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In this research, the effects of feed speed, ballbar radius, and pitch as control factors on the measurement outcomes of the helical path ballbar test were investigated in a robotic machining setup. The goal was to provide guidance on selecting setup parameters for the helical path ballbar test in machining operations, aiming to enhance the precision of helical path compensation and the accuracy of dynamic error extraction. The Taguchi method, using an L27 array, was employed to evaluate the effects of each control factor at three levels. Circular deviation (CD) before and after helical path compensation was measured as the response variable, and the signal-to-noise ratio was calculated. The results indicated that ballbar radius and feed speed significantly influence the CD after helical compensation. Additionally, a regression model was developed based on setup parameters and CD from circular ballbar tests, demonstrating predictive accuracy with an error margin below 6.44%. This prediction model can guide the selection of machining parameters for helical milling, specifically for dynamic error extraction. Overall, these findings offer valuable insights into optimizing helical path ballbar test setups for improved accuracy in both helical path compensation and dynamic error extraction in machining processes. [ABSTRACT FROM AUTHOR]

Wire electrical discharge machining (WEDM) is utilized to cut sophisticated curves or shapes that would be challenging to cut using traditional techniques. The challenge lies in simultaneously optimizing multiple conflicting objectives, such as maximizing material removal rate (MRR) while minimizing surface roughness (SR) and kerf width, to achieve high-quality machining results. This study addresses this challenge by introducing a multi-objective optimization approach using the Taguchi method and the Design of Experiments (DOE) to optimize WEDM parameters. The WEDM model AQ327L cut a workpiece material from stainless steel AISI 304 using a 0.25-mm brass wire electrode diameter. The variable input parameters were a pulse on time (Ton), a pulse of time (Toff), and a peak current (IP). The average of means analysis (ANOM), analysis of variance (ANOVA), and single-to-noise (S/N) ratio were used to determine the effect of WEDM parameters on the responses. The multi-objectives optimization introduced the ideal setting parameters were a combination of 11.33 μs Ton, 24 μs Toff, and 11 A IP. ANOVA and ANOM demonstrated that the Ton followed by IP are the most influential factors in the MRR and kerf width. In contrast, the Ton followed by the Toff are the most influential factors in SR. Finally, the findings demonstrated that the multi-objective optimization by the Taguchi approach could increase the quality of the WEDM process of AISI 304. [ABSTRACT FROM AUTHOR]

Solar collector systems efficiently transform sunlight into energy that may be used to meet various needs. This research aimed to use the Taguchi method to determine the ideal operating parameters for a solar thermal collector with a rectangular spiral absorber. Controllable parameters including mass flow rate, solar radiation, and absorber design were manipulated during the energy recovery process, and features like PV temperature and outlet water temperature were used to assess the system's effectiveness. The findings indicate that certain criteria significantly affect response indicators. The observed percentage contribution of absorber design, solar radiation, and the mass flow rate was 69.19%, 27.99%, and 2.83% in PV surface temperature. In comparison, the individual percentage contributions were 73.63%, 13.51%, and 10.57% for absorber design, solar radiation and mass flow rate for water output temperatures. The present model's R2 values for PV and outlet water temperatures are 97.24% and 99.67%, respectively. The Predictive regression model was found in fine harmony and the maximum percentage error is limited to 0.68%. The maximum analytical electrical efficiency was observed with a spiral rectangular absorber of 14.57% at the lowest mass flow rate of 0.04 kg/s at the lowest radiation level of 600 W/m2. In comparison, maximum analytical thermal efficiency was observed with a spiral rectangular thermal absorber of 63.56% at the highest flow rate of 0.06 kg/s and the highest solar radiation level of 1000 W/m2. The analytical and experiment findings were in better agreement in this study, with the highest relative error of 7.52%. According to the study's findings, the rectangular absorber-based PVT system is at its best at a higher mass flow rate to lower PV temperature and boost thermal energy recovery via water. The present research work can be extended for exergy, environmental, and economic feasibility analysis. [ABSTRACT FROM AUTHOR]

This study investigates the effect of four major process variables viz. laser power, scanning speed, hatch distance and powder bed thickness on the densification behavior of Inconel 718 (IN718), with a view to obtain defect free builds during laser powder bed fusion (L-PBF) process. In order to determine the causes of defect generation, samples with different process variables were printed and examined microstructurally. Samples printed as per Taguchi's L9 orthogonal array have exhibited different types of microscopic defects such as porosity, lack of fusion (LOF) and cracks. Based on detailed study, the optimized process parameters for obtaining defect free IN718 builds were found to be with a laser power of 320 W at a scanning speed of 850 mm/s and a hatch distance of 0.11 mm. LOF and un-melted tracks have formed at low volume energy density (VED) while porosity was found at high VED values. Cracks are most evident in XZ plane, and the formation of such cracks is high at high laser power and scanning speed. Although VED represents the energy input to the process, it should no longer be considered a process parameter, as multiple combinations of input process variables with different performance characteristics can result in the same value. This aspect has been demonstrated in this paper with experimental data. A Modified Taguchi's approach has been followed in this study to develop empirical relationships to the performance characteristics (density), in terms of process variables and demonstrated their validity through comparison of test data. The method suggests few tests as per the orthogonal array and provides complete information for all combinations of levels and process variables. This method also provides the estimated range of output responses so that the scatter in the repeated tests can be assessed prior to the tests. [ABSTRACT FROM AUTHOR]

In this paper, parameters that effectively contribute to glass surface degradation from sandblasting erosion processes are investigated and optimized on the basis of the method of Taguchi. The polystyrene glass used in this work has been eroded taking into account the projected sand mass, the particles' grain size and the velocity as the main influencing parameters by looking at specimens' surface roughness (SR) and optical transmission (OT). Taguchi's Design L9 orthogonal array of experiments has been implemented in order to obtaining the best combination among these parameters. The significant parameters affecting the responses have been determined on the basis of variance analysis. These have revealed that the particles' size and velocity are the most effective parameters on the responses OT and SR of the degraded surface with 92 and 56% contribution, respectively. These optimized influential parameters' combinations have revealed severe eroding processes occurring to the polystyrene glass surface as confirmed by the optical micrographs. [ABSTRACT FROM AUTHOR]

Newly, Pebax polymer (pure and composite polyether block amide) has been extensively applied for CO2 elimination from air contaminants. The Pebax involves of polyamide (PA) and stretchy polyether (PEO) portions, which can suggest excellent solubility as well as bulk-free fractional volume for CO2 permeation. In the present work, the polymeric nanocomposite membranes (Pebax/PEG/NCS) were synthesized by adding different amount of nanochitosan particles (NCS) and polyethylene glycol (PEG) to the Pebax with applying Taguchi's experimental design with Minitab software as well as using thermal phase separation method. The input variables to the software included 4 factors at 4 levels, namely wt% of PEG, wt% of NCS, temperature (°C), and pressure (bar) in the ranges of (0, 20, 30, 40), (0, 10, 20, 30), (30, 35, 40, 45), and (4, 6, 8, 10), respectively. The Taguchi method yielded 16 optimal test arrays, each with different conditions. The morphology and structure of NCS and synthesized membranes, Pebax/PEG/NCS, were studied using infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and field emission scanning electron microscopy (FE-SEM) tests. Their thermal properties were analyzed using thermal gravity analysis (TGA) and differential scanning calorimetry (DSC) tests. The effect of NCS amount, polymer concentration, temperature, and pressure on the performance of the Pebax/PEG/NCS was then studied. Lastly, the permeability of the constructed membranes was measured using the constant pressure-variable volume method. The first result of the present work indicated that the permeability of CO2 was higher than N2 gas due to its non-polarity and determinability. The second result obtained is that the increase of NCS increases the permeability and selectivity of N2 and CO2 gases. The third result showed that in the gas permeation test in Pebax/PEG/NCS, the maximum permeability of CO2 was from the B15 test with a value of 281.111 barrer, and the maximum permeability for N2 gas from the B14 has a permeability of 17.477 barrer at a temperature of 35 °C and a pressure of 10 bar. The obtained results are in good agreement with the literature. [ABSTRACT FROM AUTHOR]

Selective laser melting (SLM) is crucial for fabricating complex geometries, such as the tibial component of an artificial knee joint. However, its inherent high-temperature gradients often induce thermal defects and deformations, compromising product accuracy. This study addressed these challenges by using a multifaceted approach in which finite element method (FEM) simulations, Taguchi method analysis, and deep neural network (DNN) prediction were combined. Initially, a transient thermal model was developed using the FEM to analyze the thermal behavior of a tibial component during and after SLM; the model was then validated through experiments. Subsequently, the Taguchi method was employed to evaluate the thermal influence of various SLM parameters on deformation and stress. Furthermore, a K-means-based exploration method was developed and used to identify critical thermal areas affecting a component's size and quality. Finally, a DNN model was developed for rapid prediction of thermal deformation by leveraging an FEM proxy modeling methodology to facilitate efficient monitoring in a digital-twin framework. The FEM analysis revealed average deformation errors of 3.26% during SLM and 0.05 mm after SLM. The optimal SLM parameters for minimizing thermal deformation and stress for a tibial component were identified. The DNN model, trained on the proxy database, achieved error margins of only 5.47% and 4.62% in comparison with the FEM and experimental results, respectively, but took substantially less computation time than did the FEM. This study integrated FEM simulations, the Taguchi method, and DNN prediction to enhance the accuracy of SLM manufacturing of tibial components. [ABSTRACT FROM AUTHOR]

The proposed paper uses Taguchi design of experiments and topology optimization to design a low throat angle and lightweight structure of an open gap (C-frame) stamping press. First, finite element analysis was used for discussing the effects of frame structure deformation by various parameters, such as upper round corner (R1), eccentric distance of upper round corner (L1), throat depth (K), lower round corner of throat (R2), and eccentric distance of lower round corner of throat (L2). With throat angle as the quality objective, we conducted single-objective optimization using Taguchi's smaller-the-better formula. The optimal values of the quality objectives were as follows: R1 was 60 mm, L1 was 30 mm, L2 was 340 mm, and R2 was 48 mm, the resulting throat angle of which was 0°1′18.99″. The throat angle resulting from this parameter combination in the static analysis with 44% force area was 0°1′18.50″. The weight of the frame was approximately 5971 kg. We also confirmed the influence of the four process parameters on the quality objectives and their mathematical relationships using analysis of variance (ANOVA) and multiple regression analysis. Next, LSM (level set method) topology optimization was used to create an optimized structure. The analysis of the optimized structure using LSM showed that the deformation with 100% force area increased by 2.6%. However, the throat angle decreased by 0°0′0.78″, and the mass of the machine dropped by 444 kg. The proposed paper shows the process of using a combination of optimization methodologies to create an optimal structure, and the results show that the proposed methodology can improve not only throat angle but also structure weight. [ABSTRACT FROM AUTHOR]

In this work, optimization of louver fin geometries is performed to obtain better thermal hydraulic performance of multilouvered microchannel heat exchanger by CFD method. Five louver fin geometries are considered in this work namely fin pitch, fin height, louver pitch, louver angle and louver length. The air side performance is analyzed with the help of airside heat transfer coefficient and pressure drop. These parameters are determined using Colburn-j factor and f factor for Reynolds numbers range of 100–600. In this work, two factors are studied for the effect of individual and combined louver fin geometries. It is observed from the literature study that increase in Reynold number, increases the Colburn-j factor and hence increases the rate of heat transfer favorably. At the same time, increase in Reynold number, increase f factor in term increase the pressure drop which is not desirable. Hence, it is challenging to increase the heat transfer without increase the pressure drop characteristics for heat exchanger design. So, aim of this work is to maximize the heat transfer and minimize the pressure drop. To account for these two contradicting objectives, dimensionless number (JF factor) is considered to determine the thermal hydraulic performance for the heat exchanger and it accounts both Colburn-j factor and f factor simultaneously. Orthogonal array-based Taguchi analysis is performed to obtain optimized louver fin geometries. Taguchi-CFD analysis revealed that fin pitch is the most influencing parameter, that alone accounts for 94.33% of contribution ratio on JF factor. Taguchi-confirmation test showed that the enhancement of JF factor for optimal louver fin is 5.97% higher than that of the initial design parameter. Finally, CFD analysis is performed to compare the performance of optimal louver fin geometry with that of the default louver fin geometry. From this analysis, Colburn-j and JF factor of optimum fin geometry are found to be 24.42% and 18.23% higher than those of default fin geometry. Regression models are developed for optimum fin geometry to predict the Colburn-j, f and JF factor for the Reynolds numbers range of 100–850, whose adj. R2 value is 99.05%. [ABSTRACT FROM AUTHOR]

Dyes are common pollutants that are found in industrial wastewater including food, pharmaceutical, and cosmetic industries. This study aimed to degrade Ponceau 4R (P4R) by the electro-Fenton (EF) process based on iron electrodes in the aqueous solutions. For the EF process, a 900 mL glass reactor containing two iron electrodes which connected to a power supply was used. The effects of five experimental variables namely applied voltage (5–20 V), electrolyte concentration (0–0.2 mol L−1 Na2SO4), initial P4R concentration (50–250 mg L−1), pH of the solution (2–6), and H2O2 content (0.033–0.100 %v/v) were investigated in four levels and optimized by Taguchi method (OA16). The residual concentrations of P4R after the EF process were spectrophotometrically determined at 505 nm in the time range of 0–90 min with time intervals of 10 min and the removal efficiencies were obtained. Based on the results, the optimum conditions were obtained as pH = 3, voltage = 20 V, H2O2 = 0.033 % v/v, C Na2SO4 = 0.1 M and the CP4R = 50 mg L−1. Under the optimum conditions, about 100% of P4R was removed during 10 min. The energy consumed in the EF process was calculated as 19.82 KWh/m3 during 10 min. The results obtained good removal efficiencies for the degradation of P4R in the real aqueous solutions introducing it as an efficient decolorization method for treatment of P4R polluted waters. [ABSTRACT FROM AUTHOR]

In this study, three-dimensional polycaprolactone (PCL)-based scaffolds with controlled pore architecture were fabricated from sol-gel-derived bioactive glass containing 2% mol Ag (BAG) via robocasting technique. This method was implemented due to its advantageous features, including its high reproducibility, versatility in shapes and sizes, and customizability. The Taguchi method was employed to determine the experimental parameters for preparing optimized printable BAG /PCL nanocomposite inks, with five groups of printable inks. The printed scaffolds were characterized by scanning electron microscopy, simultaneous thermal analysis, Fourier transforms infrared spectroscopy and X-ray diffraction. The heat-treated BAG nanopowder at 550 °C exhibited an average particle size diameter of less than 15 nm with a homogenous silver distribution without any additional phase. Based on SEM images of BAG /PCL nanocomposite scaffolds, the regularity of printed structure depends on the weight% of powder and PCL. The BAG75P30 and BAG65P50 with 65 and 75%wt of BAG powder possessed the best regular structures (microscopic rods and also the well-designed macropores, lumen about 500 μm) with higher porosity (61–64%). All the fabricated scaffolds provided acceptable cell viability according to the MTT assay. The cells cultured on BAG75P30, BAG65P40, and BAG65P50 showed the highest ALP activity compared to other groups. Also, these three groups represented significant antibacterial properties among the groups. The 3D-printed BAG /PCL nanocomposite scaffolds with macro and micropores in the structure can be a promising candidate for bone tissue engineering to promote tissue restoration due to their structure and also antibacterial properties resulting from silver in the composition. [ABSTRACT FROM AUTHOR]

TIMETAL (Ti-5553), a high strength, low density near beta titanium alloy is an upcoming material extensively used in the aerospace industry. In order to manufacture various parts from this super alloy, machining process comes to play. The present work focuses on the electro discharge machining of Ti-5553 a cryogenically treated workpiece (CW) and normal workpiece (NW). A comparative study has been carried out on the machining between normal workpiece (NW) and cryogenically treated workpiece (CW). The ease of machinability was measured in terms of three response parameters namely; material removal rate, surface roughness and surface crack density. The process control parameters involved in the experiment were open circuit voltage, peak current, flushing pressure, duty factor and pulse on time. A five factor and 4 Levels L16 orthogonal array has been used and performed the experiments on both the workpiece (normal workpiece (NW) and cryogenically treated workpiece (CW). The TOPSIS, a Multi criteria decision making technique has been used to convert the multi response to single domain. The Taguchi method has been applied and the optimal parameter setting was obtained which yielded in the highest MRR, lower SR and lower SCD. The obtained optimal parameter settings of both the workpiece have been compared and the effects of cryogenically cooling the workpiece was quite impressive. A comparative analysis has been done and found improvement of surface morphology of the workpiece after cryogenic treatment. The study has been done using the scanning electron microscope. Thus, a brief theoretical study on the effects of cryogenic cooling along with the ease of machinability in titanium alloy has been discussed in this research work. [ABSTRACT FROM AUTHOR]

Laser powder bed fusion (L-PBF) fuses metallic powder using a high-energy laser beam, forming parts layer by layer. This technique offers flexibility and design freedom in metal additive manufacturing (MAM). However, achieving the desired surface quality remains challenging and impacts functionality and reliability. L-PBF process parameters significantly influence surface roughness. Identifying the most critical factors among numerous parameters is essential for improving quality. This study examines the effects of key process parameters on the surface roughness of AlSi10Mg, a widely used aluminum alloy in high-tech industries, fabricated by L-PBF. Part orientation, laser power, scanning speed, and layer thickness were identified as crucial parameters via cause-and-effect analysis. To systematically examine their effects, the Taguchi method was employed within the framework of the design of experiment (DoE). Experimental results and statistical analysis revealed that laser power, scanning speed, and layer thickness significantly influence surface roughness parameters: arithmetic mean (Ra) and root mean square (Rq). Main effect plots and energy density analyses confirmed their impact on surface quality. Microscopic investigations identified surface flaws such as spattering, balling, and porosity contributing to poor quality. Given the complex interplay between parameters and surface quality, accurately predicting their effects is challenging. To address this, machine learning models, specifically random forest regression (RFR) and support vector regression (SVR), were used to predict the effects on surface roughness. The RFR model's R2 values for predicting Ra and Rq are 97% and 85%, while the SVR model's predictions are 85% and 66%, respectively. Evaluation metrics demonstrated that the RFR model outperformed SVR in predicting surface roughness. [ABSTRACT FROM AUTHOR]

PC/ABS blends are commonly used for the production of automotive components due to their thermal and mechanical properties. However, changes in process conditions can have a significant impact on their properties and microstructure. Therefore, determining the optimal parameters for the injection molding (IM) process is critical for effective control of the mechanical properties and quality of the injected parts. In this study, the Taguchi method is applied to investigate the relationship between the tensile stress (σ), Young's modulus (E) and IM process of PC/ABS blends. The effects of different molding parameters such as material temperature, injection pressure, holding time and mold temperature were investigated. The optimal injection parameters to achieve higher tensile stress (σ) and Young's modulus (E) were predicted by studying the signal-to-noise ratio (S/N). Thus, the objectives of the Taguchi approach for the IM process are to determine the optimal combination of process parameters and to reduce the quality variations between only a few trials. Two optimal parameter combinations were found yielding very significant mechanical properties (σ, E) of the injected parts. These optimum combinations consist of material temperature of 260 °C, injection pressure ranging between 40 and 50 bar, holding time of 8 s and mold temperature of 60 °C. Experimental results prove that injection pressure and material temperature have the most significant impact on the mechanical properties and the microstructure of PC/ABS blends. These findings may have interesting applications in the automotive industry. [ABSTRACT FROM AUTHOR]

It is intended to investigate the influence of CNT dispersion, weight fraction and infill pattern on the tensile properties of 3D printed nanocomposites. The design of experiment is performed using Taguchi's method to analyze the minimum permutations of involved parameter levels. Prior to printing the nanocomposite samples, a pilot test is done to adjust the processing parameters. Then, nanocomposites samples are printed and tensile tests are performed on both nanocomposite filaments and 3D printed specimens measuring tensile strength and modulus. As the primary output of Taguchi method, the degree to which each involved parameter will influence the tensile properties of printed specimens is identified. Then, main effect, signal-to-noise ratio and variance analyses are performed. It is revealed that CNT dispersion plays the most important role on the tensile properties. Infill pattern and CNT weight fraction have got very close impact on the strength, while the influence of CNT weight fraction on modulus becomes much more pronounced that infill pattern. Finally, a confirmation test is done on a specific specimen whose adjusted parameters are not included in Taguchi's orthogonal array. The excellent agreement between predicted and measured properties of that sample verifies the proper performance of conducted Taguchi's analysis. [ABSTRACT FROM AUTHOR]

Residual stress is responsible for various engineering failures in cases where the magnitude of residual stress exceeds the ultimate strength. With the aim of minimizing the residual stress induced in the machining of AISI 1045 steel, different machining parameters (speed, feed, depth of cut) and the output variables were experimentally investigated in this research. Series of specimens were produced using different machining parameters, and the residual stress in each was measured. When a material is subjected to external forces or thermal treatments, residual stresses can be introduced due to changes in the lattice spacing of the material. These changes in lattice spacing are detected using a non-destructive method based on the x-ray diffraction (XRD) technique. The equipment used is iXRD with MGR40P- Stress measurement system, PROTO CANADA make. The PROTO XRDWIN 2.0 software was an integral part of the XRD machine, which records all the necessary data, calculations and provides the user with surface residual stresses values. Data analysis and the process parameters were optimized using Taguchi L9 orthogonal design of experiments. To determine the effects of the machining parameters on residual stress, Analysis of Variance (ANOVA) was used. The results indicate that the feed rate is only statistically significant parameter on the residual stress with the largest main effect. The optimal setup of machining parameters that cause the lowest residual stress of − 145.4 MPa was identified, with a speed of 710 m/min, a feed of 80 mm/min, and a DOC of 0.2 mm. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The surface texture process was done with carbon dioxide laser on dual-phase steel (DP 1180). The effects of the parameters of the carbon dioxide laser on the contact angle, skewness and kurtosis values were investigated, and the laser parameters required for obtaining the highest contact angle, lowest skewness and highest kurtosis have been optimized by the Taguchi method. In addition, the effects of these parameters on contact angle, skewness and kurtosis were calculated. The most effective parameters were laser power with 33.03% for contact angle, overlap ratio with 52.48% for skewness and overlap ratio with 41.34% for kurtosis. In the optimization result to obtain the optimum values, contact angle, skewness and kurtosis were found as 145.45, 0.07 and 3.39, respectively. These results are better than those obtained in the experiments for all three quantities. Since the results of the confirmation experiments performed with the parameters suggested by the Taguchi method are quite close to the expected results, it can be said that the Taguchi method is a reliable method in such studies. The results are supported by main effect plots and regression equations. [ABSTRACT FROM AUTHOR]

An artificial neural network (ANN) was developed to predict the corrosion resistance of MgO coatings produced by the plasma electrolyte oxidation process on ZX504 alloy, with experimental data from the Taguchi method for training and performance evaluations. Process variables, i.e., chemical composition, current density, frequency, and duty cycle, were considered as inputs; and the corrosion resistance (measured by electrochemical impedance spectroscopy technique) as output data. According to the simulation results in the training stage, a high correlation coefficient was achieved between predicted and measured values (~ 0.99). Using this well-trained ANN model, the proposed ANN model could predict corrosion resistance with a mean square error of approximately 0.0085 made from the test dataset. Examination of the surface morphology suggested a correlation between the microstructure and corrosion performance. The results showed that samples coated at lower Na3PO4, frequency, duty cycle, and higher KF and current density have the highest corrosion resistance. [ABSTRACT FROM AUTHOR]

Prosopis juliflora (PJ) fibre-reinforced polymer composites are fabricated with fly ash and SiC as fillers with different weight percentages. Jute layers are also sandwiched for added strength in the structure. The wear behaviour is found for the prepared composition of samples. Pin-on-disc wear testing apparatus is used for the wear performance along with the design of experiments approach using orthogonal arrays of Taguchi's. The effect of the input parameters (load, sliding velocity, speed) is studied on wear resistance. The experimental design creates sliding wear evaluations based on Taguchi's L9 orthogonal array to identify the most dominating factors influencing the wear rate. This study demonstrates that the most important component affecting the sliding wear rate of the composite materials is followed by the sliding velocity, speed, and load. The result of the wear rate decreases with an increase in filler content and also increases with sliding velocity. The samples with fly ash and SiC fillers reportedly seemed to have the best wear rates. [ABSTRACT FROM AUTHOR]

The present article deals with the optimization of additives used to improve penetration resistance of Himalayan soil and designing the pavement thickness. Eggshell powder, polypropylene fiber and sodium chloride were used as additives in a fine-grained soil for improvement in soil properties as a subgrade material. Optimization of additives was done using Taguchi method and MINITAB 21 software was employed for the analytical analysis of the responses obtained from the laboratory tests. The test results showed that the additives have potential for improvement in penetration resistance of fine-grained soil by 2.26 and 2.0 times that of untreated soil under unsoaked and soaked conditions respectively leading to considerable reduction in pavement thickness. The correlations given by the US Army Corps of Engineers and Indian Road Congress were used for determining the pavement thickness. Pavement thickness offered by US Army Corps of Engineers method is less and misleading to consider for pavement construction, whereas Indian Road Congress method has proved far better by offering rational lateral dimension for designing Indian rural hilly roads. [ABSTRACT FROM AUTHOR]

A reliable and efficient RSM with BBD was established to speedily analyze empagliflozin in wastewater and pharmaceutical formulation samples using HPLC. The Taguchi method was initially applied to determine the critical parameters among all selected variables and was then optimized with BBD. This development has numerous advantages, such as minimum organic solvent usage, short analysis times, and small sample volume with lesser waste generation. The chromatographic separation was accomplished with BDS Hypersil C18 (150 mm × 4.6 mm, 5 µm) as stationary phase using buffer: methanol (92.4:7.6, v/v) with a flow rate of 0.89 mL/min and detected at 240 nm. The calibration plot was linear between 2.5 and 20.0 μg/mL with LOD and LOQ values of 0.83 μg/mL and 2.52 μg/mL, respectively. The developed HPLC method was a superior technique linked with green chemistry based on the penalty points or analytical eco-scale score, which enhanced the method's reliability. The isolates were analyzed using FTIR spectroscopy, and the observed spectrum is comparable to the simulated spectrum obtained at the B3LYP/6-311G(d,p) level of theory. In addition, molecular structure, UV–visible spectral, electronic properties and molecular electrostatic potential of EMP were examined, and the findings will be useful for further research on EMP. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the properties of biodegradable plantable pots made from biomaterials. Specifically, rapeseed straw and cow manure biomaterials were studied here because these biomaterials add nutrients to the soil during their biodegradation and are readily available agricultural by-products. Furthermore, the use of biomaterials helps in replacing the plastic materials which are currently used to make pots and decreases the environmental impact by producing a cleaner product. The physical and mechanical properties of biocomposites pots were investigated and optimized in the present work. The effect of mixing ratio (straw: cow manure) in the composite, straw particle size, and chemical pre-treatments of straw by 1% HCl or 2% NaOH on the physical and mechanical properties of biodegradable pots was investigated. Additionally, the Taguchi method and ANOVA statistical analyses were employed for parameters optimization. The results indicated the straw to cow manure ratio exhibited a significant effect on the compression strength (CS), penetration strength (PS), and water absorption (WA) of pots. While the CS and PS of pots decreased with increasing the ratio of straw from 2 to 10% and increasing the particle size of straw from 1.5 to 3.0 mm, these changes increased the water absorption of pots (126.52–141.21% for 1.5-mm untreated straw). Chemical pre-treatments of straw investigated here resulted in decreased CS and PS of pots. The straw ratio in the straw/manure mixture is the most significant factor affecting the characteristics of biodegradable pots. [ABSTRACT FROM AUTHOR]

Context: The rapid growth and diversification of drug delivery systems have been significantly supported by advancements in micro- and nano-technologies, alongside the adoption of biodegradable polymeric materials like poly(lactic-co-glycolic acid) (PLGA) as microcarriers. These developments aim to reduce toxicity and enhance target specificity in drug delivery. The use of in silico methods, particularly molecular dynamics (MD) simulations, has emerged as a pivotal tool for predicting the dynamics of species within these systems. This approach aids in investigating drug delivery mechanisms, thereby reducing the costs associated with design and prototyping. In this study, we focus on elucidating the diffusion mechanisms in curcumin-loaded PLGA particles, which are critical for optimizing drug release and efficacy in therapeutic applications. Methods: We utilized MD to explore the diffusion behavior of curcumin in PLGA drug delivery systems. The simulations, executed with GROMACS, modeled curcumin molecules in a representative volume element of PLGA chains and water, referencing molecular structures from the Protein Data Bank and employing the CHARMM force field. We generated PLGA chains of varying lengths using the Polymer Modeler tool and arranged them in a bulk-like environment with Packmol. The simulation protocol included steps for energy minimization, T and p equilibration, and calculation of the isotropic diffusion coefficient from the mean square displacement. The Taguchi method was applied to assess the effects of hydration level, PLGA chain length, and density on diffusion. Results: Our results provide insight into the influence of PLGA chain length, hydration level, and polymer density on the diffusion coefficient of curcumin, offering a mechanistic understanding for the design of efficient drug delivery systems. The sensitivity analysis obtained through the Taguchi method identified hydration level and PLGA density as the most significant input parameters affecting curcumin diffusion, while the effect of PLGA chain length was negligible within the simulated range. We provided a regression equation capable to accurately fit MD results. The regression equation suggests that increases in hydration level and PLGA density result in a decrease in the diffusion coefficient. [ABSTRACT FROM AUTHOR]

The presence of a large amount of organic and inorganic pollutants in dairy effluent is a substantial environmental issue. This study investigated electrocoagulation (EC) as a potential treatment method for dairy wastewater under different operating conditions, such as applied voltage (5–25 V), electrolysis time (30–90 min), and inter-electrode distance (1–2 cm) by using aluminum electrodes. This study focuses on achieving the maximum removal of BOD, COD, and nitrate in dairy effluents with the aforementioned operating conditions. The process was optimized using the response surface methodology (RSM) and Taguchi method. RSM method optimized the electrocoagulation operating conditions such as the voltage at 23.75 V, time of 90 min, and inter-electrode distance at 1.07 cm. This optimization achieved the maximum removal percentage of BOD, COD, and nitrate at 79.06%, 84.35%, and 79.64%, respectively, in dairy effluent. Taguchi method optimized the electrocoagulation parameters such as the voltage at 25 V, time duration of 90 min, and inter-electrode distance of 1.00 cm, showcasing improved removal percentages of BOD, COD, and nitrate as 90.54%, 89.28%, and 82.74% respectively. The current study attempts to understand the optimization efficiencies between Taguchi method and response surface method for diary wastewater treatment. [ABSTRACT FROM AUTHOR]

Detecting emotions from facial images is difficult because facial expressions can vary significantly. Previous research on using deep learning models to classify emotions from facial images has been carried out on various datasets that contain a limited range of expressions. This study expands the use of deep learning for facial emotion recognition (FER) based on Emognition dataset that includes ten target emotions: amusement, awe, enthusiasm, liking, surprise, anger, disgust, fear, sadness, and neutral. A series of data preprocessing was carried out to convert video data into images and augment the data. This study proposes Convolutional Neural Network (CNN) models built through two approaches, which are transfer learning (fine-tuned) with pre-trained models of Inception-V3 and MobileNet-V2 and building from scratch using the Taguchi method to find robust combination of hyperparameters setting. The proposed model demonstrated favorable performance over a series of experimental processes with an accuracy and an average F1-score of 96% and 0.95, respectively, on the test data. [ABSTRACT FROM AUTHOR]

The forward osmosis (FO) process has recently gained significant interest in treating wastewater, brackish/seawater and concentrating feedstocks for various operations, including desalination. The study investigates the effect of different synthesis conditions of the polyamide-based thin-film composite (TFC) FO membranes on the membranes' final performance. Taguchi statistical analyses were used to fabricate and optimize the polyamide TFC FO membrane. The process parameters as factors were the amount of polyethersulfone (PES), polyethylene glycol 400 (PEG-400), polyvinyl pyrrolidone (PVP), m-phenylenediamine (MPD), and trimesoyl chloride (TMC), and TMC reaction-time (RT). The Taguchi method was adopted to investigate the optimal conditions and the significance of individual factors using an L16 (45) orthogonal array. Another Taguchi analysis (Taguchi 2) was adopted to investigate the influence of other important parameters like optimal conditions for MPD, TMC, and TMC reaction-time factors using an L9 (33) orthogonal array. Confirmation tests validated a maximum water flux of 46.4 ± 2.32 L/m2·h with a specific combination of control factors for membrane synthesis: PES/PEG/PVP/MPD/TMC/TMC RT-16/7/0.5/1/0.05/30. These tests demonstrated a high-water flux of 7.05 ± 0.35 L/m2·h when exposed to industrial wastewater (secondary effluent) as the feed solution (FS) and fertilizer as the draw solution (DS) in the FO process. The R2 values were more than 90%. The experimental validation confirmed the models' predictive ability with different FSs, including industrial wastewater. [ABSTRACT FROM AUTHOR]

In this study, the complete droplet generator of digital droplet polymerase chain reaction system is developed for limited sample detection. The digital droplet polymerase chain reaction proving the viral load quantification results directly is important for diagnosis and tracing the viral load. Before the sample undergoes the thermal cycle, a process for DNA replication, the droplet generator reached to partition each sample into 20,000 nanoliter-sized droplets. For the fastest viral load testing, the droplet generated speed is important. The droplet generator system consists of cover layer, parent droplet layer, microstructure layer, droplet observation layer, and base layer, respectively. The engineered fluid mixing is filled with the surfactant concentration in the droplet generator system. The surfactant and engineered fluid are biocompatible. The sample is mixed with the magnetic nanofluid and then the magnetic pulling force acting on the parent magnetic droplet is separated into several nanoliter-sized droplets by microstructure. The volume of droplets and the speed of the droplet process are related to A: the surfactant concentration of engineered fluid, B: magnetic nanofluid concentration, C: the pattern of the microstructure layer, and D: the volume of the parent droplet. To this end, the optimization via Taguchi method is carried out. [ABSTRACT FROM AUTHOR]

Medical containers that sterilize surgical instruments are constantly needed in the healthcare industry. In line with this need, improvements in the fabrication of medical containers are important. Determining the design factors of medical containers fabricated by deep drawing saves time and cost. This study determined, the design factors of square medical containers and experimentally verified the deep drawing process modeled in Abaqus/Explicit finite element (FE) software. Taguchi statistical method was used to reduce the number of experiments. Blank holder force (BHF), punch radius (RP), die radius (RD), coefficient of friction between die and blank (µDB), coefficient of friction between punch and blank (µPB), coefficient of friction between holder and blank (µHB) as variable factors while selecting thickness reduction (TR) and maximum punch force (PF) were selected as output parameters. The effect of variable factors on the output parameters was determined by ANOVA analysis. As a result of the examinations, it was deter-mined that TR and PF increased as BHF, µDB and µHB values increased, whereas they decreased as RP and RD increased. On the other hand, it was determined that TR decreased and PF increased as µPB increased. In addition, the corners of the sheets were chamfered in different sizes to prevent the formation of ears in the containers. Finally, the appropriate chamfer size was determined by examining the sheet thicknesses. [ABSTRACT FROM AUTHOR]

We report on the optimization of the surface roughness of hybrid additive manufactured Ni superalloys, combining a conventional laser powder bed fusion process with in situ high-speed milling. This remarkable hybrid approach has only recently been applied to different steel types and barely to Ni superalloys which opposite to steel appear to be challenging for milling processes, particularly within the powderbed of laser powder bed fusion. Different influencing factors on the surface roughness are varied in this study, following the Taguchi method. Their effect is evaluated with respect to the average surface roughness and the maximum surface roughness. The signal-to-noise ratio for the varied parameters infeed, z-pitch, feed rate, and spindle speed is calculated, determining their relevance on the surface roughness, and defining an optimal parameter combination. As the surface quality is optimized to R a = 0.47 μ m , the definition of the optimal parameter combination is of the highest relevance for the application of this novel manufacturing approach for Inconel. Using linear regression, the resulting surface roughness of these parameters is predicted, getting validated by the experimental evaluation. Due to a further analysis, including EDX analysis and a quantitative element analysis at different positions of the flank of the milling cutter, wear characteristics as well as the dissipation of the coating of the milling cutter are detected. The flank wear and the resulting breakage of the cutting edge are defined as the main reasons of a rising surface roughness. [ABSTRACT FROM AUTHOR]

The meta-heuristic algorithms require a lot of fitness calculations to get good enough solutions, which constitutes an obstacle to solving computationally complex practical problems. Recently, it has been found that surrogate-assisted meta-heuristic algorithms show potential in solving expensive complex optimization problems. This paper proposes an efficient surrogate-assisted Taguchi salp swarm algorithm (SATSSA) to solve expensive complex optimization problems. The SATSSA uses a combination of the local surrogate-assisted model (LSAM), global surrogate-assisted model (GSAM), and k-means clustering surrogate-assisted model (KCSAM) to fit the fitness function. To enhance the prediction ability of the model, an improved salp swarm algorithm with the Taguchi method (TSSA) is proposed to update and predict the model. GSAM is mainly used to capture the entire landscape of the search space. KCSAM is designed to capture part of the search space to improve the exploration capability of the algorithm. LSAM is used to capture the contours around the optimal individual. The proposed SATSSA is compared with other four excellent algorithms on 30D, 50D, and 100D benchmark functions. In addition, SATSSA is also applied to intrusion detection. Simulation results show that SATSSA is effective in improving detection rate and reducing false alarm rate. [ABSTRACT FROM AUTHOR]

This study reports a methodology for predicting surface roughness using data-driven models with grinding force as the input data. Prior to the model training process, the critical grinding parameters for brass material were selected and optimized using the Taguchi method. The experimental grinding force data were then collected and preprocessed into three features: the raw feature as the baseline feature, the statistical feature, and the fast Fourier transform (FFT) feature. The data were imported into a linear regression model as the baseline model and a deep neural network (DNN) model as the proposed strategy. The widely used surface roughness (Ra) of the ground workpiece was experimentally measured and served as the performance index. The model's performance was evaluated based on the mean absolute percentage error (MAPE) between the predicted and measured Ra values. The validation of the Ra prediction revealed that, among all test combinations, the DNN model with four hidden layers and the FFT feature as the input had the best performance of surface roughness prediction, with a MAPE of 3.17%. The independent testing and evaluation of the DNN model with the FFT feature yielded a MAPE of 6.96%, indicating that the proposed strategy effectively predicted the surface roughness of the workpiece. This work also proposes an automatic regrinding strategy in which the grinding system automatically regrinds the workpiece if the predicted Ra of the workpiece in the previous grinding process exceeds the threshold. Experimental results confirmed that among 24 ground areas, two areas have roughness exceeding the threshold and need to be regrind, and the proposed strategy can correctly identify and regrind these two areas (100% success rate). After automatic regrinding, the workpiece exhibited a roughness lower than the set threshold. [ABSTRACT FROM AUTHOR]

Many practical high-pressure die casting process (HPDCP) optimization problems are multi-objective optimization ones that optimize multiple quality attributes of castings, simultaneously. This paper proposed a new HPDCP optimization method for improving volume of shrinkage porosity (VSP) and air entrainment (AE) using Taguchi-based ProCAST simulation and multi-attribute decision-making (MADM)-based overall quality index. Taguchi orthogonal array was used to design ProCAST simulation experiment. MADM was used to convert multiple quality attributes into a single overall quality index (OQI). Taguchi optimization method was used to determine the optimal HPDCP parameters to maximize the OQI. By using the proposed method, this paper determined the optimal HPDCP parameters such as pouring temperature (PT), filling rate in shot sleeve (FR), piston velocity (PV) and preheating mold temperature (PMT) for improving the VSP and AE in carburetor housing with aluminum alloy AlSi9Cu1Mg. The optimal HPDCP parameters were PT of 640 °C, FR of 40%, PV of 6.5 m/s, and PMT of 150 °C. The PT was the most effective HPDCP parameter for improving the VSP and AE, and the next were FR, PV, and PMT. The proposed method could be actively applied to not only HPDCP but also other casting processes and other manufacturing processes. [ABSTRACT FROM AUTHOR]

Friction lap welding was used to join aluminum with glass fiber–reinforced thermoset polymer (GFRP) using a thermoplastic interlayer. The effect of different welding parameters on joint strength and fracture surfaces was investigated, and the optimal welding parameters were determined using the Taguchi method. Results revealed that low heat generation led to weak mechanical interlocking between GFRP and the thermoplastic interlayer, while high heat generation caused degradation of the aluminum/thermoplastic polymer interface. The tool traverse speed was found to be the most influential parameter in terms of joint strength, followed by plunge depth and rotational speed. Moreover, thermal measurements were conducted during the welding process using thermocouples. An uneven thermal distribution was discovered across the overlap area due to dissimilar substrates. This issue was resolved by incorporating aluminum thermal insulation, resulting in improved heat distribution and a significant enhancement of 94% in joint strength. Scanning electron microscopy (SEM) was employed to identify joining mechanisms and examine the effect of welding parameters on joint microstructure. Furthermore, Fourier-transform infrared spectroscopy (FTIR) was used to investigate chemical bond formation at the aluminum/thermoplastic polymer interface. The results showed that the joining mechanisms involved mechanical interlocking between the thermoplastic interlayer and aluminum, as well as chemical bonding, penetration, and intertwining between the thermoplastic interlayer and the thermoset composite. [ABSTRACT FROM AUTHOR]

In the present study, natural convection heat transfer is investigated in a porous cavity filled with Cu/water nanofluid and equipped with horizontal fins. Optimization and sensitivity analysis of the fin's geometry, porous medium and nanofluid properties to maximize heat transfer rate is the aim of this work. To achieve this purpose, a design space is created by input parameters which include length, number of fins, distance between fins, porosity, Darcy number and volumetric fraction of the nanoparticles. Several tools have been used to implement optimization methods including the Taguchi method (TM) for design points generation, sensitivity analysis of design variables by using signal-to-noise ratio (SNR) and analysis of variance (ANOVA), response surface method (RSM) for interpolation and regression by using nonparametric regression, and genetic algorithm (GA) for finding optimum design point. The double multi-relaxation time lattice Boltzmann method (MRT-LBM) is used to analyze and simulate the flow field and heat transfer in each design point. The results show that the optimal configuration leads to an average Nusselt number of 5.56. This optimal configuration is at the length of fins L/2, the number of fins 2, the distance between fins L/12, porosity 0.8, Darcy number 0.1, and the volumetric fraction of the nanoparticles 0.02. By using the SNR results, the Darcy number and the number of fins have the most and the least effect in maximizing the average Nusselt number, respectively. The ANOVA results and global sensitivity analysis (GSA) findings further validated this conclusion. [ABSTRACT FROM AUTHOR]

Current research is investigating the effect of different tube geometries on flow patterns and thermal performance. Perform numerical simulations and thermo-fluid couplings. Calculation results are calculated and the solution uses both flow transport and thermal correction. Results are compared and validated using experimental results. Hydraulic and heat flow behaviors in all corrugated tubes are studied and discussed under various constitutive parameters of position and shape. The turbulent fluid flow in these tubes is modeled using 3D numerical flow domain simulations and the optimization of the multilens algorithm is analyzed. The effects of various geometric design parameters such as ring diameter, spacing between each well ring, and number of well rings around the tubing spacing of the rings were analyzed using Response Surface Methodology (RSM) and Taguchi Method (TM). Analyzed. be studied. The effects of changes in flow structure, such as velocity magnitude and radial velocity, and velocity magnitude and radial velocity profiles in different configurations, are studied. An experimental design strategy using the Taguchi method (TM) is chosen according to the variance of the orthogonal L16 sequences. Optimization results show that higher differential pressure values are related to shaft diameter. Therefore, the number of corrugated rings has a great effect on the heat transfer rate and temperature difference. Various configurations of Conduit Performance Evaluation Factor (PEF) increased the PEF value by more than 1.3. [ABSTRACT FROM AUTHOR]

To increase the life of a blast furnace, copper cooling staves with high cooling capacity are installed in different locations of the blast furnace. The structure and size of the copper cooling stave depend on the structure and size of the blast furnace and the operating characteristics of the blast furnace. In HIsmelt (high-intensity smelt) direct smelting process, the furnace has some differences from the conventional blast furnace in the fuel used and in the structure. To manufacture the copper cooling stave for the HIsmelt furnace, its structure with cooling capacity to ensure the safe operation of the furnace is designed and then its casting process is also designed. The design of the copper cooling stave is given by the size of copper cooling stave, the diameter of copper tube installed in it and the arrangement of copper tube. The wall thickness of the cooling stave and the flow rate of the cooling water are determined and the cooling capacity of the copper cooling stave under the HIsmelt furnace operating conditions is simulated using Fluid Flow (Fluent) of Ansys Workbench programme (version 15), in order to examine the stability of the copper cooling stave. Hence, the thickness of the copper tube is determined to be 60 mm, the distance between the copper tube centers is 200 mm and the wall thickness of the copper cooling stave is 200 mm. The casting process is simulated using commercial simulation software, ProCAST, to construct a casting process for copper cooling stave and to prevent the melting of copper pipe in the mold during casting and solidification of the molten metal, the occlusion of flow channel of the cooling water, and the supply of the cooling agent, water of 94%+ air of 6%(weight percentage), in order to prevent the separation of the cooling stave and copper pipe. Based on the simulation results, copper cooling staves are produced and installed in the HIsmelt furnace. [ABSTRACT FROM AUTHOR]

The main goal of this research was to investigate the influence of additive manufacturing (AM) printing parameters on the mechanical properties and surface roughness of specimens fabricated using recycled polylactic acid (rPLA). In order to achieve this goal, significant printing parameters such as layer thickness, infill density, and nozzle temperature were selected based on prior research. A three-level L9 orthogonal array, based on the Taguchi method, was used in the experimental design. The mechanical properties of virgin PLA and recycled PLA printed specimens were examined and compared. To facilitate the analysis of variance (ANOVA) examination, the response data for mechanical and surface roughness parameters were transformed to signal-to-noise (S/N) ratios. The inspected responses under consideration were the surface roughness, shore D hardness, tensile strength, flexural strength, and impact strength. The main findings suggest that careful consideration of the layer height is crucial for achieving optimum mechanical properties in the recycled PLA specimens. Furthermore, the nozzle temperature also played an important factor that affected the mechanical and surface roughness properties of the 3D printed PLA specimens. Microscopic investigation demonstrated that the number and size of voids increased significantly when the layer thickness and temperature were low, namely, 0.1 mm and 195 ℃, respectively. Finally, the optimal combination of printing parameters for each performance characteristic was determined. Following this, a confirmation test was performed using the preferred combination of parameters, which indicated a strong correlation with the outcomes predicted statistically. The results obtained from this study revealed that recycled PLA exhibited mechanical properties comparable to that of virgin PLA under certain conditions. In summary, the results of this study will serve as a valuable dataset in the field of additive manufacturing, providing valuable insights for other researchers working with recycled PLA material. [ABSTRACT FROM AUTHOR]

This research aims to develop a sustainable approach for selecting fiber-reinforced synthetic aggregate concrete (FRSAC) through experiments employing the Taguchi method and multi-criteria decision-making (MCDM) techniques. This study examined the fresh and mechanical behavior, as well as considering the environmental, and economic characteristics of FRSAC theoretically to determine the most environmentally friendly concrete, which may be suitable for various types of applications in concrete. The Taguchi optimization technique considered four functional parameters: binder content, water-to-cement ratio, fiber dosage, and synthetic aggregate replacement in three levels. Synthetic aggregates were manufactured from industrial byproducts in various geometries that may have enhanced aggregate mechanical properties compared to natural aggregates. Using multi-criteria decision-making technique, namely Technique of Ordering Preferences by Similarity to Ideal Solution (TOPSIS), a robust framework was developed and analyzed for FRSAC based on four performance factors including fresh (workability), mechanical (compressive and split tensile strength), and durability (water absorption) properties. Mechanical behavior of FRSAC has been assigned higher weightage in the first case, and the combination of fresh and durability behavior of the FRSAC in second case. In this study, a TOPSIS analysis was conducted in two instances using varying weights to optimize the proportions of fiber-reinforced synthetic aggregates in concrete. The optimal mix (OM1) has resulted in a maximum compressive strength of 55.12 MPa and split tensile strength of 5.50 MPa. Similarly, the optimal mix (OM2) resulted in higher workability of 90 mm and lower water absorption of 3.92%. The anticipated results of the optimal blends were experimentally confirmed. The obtained experimental results have been supported by microstructure analysis of the control and optimal mixes (scanning electron microscopy and X-ray diffraction). [ABSTRACT FROM AUTHOR]

In this research, dissimilar metals of AA 6082 and AA 7075 are joined using Gas Tungsten Arc Welding (GTAW) process with ER4043 filler wire. The welding conditions and their range are identified for producing quality welding characteristics. Taguchi based techniques are adopted for design of experimentation and analyzing factors involved in welding characteristics. L-9 Orthogonal Array (OA) was used for Design of Experiments (DOE). Welding current, filler diameter and root gaps are selected as input parameters. The welded structure defects were inspected with X-ray radiography images as well as macrostructures. The response factors such as Ultimate Tensile Strength (UTS), % of elongation, hardness and impact strength were considered and evaluated by conducting mechanical tests. Analysis of Variance (ANOVA) is conducted to study the influence of parameters on responses. The tensile strength of sample 5 is increased by 53.37% when compared with the sample 6 due to the lower heat input rates. The welding speed (68%) has most influence parameter followed by welding current (14%) and filler diameter (14%). The dissimilar combination of aforementioned joints have wide range of application including aerospace, defense, and military sectors. [ABSTRACT FROM AUTHOR]

In this research, dissimilar plates of AA5083 and AA6082 were used to develop the dissimilar components where high corrosion resistance and good mechanical properties required especially in aerospace industries. TIG welding set-up has been made to join these dissimilar joint using ER4043 as filler rod. The parameters such as current, time and filler rod diameter were selected at three levels. The design of experimentation was made according to L-9 orthogonal array. After welding, samples were sliced into various specimens to conduct mechanical testing's. Tensile test was conducted on UTM as per ASTM E/8 standard. Izod test was conducted to calculate the impact energy observed before fracture under Charpy testing machine. Brinell hardness values were evaluated by testing the weld surface hardness. The output response factors like UTS, impact strength and hardness were considered as response factor to study the effect of parameters. ANOVA has been performed on output response and the analysis results were presented. From the ANOVA, the welding speed (52.54%) exerted a major effect on responses followed by weld current (22.83%) and filler diameter (20.18%). The grain boundaries with fine structures were identified at AA6082 interface whereas coarse grain structures were observed at 5083 interface due to the thermal properties. [ABSTRACT FROM AUTHOR]

In this study, EC process using an aluminum anode, and EC-EO process using aluminum and mixed metal oxide, i.e., platinum-ruthenium dioxide-coated onto titanium (Al-Ti/Pt-RuO2) anode was used to understand the remove of phenolic syntan (PS) from synthetic tannery wastewaters. The operational conditions of the abovementioned electrochemical processes were optimized using Taguchi L16 method in terms of maximum removal of total organic carbon (TOC) and PS. At the optimum operating condition (current density = 14.25 mA/cm2, initial pH = 4, rotational speed = 70 rpm and initial PS amount = 0.25 g/L), the incomplete removal of TOC (83.93%) and PS (81.19%) was obtained in the EC process with the energy consumption of 0.135 kWh/g TOC remove and 0.056 kWh/g PS remove. In contrast, almost (≈100%) complete removal of the dissolved organic pollutant was observed in the EC-EO process with the energy consumption of 0.113 kWh/g TOC remove and 0.0453 kWh/g PS remove. The energy consumption per g TOC and PS removed was 0.135 and 0.056 kWh for the EC process, whereas 0.113 and 0.0453 kWh for the EC-EO process. The operating cost of the EC-EO process was estimated to be 1.39 USD/m3, which was lesser (-19.65%) than the operating cost of the EC process. Signal-to-noise ratio and ANOVA results showed that current density was the most influential parameter with the highest delta value and contribution ratio for TOC and PS removal in both the EC and EC-EO process. The UV/Vis and FT-IR analyses indicate that the highest removal of aromatic compounds was obtained in the EC-EO process compared to the EC process. FT-IR analyses confirmed that the PS was first degraded into a quinone functional group, which was further oxidized into carboxylic acid. [ABSTRACT FROM AUTHOR]

Biodiesel production through the synthesis of Datura stramonium L. oil is studied to explore the most efficient approaches to suggest an alternate feedstock for biodiesel production. The main objective of this work is to optimize the process variables of biodiesel synthesis by using some statistical approach (Taguchi method, grey relational analysis (GRA), and response surface methodology (RSM) analyzing three parameters, i.e., alcohol-to-oil molar ratio, catalyst (NaOH) concentration, and process temperature for achieving maximum biodiesel derived from Datura stramonium L. oil. The transesterification process is applied by using an ultrasonic-assisted technique. Grey relational analysis (GRA) was successfully applied with the Taguchi method resulting in the optimum combination of A2B1C1. Based on the findings, the best operating conditions for transesterifying are attained with the RSM approach consisting of a 5.697:1 molar ratio (level 2), 0.3 (wt.%) NaOH concentration (level 1), and 70 °C process temperature (level 1). With a value of 87.02%, these ideal operating conditions produce the maximum yield as compared to grey relational analysis (GRA) yields 83.99%. The obtained results have been verified through the characterization of oil and biodiesel as well. Also, the fuel qualities of DSL biodiesel were identified and assessed. DSL oil was found 137.6 degrees of unsaturation during fatty acid profile analysis. DSL biodiesel was found the best kinematic viscosity (4.2 mm2/s) and acid value (0.49) when compared to Karanja and palm biodiesel. D. stramonium L. was recognized as a suitable species for biodiesel feedstock according to the findings. [ABSTRACT FROM AUTHOR]

The challenge of maintaining consistent quality in injection molding is critical, yet conducting a comprehensive inspection is both costly and time consuming. Leveraging artificial intelligence, this study proposed using machine learning—specifically multilayer perception (MLP) models—to predict the quality of injection-molded parts. The accuracy of this approach largely relies on hyperparameter tuning, a process that can be cumbersome and suboptimal if performed through trial and error. The Taguchi method has the advantages of robustness, efficiency, and simplicity, and is a widely used robust optimization tool. However, this method assumes a linear relationship between factors, which limits the processing of complex systems where interactions between factors are nonlinear. Furthermore, the Taguchi method is sensitive to initial assumptions about factors and their levels, and the results may not reflect the true behavior of the system. To address this, a two-stage design-of-experiments method was devised that systematically identifies the optimal hyperparameter settings, including the maximum number of epochs, learning rate, momentum, activation function, minimum batch size, and numbers of hidden layers and nodes. The method is executed in two stages: (1) an L12 (21 × 35) orthogonal array is used to identify the primary factors affecting model accuracy and (2) an L8 (23) full-factorial experiment is conducted discover the combinations that yield the highest performance. Two experimental case studies, integrated circuit (IC) tray width prediction and optical component weight prediction, were used to validate the proposed method. The results revealed that the best hyperparameter settings resulted in validation and test accuracy of 96.83% and 95.30%, respectively, for IC tray width prediction. The average root-mean-square errors are 0.019 and 0.022 in model validation and test, respectively, for optical component weight prediction, with short computational time. The proposed method demonstrates how the systematic optimization of hyperparameters for MLP model can enhance the efficiency and stability of model training and can be used to advance quality control in the field of injection molding. [ABSTRACT FROM AUTHOR]

Dynamic errors from the robotic machining process can negatively impact the accuracy of manufactured parts. Currently, effectively reducing dynamic errors in robotic machining remains a challenge due to the incomplete understanding of the relationship between machining parameters and dynamic errors, especially for hexapod machining cells. To address this topic, a dynamic error measurement strategy combining a telescoping ballbar, an unscented Kalman filter (UKF), and particle swarm optimization (PSO) was utilized in robotic machining. The machining parameters, including spindle speed, cutting depth, and feeding speed, were defined using the Taguchi method. Simultaneously, vibrations during machining were also systematically measured to fully comprehend the nature of dynamic errors. Experimental results indicate that dynamic errors in a hexapod machining cell (HMC) are significantly amplified in machining setups, ranging from 4 to 20 times greater compared to those of non-machining setups. These errors are particularly influenced by machining parameters, especially for spindle speed. Furthermore, the extracted dynamic errors exhibit comparable frequency distributions, such as spindle frequency and tool passing frequency, to the vibration signals obtained at the chosen sampling rate. This expands the application and enhances the comprehension of dynamic errors for spindle and cutting tool condition recognition. [ABSTRACT FROM AUTHOR]

Mechanical properties of semi-solid casting are dependent on multiple processing parameters, and improper processing parameters will not only reduce mean data but also increase variations. The present study investigated the impact of parameters in slurry preparation and heat treatment on the yield strength and ductility of T6 heat-treated A356 Al-Si alloy using rapid slurry forming (RSF) semi-solid casting. The focus was primarily on the robustness of mechanical properties based on Taguchi design method. By analyzing signal-to-noise ratio and minimum value calculated from x̄-3S, the optimum slurry preparation parameters and heat treatment parameters were determined to be no quench, enthalpy exchange material (EEM) temperature of 140 °C, EEM-to-melt ratio of 6mass%, stirring time of 18 s, solution heat treated at 520 °C for 2 h, and ageing heat treated at 190 °C for 6 h. In a small batch validation, the -3S yield strength and -3S elongation reach 256.1 MPa and 5.03% respectively, showing a satisfactory robustness. The hardness and microstructure of heat-treated samples with the best and worst properties were characterized to gain insight into the underlying mechanisms affecting the mean value and variations of mechanical properties. [ABSTRACT FROM AUTHOR]

Taguchi method was employed to investigate the influence of blended powder semisolid forming (BPSF) factors on the porosity and hardness of 316L matrix nanocomposites. These factors included the particle size (316L and Al2O3), Al2O3 weight fraction, and blending time. 316L/Al2O3 powders were added to ethanol solution and subjected to ultrasonic homogenization. Subsequently, the powders were blended using a planetary ball mill. Cold compaction was performed under 800 MPa pressure. Semisolid sintering process was conducted in 1440°C. Powder morphology, microstructure, and phase formation were investigated. The particle size of the matrix and mechanical blending time have the greatest impact on the porosity, while the reinforcing particle size and weight fraction of reinforcing material have the least influence on the porosity. As for hardness, the matrix particle size was identified as the most significant factor, followed by the reinforcing weight fraction and mechanical blending time. The reinforcing particle size exhibited the least effect on the hardness. Successful distribution and dispersion of nanoparticles within matrix were achieved in optimized samples. The results introduce BPSF as a promising method in developing high performance 316L matrix nanocomposites. [ABSTRACT FROM AUTHOR]

Economic and efficient application of enzyme induced calcium carbonate precipitation (EICP) requires optimisation of the process and understanding of the precipitate microstructure. The objective of this study was to compare the precipitate efficiency and the interface shearing resistance of the precipitate, using Taguchi method. The factors which controlled the precipitate were urea-calcium chloride concentration, urease activity and reaction duration. Precipitation tests and torsional shear tests were performed using orthogonal L25 with 25 array runs. Taguchi method suggests two different optima for precipitate efficiency and interface shearing resistance. However, to obtain a single optimum through simultaneous optimisation of both the responses, Taguchi method was integrated to grey relational analysis. The obtained optimum, henceforth, was set at 0.5 mol/L of urea and calcium chloride concentration, 45 kU/L of urease activity and reaction duration of 48 h. The results show that the interface shearing resistance was controlled by the morphology of the precipitate, especially since the chemical concentration and kinetics of ureolysis resulted in different precipitate morphology. All the control factors were significant, including the contribution of the urease activity. Urease activity enhanced the precipitate efficiency and the interface shearing resistance. Aggregation of particles at higher urease activity resulted in improved shearing resistance. [ABSTRACT FROM AUTHOR]

The Tunisian Lebna dam sediment was utilized to create the zeolite faujasite type Na-X. The aim of this investigation is to optimize the yield of Na-X zeolite using alkaline fusion hydrothermal treatment. Taguchi orthogonal array design was employed with nine trials to explore operating parameters including fusion temperature and time, activator type, and sediment type. The efficiency of alkaline fusion was evaluated using acid solubility. After dissolving the optimal alkali-fused sample in water, the Box–Behnken plan was used to identify the influence of L/S ratio, crystallization temperature, and time on zeolite Na-X yield. Rietveld analysis identified the mineral phases in the sediment as quartz (82.0%), calcite (8.8%), kaolinite (6.0), and illite (1.2%). With a NaOH activator, 850 °C fusion temperature for 30 min, 15 L/S ratio, and 75 °C crystallization temperature for 4 days, highly crystalline zeolite Na-X was created. FTIR, TGA, N2 adsorption–desorption isotherm, and X-ray diffraction were used to thoroughly describe this sample. The findings reveal the substantial zeolitization potential of the raw Lebna dam sediment, resulting in a high yield of zeolite Na-X. [ABSTRACT FROM AUTHOR]

Friction stir welding (FSW) processing of the joint is a technique to improve the quality of the weld. The present research employed the friction stir welding technique to butt-weld AA5754 plates, whereby the joints of every weld case were identified based on their tensile strength, hardness, and impact toughness. The plates were joined by varying the rotational speeds, welding speeds, and tool tilt angles. A multi-objective optimization Taguchi's design of experiments approach and grey relational analysis (GRA) were used in this study to assess the combined effects of the process variables. The developed models are evaluated for sufficiency, and then the most significant parameters are determined using the analysis of variance (ANOVA). The results of the ANOVA showed that the rotational speed has a maximum contribution of 55.24%, 59%, and 46.27% in obtaining the optimal values of tensile strength, hardness, and impact toughness, respectively. It was found that formability and mechanical behaviors increased with increasing tilt angle for the tilt angle range examined in the current study. The two methods provide the same results, and the optimal conditions are a rotational speed of 1000 rpm, a welding speed of 60 mm/min, and a tilt angle of 2.5°. The optimal values for tensile strength, hardness, and impact toughness, respectively, were found to be 136 MPa, 85.25 HV, and 13 J. Significant implications for the welding industry may arise from the highly favorable outcomes in terms of microstructure and mechanical attributes. [ABSTRACT FROM AUTHOR]