchi (L9) Orthogonal array, the simulation and experiments were conducted. Simulated springback values were found to be in good agreement with experimental values. Signal-to-noise (S/N) ratio is used to determine the optimal combination of parameters that minimizes springback. Analysis of variance is employed to study the influence of process parameter on springback.

Energy-Efficient Enhancement for Viscoelastic Injection Rheomolding Using Hierarchy Orthogonal Optimization

The viscoelastic injection molding involves multidisciplinary thermoplastic rheomolding parameters which is a complex mathematical problem. Particularly for rheomolding of complex parts with thin-walled structure, boss, and grooves, the increasing higher requirements on energy efficiency and rheomolding quality are put forward. Therefore, an energy-efficient enhancement method for viscoelastic injection molding using hierarchy orthogonal optimization (HOO) is proposed. Based on the thermoplastic rheomolding theory and considering the viscoelastic effects in injection molding, a set of partial differential equations (PDE) describing the physical coupling behavior of the mold-melt-injection molding machine is established. The fuzzy sliding mode control (FSMC) is used to reduce the energy consumption in the control system of the injection molding machine’s clamping force. Then, the HOO model of viscoelastic injection rheomolding is built in terms of thermoplastic rheomolding parameters and injection machine parameters. In initial hierarchy, through Taguchi orthogonal experiment and Analysis of Variance (ANOVA), the amount of gate, melt temperature, mold temperature, and packing pressure are extracted as the significant influence parameters. In periodical hierarchy, the multiobjective optimization model takes the forming time, warping deformation, and energy consumption of injection molding as the multiple objectives. The NSGA-II (Nondominated Sorting Genetic Algorithm II) optimization is employed to obtain the optimal solution through the global Pareto front. In ultimate hierarchy, three candidate schemes are compared on multiple objectives to determine the final energy-efficient enhancement scheme. A typical temperature controller part is analyzed and the energy consumption of injection molding is reduced by 41.85%. Through the physical experiment of injection process, the proposed method is further verified.