Taguchi Experimental Design Research Articles

Cavitation erosion behaviour of MAB-CU4 alloy: Influences of cavitation number, attack angle, time, and stand-off distance

Abstract The present study comprehensively examines the cavitation erosion behaviour of a manganese aluminium bronze alloy (MAB-CU4 alloy) as a function of several parameters (i.e., cavitation angle, cavitation number, time, and stand-off distance), particularly focusing on the influences of cavitation angle on the surface morphology and topography of the alloy. According to the design of experiment (Taguchi experimental design) analysis, mass loss increased with cavitation number and attack angle, while increasing the stand-off distance resulted in a decrease in mass loss and an increase in the surface area affected by cavitation erosion. Cavitation erosion behaviour was most affected by the cavitation attack angle, with the cavitation attack angle contributing 69.1% to total erosion, according to variance analysis. At 90° cavitation attack angle, MAB-CU4’s erosion rate was 64% greater than that at 30°. Scanning electron microscopy and optical profilometry revealed that cavitation erosion damage at 90° occurred mostly in the grain interiors as cavitation pits due to severe plastic deformation and surface corrosion, whereas pit formation was restricted around the hard secondary phases at the grain boundaries. At 30°, deep cavitation pits were limited, the erosion crater expanded, and the number of pits was reduced. Overall, finer microstructures with more grain boundaries and secondary phases may improve cavitation erosion resistance at 90°. The present study is the first to comprehensively capture erosion damage at the microstructural scale and analyse the impact of microstructural features on the erosion damage during the cavitation erosion of MAB-CU4 alloy.

Enhancing Compressive Strength of Cement by Indigenous Individual and Co-Culture Bacillus Bacteria

Using a Taguchi experimental design, this research focuses on utilizing indigenous bacteria from the Danube River to enhance the self-healing capabilities and structural integrity of cementitious materials. Bacillus licheniformis and Bacillus muralis were used as individual bacterium or in co-culture, with a concentration of 8 logs CFU, while the humidity variation involved testing wet and wet–dry conditions. Additionally, artificial neural network (ANN) modeling of the compressive strength of cement samples results in improvements in compressive strength, particularly under wet–dry conditions. By inducing targeted bacterial activity, the formation of calcium carbonate precipitates was initiated, which effectively sealed formed cracks, thus restoring and even enhancing the material’s strength. In addition to short-term improvements, this study also evaluates long-term improvements, with compressive strength measured over periods extending to 180 days. The results demonstrate sustained self-healing capabilities and strength improvements under varied environmental conditions, emphasizing the potential for long-term application in real-world infrastructure. This study also explores the role of environmental conditions, such as wet and wet–dry cycles, in optimizing the self-healing process, revealing that cyclic exposure conditions further improve the efficiency of strength recovery. The findings suggest that autochthonous bacterial co-cultures can be a viable solution for enhancing the durability and lifespan of concrete structures. This research provides a foundation for further exploration into bio-based self-healing mechanisms and their practical applications in the concrete industry.

Recovery of samarium and cobalt/iron oxide from SmCo magnets through acid baking and water leaching

AbstractRare earth elements (REEs) and cobalt (Co) are listed as critical raw materials because of their importance in global industrial production growth, high supply risk, and economic significance. The recovery of Co and REEs from secondary resources is therefore proposed as a key countermeasure to address this concern. In this study, a straightforward process that integrates acid baking and water leaching is proposed for the recovery of samarium (Sm) and Co from scrap SmCo magnets. Firstly, the chemical composition of SmCo magnets is revealed by ICP-OES and XRF. The Taguchi experimental design technique is employed to optimize nitric acid baking and water leaching. Based on the thermal decomposition behavior of Co, Fe, and Sm, the acid baking temperature is studied for the conversion of metal nitrates, excluding REEs nitrates, into metal oxides. The optimal conditions for acid baking and water leaching are identified, and a reactor for the pilot-scale acid baking process is proposed. The optimum parameters are tested with the proposed reactor.

Biomechanics of the Human Knee Joint in Maximum Voluntary Isometric Flexion: Study of Changes in Applied Moment, Agonist-Antagonist Participations, Joint Center, and Flexion Angle.

Estimation of the knee joint strength by maximum voluntary isometric contraction (MVIC) is a common practice to assess strength, coordination, safety to return to work or engage in sports after an injury, and to evaluate the efficacy of treatment modalities and rehabilitation strategies. In this study, we utilize a previously validated coupled finite element-musculoskeletal model of the lower extremity to explore the sensitivity of output measures (posterior cruciate ligament [PCL]/muscle/contact forces and passive moments) in knee MVIC flexion exercises at seated position. To do so, at three knee flexion angles (KFA), input measures (resistance moment and contribution moments of quadriceps and gastrocnemii) were varied at four levels each using the Taguchi design of experiment. Our findings reveal significant increases in PCL forces with KFA (p < 0.01), net MVIC moment (p < 0.01), and resistance moment of quadriceps (p < 0.01). In contrast, they drop at larger activity in gastrocnemii (p < 0.01). Tibiofemoral (TF) contact forces increase with the net MVIC moment (p < 0.01). The passive knee flexion moment, while highly dependent on the location at which computed, also increases with the net MVIC moment (p < 0.01). Changes in KFA, MVIC moment, and proportions thereof carried by quadriceps and/or gastrocnemii substantially affect biomechanics of the joint. Compared with level walking and stair ascent, slightly larger contact forces/stresses and much greater PCL forces are computed. This study improves our understanding of the knee joint behavior during MVIC in effective evaluation and rehabilitation interventions. Besides, it emphasizes the importance of positioning the joint center in model studies.

Characterization, generative design, and fabrication of a carbon fiber-reinforced industrial robot gripper via additive manufacturing

Robot grippers are crucial components across various industrial applications, requiring special design and production for obtaining the optimal performance. Conventional plastic injection moulding techniques fall short in achieving the specificity needed for these grippers. To address this challenge, current paper focuses on developing a robot gripper using carbon fiber-reinforced polyamide with a next-generation composite filament and employing the innovative Generative Design technique. In the work, we began by characterizing and optimizing the composite material specifications. Then, the tensile strength and fracture mechanics of standard samples based on printing parameters, applying Taguchi experimental design for optimization were evaluated. Analysis of Variance (ANOVA) was used for factor analysis to fine-tune the process. Using the Generative Design technique, we determined optimal geometries, which were then fabricated through Fused Deposition Modeling (FDM). As a result, the optimization efforts led to significant improvements i.e., tensile strength increased from 103.2 to 116 MPa, and the elasticity modulus from 8386 to 8990 MPa. In practical industrial applications, we achieved a reduction in material weight from 14 to 4 g, lowered production costs from $5.16 to $1.50, and cut production time from 58 to 28 min. This study presents a validated method for developing industrial products with reduced material usage and costs, promoting sustainable production practices.

Coupling Taguchi experimental designs with deep adaptive learning enhanced AI process models for experimental cost savings in manufacturing process development

The Aluminum alloy AA7075 workpiece material is observed under dry finishing turning operation. This work is an investigation reporting promising potential of deep adaptive learning enhanced artificial intelligence process models for L18 (6133) Taguchi orthogonal array experiments and major cost saving potential in machining process optimization. Six different tool inserts are used as categorical parameter along with three continuous operational parameters i.e., depth of cut, feed rate and cutting speed to study the effect of these parameters on workpiece surface roughness and tool life. The data obtained from special L18 (6133) orthogonal array experimental design in dry finishing turning process is used to train AI models. Multi-layer perceptron based artificial neural networks (MLP-ANNs), support vector machines (SVMs) and decision trees are compared for better understanding ability of low resolution experimental design. The AI models can be used with low resolution experimental design to obtain causal relationships between input and output variables. The best performing operational input ranges are identified for output parameters. AI-response surfaces indicate different tool life behavior for alloy based coated tool inserts and non-alloy based coated tool inserts. The AI-Taguchi hybrid modelling and optimization technique helped in achieving 26% of experimental savings (obtaining causal relation with 26% less number of experiments) compared to conventional Taguchi design combined with two screened factors three levels full factorial experimentation.

Piperazine-Based Mixed Solvents for CO2 Capture in Bubble-Column Scrubbers and Regeneration Heat

This work used piperazine (PZ) as a base solvent, blended individually with five amines, which were monoethanolamine (MEA), secondary amines (DIPAs), tertiary amines (TEAs), stereo amines (AMPs), and diethylenetriamine (DETA), to prepare mixed solvents at the desired concentrations as the test solvents. A continuous bubble-column scrubber with one stage (1 s) was first used for the test. Six parameters were selected, including the type of mixed solvent (A), the ratio of mixed solvents (B), the solvent feed rate (C), the gas flow rate (D), the concentration of the mixed solvents (E), and the liquid temperature (F), each one having five levels. Using the Taguchi experimental design, only 25 runs were required. The outcome data, such as the absorption efficiency (EF), the absorption rate (RA), the overall mass-transfer coefficient (KGa), and the absorption factor (φ), could be determined under steady-state conditions. The optimal mixed solvents were found to be A1 (PZ + MEA) and A2 (PZ + DIPA). The parameter importance and optimal conditions for EF, RA, KGa, and ϕ were determined separately; the verification of all optimal conditions was successful. This analysis found that the importance of the parameters was D &gt; C &gt; A &gt; E &gt; B &gt; F, and the gas flow rate (D) was the most important factor. Subsequently, multiple-stage scrubbers were used to capture CO2. Comparing 1 s and 3 s (three-stage scrubber), EF, RA, KGa, and φ increased by 33%, 29%, 22%, and 38%, respectively. The desorption tests for the four optimal scrubbed solutions, including multiple stages, showed that the heat of regeneration for the three scrubbers was 3.57–8.93 GJ/t, in the temperature range of 110–130 °C, while A2 was the best solvent. Finally, the heat regeneration mechanism was also discussed in this work.

Properties of foam glass produced with the use of soot from a cement factory as a foaming agent: A Study Based on Taguchi Design of Experiments

Cellular glass is a lightweight, porous medium with excellent heat transfer resistance that can be used in a variety of industries. This study investigated the use of soot from cement plants as a new foaming agent for producing foam glass. The experiments were designed using the Taguchi Design of Experiments (DOE) method. By applying this approach, instead of creating and testing 27 different groups of samples, only 9 groups were produced. The properties of the remaining 18 sample groups were then predicted based on Taguchi analysis. Soot and silicon carbide were used simultaneously (at weight ratios of 2% and 3%) as foaming agents in the samples. Alumina was also used as a modifier with weight ratios of 4%, and 8%. Mechanical strength, water absorption, density, and thermal resistance were evaluated. The findings indicated a direct correlation between elevated soot content and increased water absorption (open porosity), coupled with a reduction in compressive strength and overall density of the foam glass. Electron microscopy observations revealed a wide range of crystallite morphologies in the resulting foam glass, which results in diverse properties in the material. The developed glass foams exhibit a density spanning from 125 to 700 kg/m3, with compressive strength varying between 1.2 and 6.7 MPa, and thermal conductivity in the range of 0.08–0.5 W/m·K. The samples with 3% soot, 0% alumina, and 3% SiC exhibited exceptional thermal insulation properties. In contrast, the samples containing 1% soot, 8% alumina, and 1% SiC demonstrated the highest compressive strength. Overall, this study found that soot from cement plants is a viable foaming agent for producing foam glass with desirable properties. The use of soot from cement plants can not only reduce the dispersion of pollution in the environment but also produce a wide range of foam glass with different properties at a lower cost.

Optimising the acquisition conditions of high information quality low-field NMR signals based on a cutting-edge approach applying information theory and Taguchi's experimental designs – Virgin olive oil as an application example

BackgroundDeveloping a new spectrometric analytical method based on a fingerprinting approach requires optimization of the experimental stage, particularly with novel instruments like benchtop low-field NMR spectrometers. To ensure high-quality LF-NMR spectra before developing the multivariate model, an experimental design to optimize instrument conditions is essential. However, difficult-to-control factors may be critical for optimization. Taguchi methodology addresses these factors to obtain a system robust to variation. This study uses the Taguchi methodology to optimize instrument settings for acquiring high-quality 1H and 13C LF-NMR signals in a short time from virgin olive oil (VOO). ResultsTwo experimental trials (for 1H and 13C signals, respectively) were carried out and analysed to find an optimal and robust combination of instrument settings against changes in two difficult-to-control factors: ambient temperature and small deviations of the NMR tube volume (700 ± 50 μL). The responses to be optimised, run time and spectral information quality, were analysed separately and jointly, as some factors showed opposite behaviour in the effect on the responses. Multiple response analysis based on suitable desirability functions yielded a combination of factors resulting in desirability values above 0.8 for 1H LF-NMR signals and almost 1.0 for 13C LF-NMR signals.In addition, a novel approach to assess the information quality of an analytical signal was proposed, addressing a major challenge in analytical chemistry. By applying information theory and calculating information entropy, this approach demonstrated its potential for selecting the highest quality (i.e. most informative) analytical signals. SignificanceThe acquisition instrument conditions of LF-NMR were successfully optimised using Taguchi methodology to acquire highly informative 1H and 13C spectra in a minimum run time. The importance lies in the future development of non-targeted analytical applications for VOO quality control. In addition, the innovative use of information entropy to a priori assess the signal quality represents a significant advance and proposes a solution to a long-standing challenge in analytical chemistry.

On the Optimization of Roughness and Corrosion Resistance of Laser Beam Powder Bed Fusion Fabricated Ti–6Al–4V Parts—An Electrochemical Approach

Laser beam powder bed fusion is emerging as a technology for fabricating components made of advanced alloys, such as Ti–6Al–4V. However, it suffers from rough as‐built (AB) surfaces, necessitating postprocessing for desired quality and performance. Electrochemical methods such as electrochemical polishing (ECP) and anodization (AN) are promising postprocessing methods; ECP can effectively smoothen surfaces irrespective of their complexity and hardness, while AN enhances the material's corrosion resistance. However, literature lacks research that discusses combined ECP and AN treatment on surface texture evaluation and corrosion behavior. This work presents a detailed study on the effects of different processing factor levels using a Taguchi design of experiment (DOE) approach and discusses the underlying process mechanisms. The optimized treatment conditions to achieve highest roughness improvement and best corrosion resistance are discussed and the most influential postprocessing factors are revealed and ranked. The treatment that achieved smooth surfaces and high corrosion resistance is ECP at 20 V and 15 °C for 20 min, followed by AN at 15 V for 5 min. This treatment achieves a 72% roughness improvement, providing an arithmetic areal surface roughness of 2.63 μm and a corrosion current density of 0.09 μA cm−2, which is almost similar to the AB part.

Optimization of Docetaxel-Loaded Cholesterol Nanostructured Lipid Carriers for Improving Cancer Treatment Using Taguchi Experimental Design

Optimization of Docetaxel-Loaded Cholesterol Nanostructured Lipid Carriers for Improving Cancer Treatment Using Taguchi Experimental Design

Intelligent Location-Routing for Sustainable Reverse Supply Chain of End-of-Life Vehicles Considering Awareness Cost and Carbon Penalty

This paper presents a comprehensive investigation into optimizing the reverse supply chain for end-of-life vehicles (ELVs) with a focus on sustainability considerations, including awareness cost and carbon penalty. A novel three-objective mathematical model is developed, leveraging fuzzy logic to address the complex nature of the problem. Two multi-objective algorithms, the Grey Wolf Optimizer (GWO) based on the Pareto boundary and the NSGA-II algorithm, are deployed to solve the model. A case study in China is conducted to validate the proposed model, with results compared against the outcomes of the algorithms. Additionally, a sensitivity analysis approach is employed to assess the impact of awareness cost and carbon penalty parameters. Furthermore, the Taguchi experimental design method is utilized to identify the optimal combination of parameter values. The findings reveal that the GWO algorithm surpasses NSGA-II in terms of solution quality and diversity, although NSGA-II demonstrates superior performance in uniformity and computational time. The sensitivity analysis highlights the positive correlation between increased awareness cost and various performance metrics, such as the number of collected vehicles, economic profit, and social profit, while also indicating a reduction in environmental impacts. Conversely, escalating carbon penalties leads to a decrease in the acceptance and processing of vehicles within the supply chain, resulting in diminished chain and social profits, despite the decrease in carbon penalties.

Evaluation of the dielectric, and piezoelectric properties and optimizing the figure of merit of the 0–3 KNN-0.8ZnO/PVDF-HFP piezoelectric composite by the Taguchi method

Piezoelectric ceramic and composite materials are attractive for various applications, but they can be challenging to process. In this research, KNN-0.8ZnO with high density (ρth=95 %), favorable microstructure, and suitable dielectric and piezoelectric properties (K=875, d33=125 pC/N, tanδ=0.01) was first synthesized. Additionally, polyvinylidene fluoride-hexafluoropropylene (PVDF-HFP) copolymer, known for its advantageous piezoelectric and mechanical properties, was selected as the polymer phase. subsequently, the KNN-0.8ZnO/xPVDF-HFP composite samples with a 0–3 connectivity pattern were made with the cold sintering method. The Taguchi design of experiment (DOE) was employed to determine the optimal condition for maximizing the figure of merit (FOM). Furthermore, an analysis of variance (ANOVA) was carried out to evaluate the significance of individual factors on each measured property. Phase identification was performed using X-ray diffraction (XRD) analysis, while the microstructure was examined using scanning electron microscopy. Among the different composite samples fabricated using the L9 orthogonal array (OA) of the Taguchi method, the KNN-0.8ZnO/20PVDF-HFP composite containing 20 wt% polymer phase, that was cold-sintered under a pressure of 400 MPa at 200 ͦC for 2 h, exhibited the highest FOM value of 1.945Pm2/N. This result aligns with the optimal conditions predeicated by the Taguchi DOE method. The compressive strength of the KNN-0.8ZnO/20PVDF-HFP composite was assessed through a compression test, yielding a value of 207 MPa, while the elastic modulus was approximately 3 GPa. The findings of this study demonstrate that the cold sintering method is an effective approach for producing dense piezoelectric composites with favorable electrical and mechanical properties, along with a high FOM for energy harvesting applications.

COMPARATIVE ANALYSIS OF MACHINING AISI 1020 MILD STEEL USING MINERAL OIL BASED AND NEEM SEED OIL BASED CUTTING FLUIDS

Retaining workpiece dimensional accuracy and quality, elongated tool life, minimal surface roughness, minimum tool wear and overall high productivity in metal cutting (machining) operations are areas the cutting fluids plays pivotal role. This study focuses on surface roughness, cutting temperature and tool wear by evaluating their optimal factor effectiveness during turning of AISI 1020 Mild Steel using an environmentally friendly cutting fluid. Serious concern has been raised about the non-biodegradable and non-recyclable of the conventional (mineral based) cutting fluid and this prompted the renewal of research interest in environmentally friendly cutting fluids such as the neem seed oil based cutting fluid. The locally sourced neem seed oil (NSO) was characterized by investigating the physiochemical properties and the fatty acid composition (FAC). Surface roughness, cutting temperature and tool wear were minimized during turning of AISI Mild Steel using coated carbide insert with the evaluation compared with the mineral oil based cutting fluid. Taguchi experimental design was employed during the optimization. The formulated fluid showed 8.35 pH value, 0.896 m 2/s viscosity, good resistance to corrosion, stable and milkfish colouration. The S/N ratio for NBCF and MBCF are 800 CS, 0.4 FR and 0.6 doc; and 800 CS, 0.4 FR and 0.6 DOC respectively with R-sq and R-sq(pred) values as 98.37% and 97.38 under the NBCF and lastly 94.53% and 91.25% under the MBCF for surface roughness respectively. For cutting temperature and tool wear, S/N ratios show A 1B 1C 1 under both NBCF and MBCF. The findings shows that the neem seed oil based cutting fluid outperform the mineral oil-based fluid under the same cutting parameters and this has contributed to the science of machining.

Investigation of wear characteristics of granite dust & coconut shell ash reinforced aluminum metal matrix composite using design of experiment

Recently, one of the most important issue faced by all nations is a waste management. Therefore, it is essential to search for creative solutions to waste reduction, reuse, and recycling. This can be accomplished by adding waste materials to composite materials as a reinforcements. Reusing waste materials enhances the characteristics of existing materials, while also helping the environment by solving the disposal problem. The main aim of this paper is to study the wear characteristics of hybrid aluminum metal matrix composite reinforced with coconut shell ash (CSA) and granite dust. The hybrid composite samples were manufactured using stir casting by reinforcing CSA (ranging from 0 wt% to 12 wt%) and granite dust (maintained at 2 wt%) in Al6061 alloy. SEM and EDAX analysis were performed to investigate the microstructure and elemental composition. The wear characteristics of the hybrid composites were determined via pin-on-disc tests. Finally, the Taguchi design of experiment was performed on the specimen having the best wear characteristics by selecting the L27 orthogonal array and identified the influence of process variables on the wear rate. The results of the pin-on-disc experiment showed that the wear rate decreased with increasing CSA%. The hybrid composite composed of 02 wt% granite dust, & 12 wt% CSA indicates a lower wear rate (56.25%) as compared to the matrix alloy. The Taguchi analysis prooved that the sliding distance has a greater impact on the wear rate than the other parameters. This material can be a superior substitute where high wear resistance is required.

Treatment of pulp and paper mill effluent through combined aerobic and anaerobic suspended fixed-bed bioreactor.

This study explored using ultrafiltration (UF) membranes to treat pulp and paper mill wastewater, implementing a novel Taguchi experimental design to optimize operating conditions for pollutant removal and minimal membrane fouling. Researchers examined four factors: pH, temperature, transmembrane pressure, and volume reduction factor (VRF), each at three levels. Optimal conditions (pH10, 25°C, 6bar, VRF 3) led to a 35% reduction in flux due to fouling and high pollutant rejections: total hardness (83%), sulfate (97%), spectral absorption coefficient (SAC254) (95%), and chemical oxygen demand (COD) (89%). Conductivity had a lower rejection rate of 50%. Advanced imaging techniques like atomic force microscopy (AFM) and scanning electron microscopy (SEM) revealed reduced membrane fouling under these conditions. The Taguchi method effectively identified optimal conditions, significantly improving wastewater treatment efficiency and promoting environmental sustainability in the pulp and paper industry. PRACTITIONER POINTS: This study optimized UF membrane conditions for pulp and paper mill wastewater, reducing fouling and enhancing pollutant removal, offering practical strategies for industrial treatment. AFM and SEM provided key insights into membrane fouling and mitigation, promoting real-time diagnosis and optimization for enhanced treatment efficiency. Prioritizing anaerobic fixed-bed systems in wastewater treatment is beneficial for achieving high COD removal efficiency. Optimizing hydraulic retention time (HRT) in these systems can further improve their overall effectiveness and sustainability.

Manufacturing of hexagonal cross-section thermoplastic matrix composite parts with automatic filament winding system

Thermoplastic filament winding is a flexible manufacturing method typically used in the production of cylindrical composite structures, allowing for in-situ consolidation without the need for a second consolidation step. The objective of this study is to produce non-cylindrical geometries, typically manufactured using thermoset matrix composites according to the literature, using the thermoplastic filament winding process. For this purpose, glass fiber (GF) reinforced polypropylene (PP) prepreg tapes were used to produce hexagonal cross-section thermoplastic composite parts. The critical process parameters; hot-air heater nozzle temperature, compression roller pressure, the linear speed of mandrel rotation, and corner radius of the mandrel, were determined using the Taguchi experimental design method. The interlaminar shear strength (ILSS) and maximum compressive strength (σmax) values were obtained as 211 MPa and 49.40 MPa as maximum, respectively. ANOVA analysis showed that the corner radius had the most significant impact on ILSS, while mandrel rotation speed and temperature were critical for σmax.

Degradation of 2,4-dinitrotoluene from aqueous solutions by three-dimensional electro-Fenton with magnetic activated carbon particle electrodes (GAC/Fe3O4)

Abstract 2,4-Dinitrotoluene (2,4-DNT) is a broadly applied nitroaromatic compound with multiple applications, and its simple production has resulted in its extensive utilization in producing explosives, dyes, and rubber. This substance is hazardous and induces genetic mutations in humans, fish, and microorganisms. Thus, this research was done to assess the effectiveness of the three-dimensional electro-Fenton (3D/EF) process employing magnetic activated carbon particle electrodes (GAC/Fe3O4) in eliminating 2,4-dinitrotoluene from water-based solutions. In this experimental investigation, Fe3O4 nanoparticles were created using the chemical co-precipitation technique. The G/β-PbO2 anode was fabricated by electrochemically depositing PbO2 layers on graphite sheets. G/β-PbO2 and stainless steel were utilized as the anode and cathode, respectively. The structure, particle size, and properties of the GAC/Fe3O4 nanocomposite were analyzed using FESEM, XRD, and EDX. The morphology of the G/β-PbO2 electrode was also examined using SEM. The Taguchi experimental design method was employed to identify the optimal conditions. The outcomes demonstrated that higher reaction time and current density, as well as lower pH and pollutant concentration, resulted in improved 3D/EF efficiency. Accordingly, the optimum values of parmeters were identified to be a concentration of 2,4-DNT = 50 mg/L, pH = 3, electrolysis time = 100 min, and current density = 8 mA/cm2. With these parameters, the degradation efficiency of 2,4-DNT through the examined system was 98.42 %, alongside removal efficiencies of 84.69 % for COD and 79.67 % for TOC. Additionally, the results indicated an increase in the average oxidation state (AOS) (from 1.27 to 1.95) and carbon oxidation state (COS) (from 1.27 to 2.75) in the 3D/EF process, along with a decrease in the COD/TOC ratio (from 1.81 to 1.36), indicating the effectiveness of the 3D/EF system in enhancing the biodegradability of 2,4-DNT. Overall, the combined 3D/EF process with a G/β-PbO2 anode has relatively high efficiency in degrading solutions containing DNT and can be considered a viable treatment option for wastewater containing substances such as 2,4-DNT.

Parametric Investigation of Die-Sinking EDM of Ti6Al4V Using the Hybrid Taguchi-RAMS-RATMI Method

Ti6Al4V is a widely used alloy due to its excellent mechanical qualities and resistance to corrosion, which make it fit for automotive, aerospace, defense, and biomedical sectors. Due to its high strength and limited heat conductivity, it is difficult to machine. Both the workpiece’s and the electrode’s conductivity are important factors that impact the electro-discharge machining (EDM) process. In this case, the machining efficiency is also influenced by the electrode selection. As a result, choosing the right electrode and machining parameters is essential to improving EDM performance on the Ti6Al4V alloy. Research on EDM for Ti6Al4V is limited, with little focus on electrode material selection and shape. The impact of EDM settings on MRR, TWR, and surface roughness is complex, and a comprehensive optimization strategy is needed. Copper electrodes are widely used, but further investigation is needed on EDM’s effects on Ti6Al4V’s surface properties and surface integrity. Addressing these research gaps will improve the understanding and application of EDM for Ti6Al4V, focusing on parameter optimization, surface integrity, and thermal and mechanical effects. By employing copper tools to optimize four crucial EDM process parameters—peak current, duty cycle, discharge current, and pulse-on time—this research aims to increase surface integrity and machining performance. A comprehensive Taguchi experimental design is used to systematically alter the EDM settings. By optimizing parameters using tolerance intervals and response modelling, the recently developed RAMS-RATMI approach improves the dependability of the EDM process and increases machining efficiency. With the optimized EDM settings, there were notable gains in depth of cut enhancement, surface roughness minimization, tool wear rate (TWR) reduction, and material removal rate (MRR). The results of the surface integrity examination showed fewer heat-affected zones, fewer microcracks, and a thinner recast layer. Analysis of variance was used to verify the impact and resilience of the optimized parameters. Superior machining performance, higher surface quality, and increased operational dependability were attained with the Ti6Al4V-optimized EDM process, providing industry practitioners with insightful information and useful recommendations.

Enhancing the performances of self-consolidating composite mortars with Alfa fibers and slag: A combined Taguchi-ANN optimization

Alfa fiber-reinforced self-compacting mortars (SCMs) offer enhanced workability. Thus, the potential of combining natural Alfa fibers and ground granulated blast furnace slag (GBFS) to optimize the rheological and mechanical properties was ascertained. The effect of fibers and GBFS on the properties of SCMs after treatment with linseed oil and NaOH was also evaluated. Partial substitution of cement by slag (10 % and 30 %.) was achieved. Mini cone spreading, V-funnel flow tests as well as compressive and bending tests at 7 days and 28 days were performed on the prepared mixtures. For optimization and predictive purposes, both Taguchi optimization and Artificial Neural Network modeling were employed. Our results indicated that, according to Taguchi experimental design, the use of 1 % fiber in the initial mixture achieved a good distribution within the paste and improved flexural strength. In addition, the treatment of fibers with NaOH actually improved the structure and bonding surface. Fiber content and GBFS replacements achieved the desired rheological and mechanical characteristics. Prediction of both compressive and flexural strengths was successfully achieved by an accurate application of machine a learning algorithm based on six inputs, one hidden layer and four outputs. The combined ANN-Taguchi approach provided accurate predictions of SCM performances and identified a robust mix-design that was less prone to fluctuations in the initial material properties. Alfa fibers and GBFS promoted both fresh and hardened properties. This study demonstrated the effectiveness ML and statistical optimization in developing high-performance, sustainable-SCMs with superior workability and strengths, making them ideal for various construction applications.