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Automated high-density storage systems (AHDSS) have attracted widespread attention in recent years owing to their advantages of high throughput and space utilisation. However, owing to the characteristics of large-scale, multi-disturbance, and short-period task scenarios, a system is required to make instant and efficient decisions. To this end, this paper proposes a data-driven real-time decision-making method to solve the real-time equipment scheduling and dynamic location assignment problem in AHDSS. The proposed method comprises two phases: decision scheme learning and real-time decision-making. The operation state attribute features of the AHDSS were constructed to generate training data for equipment scheduling and location assignment scheme learning. Thereafter, a hierarchical learning and decision-making mechanism based on the deep belief network (DBN) is proposed. The integrated learning of better scheduling solutions was realised by establishing three-stage models of lift selection, shuttle selection, and location priority. Additionally, the Taguchi method was adopted to determine the best performance parameters for DBNs at different learning stages. Compared with other well-known machine learning algorithms, DBNs have a higher learning accuracy. Finally, a real-world AHDSS problem is studied, and the results demonstrate that the proposed approach outperforms existing dispatching rules. [ABSTRACT FROM AUTHOR]

Water‐based nanolubricants are playing increasingly important roles in hot steel rolling over the past decade regarding environmental protection, energy saving, and product quality improvement. The contact friction between the work roll and the workpiece under water‐based nanolubrication, however, has been scarcely investigated. In this study, water‐based lubricants containing 0–4.0 wt% TiO2 nanoparticles are employed in hot rolling of a mild steel under different rolling conditions. The Taguchi method is used for the orthogonal design of the hot‐rolling tests to sequence the key factors that affect the rolling force in terms of importance. The as‐synthesized water‐based nanolubricants indicate excellent dispersion stability after standing for 24 h, which can be readily restored to the original state via manual shaking. The coefficient of friction (COF) during the steady‐state hot steel rolling is inversely calculated using a flow stress model developed from hot compression testing. A novel COF model for hot rolling of the steel is thus proposed through multiple linear regression. It is found that the result of linear regression agreed well with that of inverse calculation, indicating that the proposed COF model is applicable. Finally, the lubrication mechanism is examined through a boundary lubrication regime determined from a modified lubricant film thickness model. [ABSTRACT FROM AUTHOR]

AbstractThe current investigation examines the wear performance of High-Velocity Oxygen Fuel coated Colmonoy-88 coating on SS 304. An L9 orthogonal array design based on the Taguchi fractional factorial method was used to create the erosive wear tests. The impact of three parameters, such as impact velocity (100, 120, and 140 m/s), angle of impact (30°, 60°, and 90°), and test duration (10, 15 and 20 min), on wear performance was investigated by analysis of variance. Results show that the impact angle is the most vital factor for mass loss in both SS 304 and Colmonoy-88, followed by impact velocity and time duration. It was revealed that the maximum wear takes place at 30° impact angle in both specimens. The outcomes of the XRD and EDS analysis show that the Colmonoy-88 has a high chromium content, which provides it with exceptional erosion resistance. The Colmonoy-88 wear mechanism involved inter-splat micro-cutting, lips, crack initiations, and craters caused by fly ash particles at varying impact angles. [ABSTRACT FROM AUTHOR]

The present work involves in a novel approach of studying the material characteristics of AZ31 alloy by varying the cooling method in powder metallurgy and particle size of the matrix material. It also has a novel approach of reinforcing AZ31 alloy with quarry dust and providing self oxide coating to the material in a distinct way for corrosion resistance. The alloy is prepared through powder metallurgy with a pressure of 675 MPa, sintered at 540 ºC, with one hour of soaking. The Scanning Electron Microscopy images are taken to analyse the microstructure. Wear and corrosion studies are done to analyse the effect of parameters. Optimisation for wear is also done with Taguchi method. The AZ31 samples reinforced 5, 10 and 15% of quarry dust are prepared and studied for mechanical properties. The material prepared using 75–150 micron range, cooled in still air cooling and with 5% reinforcement has shown higher values of compressive strength and microhardness. The alloy provided with self-oxide coating has shown higher resistance to corrosion than that of uncoated alloy and the composite. [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]

The rapid consumption of fossil fuels has led to calls to switch from non-renewable to renewable energy sources. Microbial fuel cells are a promising technology that simultaneously treats wastewater and produces power. This study used the Taguchi Experimental method to optimize anode thickness and pH to obtain the maximum power density of an air-cathode microbial fuel cell (ACMFC). The graphene-sponge (G-S) anode thickness and chamber pH were selected as operating parameters, with their corresponding levels. The L9 orthogonal array was chosen for the experimental design. According to the Taguchi Method, the optimum G-S anode thickness and chamber pH were determined to be 1.0 cm and 8.0, respectively. A confirmatory run was performed under these optimum conditions, and the maximum power density observed was 707.75 mW·m-3. Analysis of variance (ANOVA) was conducted to identify the percentage contributions of the operating parameters to the process, which were found to be 30.66% for pH and 69.34% for anode thickness. [ABSTRACT FROM AUTHOR]

Nowadays, computational and computing tools are widely used in prediction applications. Neural computing is a modern and emerging technique to predict data efficiently and precisely. In this context, erosion investigation of Mo2C–WC10Co4Cr high-velocity oxy-fuel (HVOF) deposited on AISI 316L was carried out in the present work by implementing a neural computing and Taguchi's method. This research paper focuses on neural network (NN) technique for the prediction of erosion in Mo2C–WC10Co4Cr HVOF coating. The WC10Co4Cr powder was composed of 3% (by weight) of molybdenum carbide, each with a concentration of 3 wt.%. The input parameters used for designing the NN model were erodent properties (bulk density, circularity factor, average particle size, and slurry concentration), material properties (hardness and porosity of bare/coated), and process parameters (speed and time). A set of experiments was optimised by using Taguchi's method (L16 2 × 5 array). Results indicated that the overall accuracy of Pearson coefficient (R) was found as 0.99582 with experimental data. However, R = 1 was found for testing results. [ABSTRACT FROM AUTHOR]

Dry sliding wear tests on Cu-Al-Mn Shape Memory Alloys (SMAs) were performed in this study. The alloy was synthesised with the amount of manganese content varied as 5, 7, and 9 wt.% and the amount of aluminium was kept constant at 10.5 wt.% with the remaining copper. Dry sliding wear tests were carried out at different conditions of sliding speeds, sliding distances, and various load conditions. Experiments were carried out using Taguchi's technique to obtain an experimental design. The data were analysed using an L27 orthogonal array. The wear rate (WR) and coefficient of friction (COF) were evaluated using the 'smaller is better' method approach. The main parameters affecting WR and COF were determined using ANOVA. The effects of applied load, sliding speed, sliding distance, and material on WR and COF are determined. The optimum combinations of parameters were set to achieve the lowest wear rate and highest COF. Finally, confirmation tests were conducted to ensure that the experimental results were accurate. After the wear test, the sample texture was observed and analysed using a Scanning Electron Microscope (SEM). [ABSTRACT FROM AUTHOR]

This paper attempts to optimise the single screw extrusion (SSE) process parameters for extruding Acrylonitrile-butadiene-styrene (ABS) and Polycarbonate (PC) blend filament, having improved tensile strength and melt flow rate. The melt flow and mechanical properties of ABS-PC blend filament are highly reliant on the SSE process parameters. Thus, optimising the process parameters to fabricate the blend filaments with high performance has become essential. Grey relational analysis has been integrated with the Taguchi method to optimise the SSE process parameters by evaluating the grey relational grades in terms of the performance index. Experimentation has been carried out according to Taguchi's L9 orthogonal array (OA), which has been designed considering three SSE process parameters, i.e. screw rotation, blend composition and chamber temperature. The co-continuous structure and compatibility between the phases of the blend obtained at ABS:PC 50:50 by wt%. Micrographs and thermographs support the results. The tensile strength of the 3D printed ABS:PC 50:50 by wt.% composite specimen has improved by 38.02% as compared to virgin ABS. [ABSTRACT FROM AUTHOR]

Highlights This study investigates the fatigue characteristics of 3D‐printed composites made from polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS), reinforced with carbon fiber. It involves designing and building a rotating bending fatigue machine, creating standard specimens via FDM, and applying DOE using Taguchi method. Standard specimens are subjected to cyclic loading with a print orientation of 0°, 45°/−45°, and 90°, motor speed and load. Materials such as PLA, ABS, PLA‐CF, and ABS‐CF are tested by maintaining a consistent layer thickness of 0.16 mm and 99.99% infill density while varying stress levels. PLA‐CF outperforms PLA, ABS, and ABS‐CF in fatigue life, with 0° print orientation exhibiting superior fatigue strength. Statistical analysis underscores the significance of print direction, material composition, and stress level. Additionally, the study aims to construct S‐N curves for 3D‐printed PLA/ABS composites with carbon fiber reinforcement, advancing our understanding of mechanical properties and print parameter optimization for enhanced fatigue performance in 3D‐printed composites. Fatigue characteristics of 3D printed composites made from PLA and ABS, reinforced with carbon fiber investigated. Four polymer composites were used: PLA, ABS, PLA‐CF (short carbon fiber), and ABS‐CF (short carbon fiber). The research focused on the impact of 3D print orientation on fatigue properties, considering print angles of 0°, 45°/−45°, and 90°, alongside adjustable factor like motor speed and load. With a consistent layer thickness of 0.16 mm and 99.99% infill density, the fatigue tests were conducted under stress‐controlled conditions at varying stress levels. Results demonstrate that PLA‐CF specimens exhibit superior fatigue lifetimes compared to PLA, ABS, and ABS‐CF samples. [ABSTRACT FROM AUTHOR]

Permanent magnet-assisted synchronous reluctance motor (PMSRM) has been widely used in many fields due to their advantages of less permanent magnets and low cost. However, the permanent magnet torque and reluctance torque of the traditional PMSRM reach their maximum values at different current angles. Therefore, the utilization ratio of the total torque to each torque component is low, which leads to the low power density of the PMSRM. To solve this problem, a new rotor structure suitable for PMSRM is proposed in this paper. The rotor can improve the total torque by increasing the maximum value of permanent magnet torque and the utilization rate of total torque to each torque component. Thus, the power density of the motor is effectively improved. In order to realize the matching design of each parameter in the proposed rotor structure, the Taguchi method is used to optimize the design, and the influence of each optimization variable on torque and torque ripple is analyzed. The finite element simulation analysis method is used to establish the electromagnetic simulation model of the traditional structure, the new structure proposed and the optimized structure of the new structure by Maxwell simulation software. The simulation results show that the proposed new rotor structure not only effectively improves the torque density, but also effectively reduces the torque ripple. [ABSTRACT FROM AUTHOR]

In mass production, injection molding plays a vital role in manufacturing various parts with complex settings. As perfluoroalkoxy alkane (PFA) injection‐molded products are widely used in immersion system, dimensional quality needs more attention. However, there is limited research on the dimension defects of PFA injection‐molded products. This study focused on the influence of mold design and process parameters on PFA part shrinkage, using mold flow simulation and orthogonal testing separately. Several gate locations and sizes were simulated to minimize shrinkage in mold design. Displacements varied with gate locations, and shrinkage decreased with larger gate sizes. The Taguchi method analyzed process parameters' impact on shrinkage. The results indicated that the injection rate had the most significant effect on the shrinkage of tube length, while melt temperature, holding pressure, and screw speed affected the shrinkage of tubes' outside diameter. Different flow directions exhibited variance in shrinkage. Using max–min normalization, the two shrinkage values reached 0.00972, whereas the smallest value obtained in the orthogonal experiment was 0.1545 in run 3. Thus, optimizing mold design and process parameters were two effective methods to reduce shrinkage. This study reduced shrinkage and improved the quality of PFA injection molding parts for semiconductor systems. [ABSTRACT FROM AUTHOR]

In modern manufacturing, optimization algorithms have become a key tool for improving the efficiency and quality of machining technology. As computing technology advances and artificial intelligence evolves, these algorithms are assuming an increasingly vital role in the parameter optimization of machining processes. Currently, the development of the response surface method, genetic algorithm, Taguchi method, and particle swarm optimization algorithm is relatively mature, and their applications in process parameter optimization are quite extensive. They are increasingly used as optimization objectives for surface roughness, subsurface damage, cutting forces, and mechanical properties, both for machining and special machining. This article provides a systematic review of the application and developmental trends of optimization algorithms within the realm of practical engineering production. It delves into the classification, definition, and current state of research concerning process parameter optimization algorithms in engineering manufacturing processes, both domestically and internationally. Furthermore, it offers a detailed exploration of the specific applications of these optimization algorithms in real-world scenarios. The evolution of optimization algorithms is geared towards bolstering the competitiveness of the future manufacturing industry and fostering the advancement of manufacturing technology towards greater efficiency, sustainability, and customization. [ABSTRACT FROM AUTHOR]

The present study aimed to use geopolymer materials synthesized from different fly ashes, which are promising for the adsorption of copper ions from aqueous solutions. The characterization of fly ashes and prepared adsorbents was performed by energy-dispersive X-ray spectroscopy (EDS) analysis, Brunauer–Emmett–Teller (BET) surface area analysis, and Scanning Electron Microscopy (SEM). Taguchi and ANOVA methods were used to predict the effect of different working parameters on copper ion removal by prepared geopolymers. Based on data obtained by the Taguchi method, it was found that the factor most influencing the adsorption process is the type of adsorbent used, followed by the solution pH, the reaction time, the adsorbent dose, and the initial copper ion concentration. The ANOVA results agree with the Taguchi method. The optimal conditions of the adsorption process were: fly ash C modified by direct activation with 2 M NaOH, at 70 °C for 4 h, solution pH of 5, initial pollutant concentration of 300 mg/L, 40 g/L adsorbent dose, and 120 min of reaction time. Copper ion removal efficiency was determined experimentally under optimal conditions, achieving a value of 99.71%. [ABSTRACT FROM AUTHOR]

The rapid development of new energy vehicles demands significant improvements in connector structures and performance standards. Wire harness connectors, crucial for linking various electrical components, face challenges due to their small size and thin-walled structure, which can lead to dimensional shrinkage and warping during injection molding. To address these issues, this study optimizes the injection molding process by fine-tuning parameters such as melt temperature, mold temperature, injection time, holding pressure/time, and cooling time. By integrating the Taguchi method with grey relational analysis, the study enhances the molding process for thin-walled composite connectors. This combined approach provides a comprehensive framework for optimizing multiple quality objectives and improving the overall performance of injection-molded composite components. [ABSTRACT FROM AUTHOR]

Lipomyces maratuensis InaCC Y720 is a potential novel oleaginous yeast. Media-based production optimization has never been carried out using this strain. This study aims to define an optimized medium from 12 medium component factors, where the Taguchi method is used for screening significant factors of medium and the response surface methodology (RSM) is used to optimize the concentration of significant factors. According to Taguchi, glucose, yeast extract, and magnesium sulfate (MgSO4) have a significant influence on lipid accumulation, with their concentrations maintained at optimal levels through RSM optimization. Conversely, potassium dihydrogen phosphate, sodium hydrogen phosphate, and calcium chloride inhibit lipid accumulation, and copper(II) sulfate has the least influence, categorizing them as eliminated factors. The RSM-optimized medium increased lipid content by 3.6-fold compared to the initial medium. Glucose and yeast extract showed a positive correlation with lipid accumulation, suggesting potential for further optimization, while the optimum concentration for MgSO4 was 0.15 g/L. This study is intended to serve as a reference for increasing lipid accumulation by L. maratuensis InaCC Y720. [ABSTRACT FROM AUTHOR]

Fused Filament Fabrication (FDM) has emerged as a prominent and innovative manufacturing technique, facilitating the creation of intricate, lightweight components at reduced time and cost. Despite its advantages, the productivity and mechanical performance of 3D-printed parts remain challenging areas. Hence, there is a growing interest in investigating the interplay between FDM build time and mechanical properties. Structural parameters such as layer thickness (Lt), raster angle (Ia), and air gap distance (Ifd) can exhibit conflicting effects on productivity and mechanical properties. This study employs GRA and VIKOR techniques for the multi-criteria selection of 3D printing, aiming to optimize both printing time and specific flexural properties of PLA/copper composite beams constructed in the edge direction. We compare the parameters selected by both methods and evaluate their impact on the responses. The behaviors of the two models differ: GRA optimizes two responses the specific stiffness ans specific strength, while VIKOR is more effective for minimising printing time. Both models select the lower raster angle of 0° as optimuim. Lt significantly influences printing time, being the primary parameter in the VIKOR method, whereas Ifd primarily contributes to mechanical properties. [ABSTRACT FROM AUTHOR]

This research presents a comprehensive comparative analysis of optimization techniques for achieving the optimal design of cellular beams. The incorporation of gaps within cellular beams reduces the weight of the beam and increases section height, resulting in the production of lighter and stronger sections. The Taguchi method is employed to fine-tune the parameters of the Grey Wolf Optimizer, enabling the achievement of a robust design. The performance of each algorithm is evaluated through three design examples, facilitating comprehensive comparisons among the seven algorithms. Moreover, the study encompasses the modeling and analysis of optimally designed cellular beams using finite element software. [ABSTRACT FROM AUTHOR]

With increasing wafer sizes and diversifying die patterns, automated optical inspection (AOI) is progressively replacing traditional visual inspection (VI) for wafer defect detection. Yet, the defect classification efficacy of current AOI systems in our case company is not optimal. This limitation is due to the algorithms' reliance on expertly designed features, reducing adaptability across various product models. Additionally, the limited time available for operators to annotate defect samples restricts learning potential. Our study introduces a novel hybrid self-training algorithm, leveraging semi-supervised learning that integrates pseudo-labeling, noisy student, curriculum labeling, and the Taguchi method. This approach enables classifiers to autonomously integrate information from unlabeled data, bypassing the need for feature extraction, even with scarcely labeled data. Our experiments on a small-scale set show that with 25% and 50% labeled data, the method achieves over 92% accuracy. Remarkably, with only 10% labeled data, our hybrid method surpasses the supervised DenseNet classifier by over 20%, achieving more than 82% accuracy. On a large-scale set, the hybrid method consistently outperforms other approaches, achieving up to 88.75%, 86.31%, and 83.61% accuracy with 50%, 25%, and 10% labeled data. Further experiments confirm our method's consistent superiority, highlighting its potential for high classification accuracy in limited-data scenarios. [ABSTRACT FROM AUTHOR]

This study investigates the influence of the main process parameters of injection molding(mold temperature, melt temperature, and injection rate) on the appearance of defects of flake-pigmented metallic polymer parts. To understand the influence of process parameters, an appearance defects index (ADI) is proposed to quantify the appearance defects. In this process, we propose a criterion for judging the appearance of defects based on the results of fiber orientation and tensor distribution analyses of the skin layer, which is then verified analytically by simulating experiments from the literature. Using the Taguchi experimental method, we designed an L 25 orthogonal array to systematically evaluate the influence of process parameters. For each experimental condition, the signal-to-noise ratio (S/N ratio) was calculated to determine the optimal level of each factor and its influence on the appearance of defects. According to the results, mold temperature has the greatest influence on the appearance of defects, with an influence of 48.7%, followed by injection rate with an influence of 40.8%, and melt temperature with an influence of 10.5%. The optimal process parameters were found to be a mold temperature of 40 °C, a melt temperature of 250 °C, and an injection rate of 10 cm3/s, which resulted in a 12.6% improvement in the Appearance defects index (ADI) compared to the standard injection molding condition of ABS materials. This study confirmed that it is possible to improve the appearance of defects by adjusting the process parameters of injection molding. [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]

The powder metallurgy process of manufacturing the motor core and inductor core using SMC greatly changes formability depending on the process variables. Therefore, this study explored the optimal process conditions of the powder metallurgy of the SMC stator core using Fe-6.5 wt.%Si by applying the Taguchi method, and selected deviations between the maximum and minimum relative densities as characteristic values; selected the formation pressure, molding temperature, and heating time as control factors; and derived the process conditions with the maximum SNR. As a result, the molding pressure was 120 MPa, the molding temperature was 500 °C, and the heating time was 120 s, and the material properties of the electrical properties' core loss, saturation flux density, and bulk conductivity were measured and analyzed. After that, a prototype was produced, the analysis was verified, the mechanical properties were verified by performing density and SEM analysis at 15, 9, and 3 mm points based on the press vertical direction, and a motor was manufactured to verify the electrical properties. [ABSTRACT FROM AUTHOR]

Hot embossing is a manufacturing technique used to create microchannels on polymer substrates. In recent years, microchannel fabrication technology based on hot embossing has attracted considerable attention due to its convenience and low cost. A new evaluation method of microchannels, as well as an approach to obtaining optimal hot embossing conditions based on the Taguchi method, is proposed in this paper to fabricate precise microchannels for a flexible proton-exchange membrane fuel cell (PEMFC). Our self-made hot embossing system can be used to fabricate assorted types of micro-channel structures on polymer substrates according to various applications, whose bottom width, top width, height and cross-sectional area vary in the aims of different situations. In order to obtain a high effective filling ratio, a new evaluation method is presented based on the four parameters of channel structures, and the Taguchi method is utilized to arrange three main factors (temperature, force and time) affecting the hot embossing in orthogonal arrays, quickly finding the optimal condition for the embossing process. The evaluation method for microchannels proposed in this paper, compared to traditional evaluation methods, incorporates the area factor, providing a more comprehensive assessment of the fabrication completeness of the microchannels. Additionally, it allows for the quick and simple identification of optimal conditions. The experimental results indicate that after determining the optimal embossing temperature, pressure and time using the Taguchi method, the effective filling rate remains above 95%, thereby enhancing the power density. Through variance analysis, it was found that temperature is the most significant factor affecting the hot embossing of microchannels. The high filling rate makes the process suitable for PEMFCs. The results demonstrate that under optimized process conditions, a self-made hot embossing system can effectively fabricate columnar structure microchannels for PEMFCs. [ABSTRACT FROM AUTHOR]

This study uses an infrared cutting laser system to dice GaAs wafers. The Taguchi method determines the laser wafer dicing parameters [laser power (W), depth of focus (μm), and platform speed (m/s)] in relation to the dicing yield and single-grain compressive strength. An orthogonal array (L9 33), a signal-to-noise ratio, and an analysis of variance are employed to study the effects of these parameters. The result shows that the laser wafer dicing yield ranges from 85.53% to 95.20%, with laser power accounting for 86.08% of the total variation, making it the most significant factor. Additionally, the wafer dicing yield is positively correlated with grain compressive strength. Grain defects and corner chipping produced during the cutting process will reduce the compressive strength of the grains. Under the optimized laser wafer cutting conditions, the dicing yield and grain compressive strength reached 95.87% and 331.93 N/mm2, respectively. [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]

Copyright of Journal of Drainage & Irrigation Machinery Engineering / Paiguan Jixie Gongcheng Xuebao is the property of Editorial Department of Drainage & Irrigation Machinery Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The current study explores the effectiveness of the ECM process when machining newly developed high entropy alloy (HEA)-reinforced magnesium composites. To evaluate the machinability, the study focuses on two key output constraints: surface roughness (Ra) and material removal rate (MRR). Experimental trials involve adjusting variables such as feed rate (FR), current, Electrolyte concentration (EC), & voltage in which experiment design is done through Taguchi method. Results highlights voltage as the most important input parameter governing Ra, followed by current. Similarly, voltage emerges as the primary influencer for MRR, with current being the second most influential. Furthermore, artificial neural networks (ANN) yielded predictions closely aligns with the experimental data. The optimal parameter set identified through CRITIC-WASPAS method included 5 Wt.% HEA, 15 V Voltage, 2 Amps current, 0.3 mm/min feed, and 25 g/lit electrolyte concentrations, resulting in a surface finish of 3.47 µm and a production rate of 0.039 mg/min. [ABSTRACT FROM AUTHOR]

The optimization of performance parameters, in particular the yield of the synthesis reaction of β‐enaminones in demineralized water, is crucial to improve their efficiency and accuracy. In this report, we investigate the optimization of the synthesis of β‐ketoenamines in deionized water by controlling several parameters such as reaction time, temperature, amine equivalent, acid percentage, and stirring rate. An orthogonal L16 (45) network was created using Taguchi's approach, allowing for the best possible parameters. To forecast the contribution of each parameter, analysis of variance (ANOVA) techniques are also used. Multiple linear and nonlinear regression (MLR, MNLR) and multilayer perception artificial neural network (MLP‐ANN) predictive models were developed. Analysis of the results led to optimized design parameters, with time = 6 h, temperature = 25°C, amine equivalent = 1.5, acid percentage = 20%, and stirring rate = 1000 rpm, leading to a maximum yield of 63%. ANOVA analysis revealed that temperature, stirring rate, acid percentage, and time are the parameters with the greatest influence. The least sensitive parameter is the amine equivalent. The two main interactions are temperature * acid % and amine equivalent * rpm. The MLP‐ANN predictions are in good agreement with the experimental values, resulting in a higher R2 compared to the quadratic regression model and the MLR model. By using molecular docking studies, the produced compounds' biological activity was investigated. Some of the synthesized compounds appear to be interesting and could be used for therapeutic applications. The results of this study give us insight into the gentle, cost‐effective, and biologically active synthesis of β‐enaminones in deionized water. [ABSTRACT FROM AUTHOR]

This experimental research aims to produce and study the properties of MoSi 2 reinforced with CNT composites using the SPS sintering method. First and before any laboratory operations, using the Minitab 14 software, experimental samples were designed under L16 arrays. Four levels were set for defining parameters, such as the amount of reinforcing phase (CNT), sintering temperature (°C), and holding time (T). XRD, FESEM, density, micro-hardness, bending strength, and fracture toughness tests were used in the study for in-depth investigations. According to the signal-to-noise analysis, the parameter with the greatest influence is the reinforcement rate. Based on the obtained results, the composite with 5 wt% of carbon nanotubes, a sintering temperature of 1300 °C, and a holding time of 10 min was found to have the highest results. [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]

Frequency encoding chipless Radio Frequency Identification (RFID) tags have been frequently using the radar cross section (RCS) parameter to determine the resonant frequencies corresponding to the encoded information. Recent advancements in chipless RFID design have focused on the generation of multiple frequencies without considering the frequency position and signal amplitude. This article proposes a novel method for chipless RFID tag design, in which the RCS response can be located at an exact position, corresponding to the desired encoding signal spectrum. To achieve this, the empirical Taguchi method (TM), in combination with particle swarm optimization (PSO), is used to automatically search for optimal design parameters for chipless RFID tags with a fast response time, to comply with the frequency encoding requirements in the presence of the mutual coupling effect. The proposed design method is validated using I-slotted chipless tag structures that are fabricated and measured with different sets of resonant frequencies. [ABSTRACT FROM AUTHOR]

This paper highlights the surface roughness optimization of a specific material, Al 3003, which has been subjected to the non-equal channel angular pressing (NECAP) process. Considering spindle speed, feed rate, and depth of cut as input variables and surface roughness as an output variable, experiments have been conducted based on the L27 orthogonal array of the Taguchi method. Four prediction models, namely exponential and response surface methodology (RSM) as mathematical models, and artificial neural networks (ANNs) prediction models with different training algorithms (Bayesian Regularization (BR) and Levenberg–Marquardt (LM)), are proposed. Applying effectiveness and performance criteria, the prediction accuracy of the exponential model (90.35%), RSM (93.07%), BR (97.83%), and LM (97.54%) shows that all proposed prediction models are efficient enough. The ANN model trained with BR is found to be the best fit for predicting surface roughness. In order to optimize surface roughness, a newly introduced optimization method called the Intelligible-in-time Logics Algorithm (ILA) is employed. High spindle speed (1000rev/min), low feed rate (100mm/min) and depth of cut (0.5mm) have been the optimum cutting parameter combinations to obtain minimum surface roughness (0.4956μm). The results have been verified by confirmation tests and Particle Swarm Optimization (PSO) method. ILA and PSO predict the same optimum parameter combinations and minimum surface roughness, while ILA performs optimization in less time (114.4s), about 3.5 times faster than PSO. The paper’s findings strongly advocate the application of ILA in machining data optimization. [ABSTRACT FROM AUTHOR]

The research focuses on optimising the mix design of ultra high-performance geopolymer mortar by employing the Taguchi method’s orthogonal array parameters through a systematic experimental approach. Utilising an L9 orthogonal array, the investigation was structured into two phases, each examining a distinct set of variables across three levels to ascertain their impact on compressive strength. The optimal mix was characterised by a water to binder ratio of 0.28, a fibre volume of 3%, a silicon carbide to binder ratio of 0, and a superplasticizer to binder ratio of 2%. This mix achieved 126 MPa of compressive strength. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Basalt fiber (BF)‐reinforced thermoplastic polymers (TPs) show great potential by leveraging their recyclability. Sizing agents are crucial in optimizing BF quality and aiding polymer impregnation during production. However, the absence of established guidelines for sizing agents tailored to thermoplastic BFs persists. This study investigates the effects of sizing agent ingredients on the mechanical and surface properties of BFs under industrial conditions. The Taguchi method was used to formulate nine BF sizing agents, predominantly incorporating polypropylene (PP) emulsion, epoxy or polyurethane emulsion, silane coupling agents (SCAs), and additives. Our investigation extends to evaluating the tensile strength, surface roughness, and wetting characteristics of individual BFs. Results indicate that a heightened PP concentration enhances BF adhesion to TPs but concurrently reduces BF tensile strength. Furthermore, using SCA, specifically dodecyltrimethoxysilane, leads to a remarkable enhancement of approximately 20% in BF tensile strength and an impressive 40% in BF adhesion to TPs. This study unravels sizing agent intricacies, illuminating their nuanced interplay with the work of adhesion rooted in fiber and polymer surface energy. Our work offers innovative solutions to optimize BF‐reinforced thermoplastic polymers. Highlights: Investigating thermoplastic sizing agent formulations for basalt fibers (BFs)Guiding formulation of BF sizing agents with the Taguchi Method.Predicting contact angles between BFs and commonly used thermoplastic polymers.PP emulsions favor BF‐thermoplastic polymer adhesion but not BF tensile strength. [ABSTRACT FROM AUTHOR]

In the processes of nanomaterial synthesis and characterization, it is important to explore and understand the relationships between variables and levels of processes by introducing experimental design methods and statistical approaches. The main goal of this work is to improve the quality of the graphene oxide (GO) that is made by using the TOPSIS-Based Taguchi Method and the L9(33) experimental design. Various parameters were chosen for experimentation, including samples of graphite with varying levels of purity (85%, 99%, and 99.99%). Prior to initiating the reaction, the graphite underwent pre-application, which involved diverse treatments such as no pre-processing, pre-heating at 200 °C, and ultrasonication. Additionally, different types of auxiliary oxidants (NaNO3, H3PO4, and Na2B4O710H2O) were employed. Raman spectroscopy was used to measure the peak intensity ratio (D/G) of the D peak and the G peak. X-ray diffraction (XRD) was employed to determine the crystal size (CS-nm). The surface area (SA-m2/g) was measured using the BET method. The average particle size (PS-nm) and the Zeta potential (ZP-mv) were determined using a Zeta-Sizer. The atomic ratio of carbon to oxygen (C/O) was also studied using scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM+EDX) to get a better understanding of graphene oxide (GO). The quality criteria's findings were assessed for each experiment using the TOPSIS-Based Taguchi Method, and the optimum circumstances were identified. The recovery rates for D/G, C/O, ZP, SA, PS, and CS were computed as 15.88%, 55.55%, 19.23%, -63.23%, -82.77%, and 20.79%, respectively. The utilization of low-purity graphite and boron compounds in the Hummers method yielded a favorable outcome in the synthesis of graphene oxide. When evaluating the experiment from an economic and environmentally conscious perspective, the results are quite impressive. [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]

In today's wood industry, research is being conducted to increase material strength, ensure long-term use, and increase its hardness against many harmful external factors. With the studies on the protection of wood, new protection materials and methods are introduced. In this study, wood was etched with solid sodium bicarbonate (NaHCO3) and 1, 2, and 3 bars of air pressure after treatment with NaHCO3 solution and drying. The change in hardness values of impregnated and surface-treated (paint, varnish) chestnut wood after artificial aging was examined. Etching, impregnation, and surface treatment factors were optimized using the Taguchi design of experiments (DoE) after artificial aging for 3, 6, and 9 months. L16 orthogonal array was used to determine the optimum conditions for determining hardness values and their percentage changes. The results showed that the abrasive factor prevails over the effect of surface treatments. It has been understood that the most effective factor in the hardness value changes during the artificial aging period (3-6-9 months) is abrasion, and the factor with the least effect is the surface parameter. The percentage accuracy of the model used in estimating the wear factor average R² across all dependent variables was 95%. [ABSTRACT FROM AUTHOR]

This research investigates the impact of dry machining AA4015/B4C MMCs (metal matrix composites) utilizing an uncoated B4C insert on Flank wear (VBc) and surface roughness (Ra). This work attempts to close the knowledge gap on the effects of cutting parameters (feed, depth of cut, and speed) on tool wear and surface quality in machining technology. The primary rationale lies in optimizing machining processes for MMCs, known for their challenging machinability due to their tough metallic matrix and hard ceramic reinforcement. The study’s significance is underscored by the exploration of optimal processing parameters to minimize Flank wear and improve surface roughness, crucial factors influencing component quality and lifespan. Specifically, the research identifies v1-f1-d3 (VBc) and v3-f1-d3 (Ra) as the best process parameter combinations, significantly reducing both VBc and Ra. The obtained mathematical models for VBc and Ra provide statistically significant insights into the relationships between cutting variables and performance characteristics. The employment of Taguchi’s L9 orthogonal array proves invaluable in achieving these optimized process parameters efficiently. The Taguchi method’s advantage lies in its ability to systematically explore numerous variables and their interactions with minimal experiments. By reducing the number of trials required, this methodology streamlines the optimization process, saving time, resources, and costs while delivering enhanced machining performance for MMCs. This research, through its systematic approach and emphasis on optimized parameters, contributes to the advancement of machining techniques for MMCs, holding implications for various industrial applications demanding high-performance materials. [ABSTRACT FROM AUTHOR]

The incorporation of supplementary cementitious materials (SCMs) into cementitious materials can be used to offset the overall carbon footprint of cement in addition to improving performance and promoting circular economy. Synthesized silicomanganese fume (SiMnF), silica fume (SF), and ordinary portland cement (OPC) based binary and ternary cementitious mortar specimens were designed and optimized using the Taguchi method. Four factors with three levels each were investigated—SiMnF content of 0%–40% and SF content of 0%–10% (by mass) of the total cementitious, sand-to-binder of 1.5–2.5, and water-to-binder ratio of 0.35–0.45. Based on the orthogonal array proposed by the Taguchi method, nine mortar mixes were batched and their flow after mixing and compressive strength at 3, 7, and 28 days of casting were measured. The strength data were statistically analyzed using ANOVA to investigate the effects of the chosen experimental variables. It was observed that the strength is considerably reduced from the addition of SiMnF, but the reduction is marginal from increasing the sand-to-binder ratio. The addition of 5% SF increased the strength. A restricted analysis indicated that specimens prepared with 20% SiMnF, or 20% SiMnF and 5% SF can yield mortar strengths of up to 30.5 MPa and 48.8 MPa, respectively. Microstructural investigations revealed that the mixes with SiMnF have detectable pores at 1,000× magnification, however, the addition of 5% SF densifies the matrix with no visible pore at the same magnification. This corroborates the strength data. The life-cycle assessment (LCA) indicates that the utilization of SiMnF in the mortar mixtures can reduce CO2 emissions by up to 25% at a reasonably acceptable compressive strength. [ABSTRACT FROM AUTHOR]

A novel asymmetric interior permanent magnet (AIPM) machine is proposed in this paper. The machine's rotor consists of asymmetric poles and auxiliary flux barriers. The torque ripple of the machine is weakened by the asymmetric design of the left and right sides of the magnetic poles. The magnetic‐field‐shifting (MFS) effect improves the electromagnetic torque after adding the auxiliary flux barrier to shift the magnetic axis. The influence of critical geometrical parameters on the electromagnetic performance of the machine is investigated under the condition that the stator and permanent magnet volume remain unchanged. The relevant geometrical parameters of the machine are optimized and designed through the improved Taguchi method. The performance of the AIPM machine and the conventional machine under no‐load and load conditions are further compared by simulation analysis with finite elements, verifying the increase in electromagnetic torque and the reduction in torque ripple. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]