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In this study, a multi-objective optimization regarding the tribological characteristics of the hybrid composite with a base material of aluminum alloy A356 as a constituent, reinforced with a 10 wt.% of silicon carbide (SiC), size 39 µm, and 1, 3, and 5 wt.% graphite (Gr), size 35 µm, was performed using the Taguchi method, gray relational analysis (GRA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making methods. Tribological tests were carried out on a “block on disc” type tribometer with lubrication. Load, sliding speed, and graphite mass concentration were analyzed as input parameters. As output parameters, wear rate and coefficient of friction were calculated. An analysis of variance (ANOVA) was conducted to identify all parameters that have a significant influence on the output multi-response. It was found that the normal load has the highest influence of 41.86%, followed by sliding speed at 32.48% and graphite addition at 18.47%, on the tribological characteristics of composites. Multi-objective optimization determined that the minimal wear rate and coefficient of friction are obtained when the load is 40 N, the sliding speed is 1 m/s, and the composite contains 3 wt.% Gr. The optimal combination of parameters achieved by GRA was also confirmed by the TOPSIS method, which indicates that both methods can be used with high reliability to optimize the tribological characteristics. The analysis of worn surfaces using scanning electron microscopy revealed adhesive and delamination wear as dominant mechanisms.

This research employs the Taguchi method and analysis of variance (ANOVA) to investigate, analyze, and optimize the impact strength of tough polylactic acid (PLA) material produced through fused deposition modeling (FDM). This study explores the effect of key printing parameters—specifically, infill density, raster angle, layer height, and print speed—on Charpy impact strength. Utilizing a Taguchi L16 orthogonal array experimental design, the parameters are varied within defined ranges. The results, analyzed through signal-to-noise (S/N) ratios and ANOVA, reveal that infill density has the most substantial impact on Charpy impact strength, followed by print speed, layer height, and raster angle. ANOVA identifies infill density and print speed as the most influential factors, contributing 38.93% and 36.51%, respectively. A regression model was formulated and this model predicted the impact strength with high accuracy (R2 = 98.16%). The optimized parameter set obtained through the Taguchi method, namely, a 100% infill density, 45/−45° raster angle, 0.25 mm layer height, and 75 mm/s print speed, enhances the impact strength by 1.39% compared to the experimental design, resulting in an impact strength of 38.54 kJ/m2. Validation experiments confirmed the effectiveness of the optimized parameters.

The Taguchi method, a robust experimental design technique, establishes a strong connection between input and output variables. Known for its capacity to yield precise results with fewer trials and minimized errors, this method has gained widespread application in various fields such as engineering, physics, chemistry, economics, finance, and more. In this paper, the authors examine the importance of the Taguchi orthogonal array method, its step-by-step optimization procedure, and its potential for future applications. Through a thorough literature review, the authors investigate how the Taguchi method has been effectively employed to identify key factors influencing response variables. The versatility of the Taguchi method becomes apparent when considering its applications across diverse disciplines. Researchers in engineering have successfully utilized this technique to optimize processes and enhance product quality. Furthermore, in scientific fields like physics and chemistry, the Taguchi method has proven invaluable for conducting experiments efficiently, resulting in more accurate and reproducible outcomes. Researchers gain critical insights into the effects of factors on the response variable by employing statistical tools such as mean analysis, variance analysis, and signal-to-noise ratio. The Taguchi method remains a valuable and broadly applicable tool for optimizing experiments and identifying influential factors across multiple disciplines. This paper’s extensive literature review emphasizes its significance in various fields and outlines the step-by-step procedure to leverage its potential for optimization.

In this paper, the Taguchi method was used to identify the optimum mixture proportions of alkali-activated reactive powder concrete (AARPC) by considering the most influential parameters. Five main parameters, including binder content, alkaline activator-binder ratio (Al-binder), binder-fine aggregate ratio, sodium silicate to sodium hydroxide ratio ([Na.sub.2]Si[O.sub.3]-NaOH), and sodium hydroxide (NaOH) concentration, were considered in the mixture design. A total of 18 trial batches were designed according to the L18 array obtained from the Taguchi method. The results showed that the highest average compressive strength was 110.9 MPa (16.08 ksi) and the lowest average compressive strength was 50.6 MPa (7.34 ksi). The test results of the 18 trial batches were then evaluated by the analysis of variance (ANOVA) method to determine the optimum level of each parameter. It was found that specimens with a binder content of 700 kg/[m.sup.3] (0.025 lb/[in..sup.3]), Al-binder ratio of 0.3, binder-fine aggregate ratio of 0.8, [Na.sub.2]Si[O.sub.3]-NaOH ratio of 2, and NaOH concentration of 14 M produced the highest 28-day compressive strength (116.77 MPa [16.94 ksi]) at the ambient curing conditions. Keywords: alkaline activator; compressive strength; Taguchi method; ultra-high-strength concrete.

Sewage sludge is a common form of municipal solid waste, and can be utilized as a renewable energy source. This study examines the effects of different key operational parameters on sewage sludge pyrolysis process for pyrolytic oil production using the Taguchi method. The digested sewage sludge was provided by the urban wastewater treatment plant of Tainan, Taiwan. The experimental results indicate that the maximum pyrolytic oil yield, 10.19% (18.4% on dry ash free (daf) basis) by weight achieved, is obtained under the operation conditions of 450 °C pyrolytic temperature, residence time of 60 min, 10 °C/min heating rate, and 700 mL/min nitrogen flow rate. According to the experimental results, the order of sensitivity of the parameters that affect the yield of sludge pyrolytic oil is the nitrogen flow rate, pyrolytic temperature, heating rate and residence time. The pyrolysis and oxidation reactions of sludge pyrolytic oil are also investigated using thermogravimetric analysis. The combustion performance parameters, such as the ignition temperature, burnout temperature, flammability index and combustion characteristics index are calculated and compared with those of heavy fuel oil. For the blend of sludge pyrolytic oil with heavy fuel oil, a synergistic effect occurs and the results show that sludge pyrolytic oil significantly enhances the ignition and combustion of heavy fuel oil.

Direct metal laser sintering (DMLS) is an additive manufacturing technique for the fabrication of near net-shaped parts directly from computer-aided design data by melting together different layers with the help of a laser source. This paper presents an investigation of the surface roughness of aluminum samples produced by DMLS. A model based on an L 18 orthogonal array of Taguchi design was created to perform experimental planning. Some input parameters, namely laser power, scan speed, and hatching distance were selected for the investigation. The upper surfaces of the samples were analyzed before and after shot peening. The morphology was analyzed by means of field emission scanning electron microscope. Scan speed was found to have the greatest influence on the surface roughness. Further, shot peening can effectively reduce the surface roughness.

This research investigates the control of thickness and weight in plastic extrusion vacuum-thermoforming products to identify optimal key parameters for cost reduction and energy savings. The initial step involves identifying crucial influencing factors. In this step, the Delphi technique was employed through a questionnaire administered to a panel of expert scholars to ensure minimal error and maximal reliability in determining key influencing factors. Consensus was sought to establish appropriateness and consistency. Subsequently, the Taguchi method was applied for quality design and planning of the extrusion vacuum-forming process. The experimental design parameters were selected using an L18 (21 × 37) orthogonal array, and the desired quality characteristics were determined. Comparative analysis of quantitative production data from two consecutive experiments was conducted, and based on F-values and contribution analysis, the combination of control factors maximizing the Signal-to-Noise (S/N) ratio was identified. The objective is to seek optimal parameters for improving the quality of the plastic polypropylene (PP cup lid) manufacturing process, reducing process variability, and identifying the most robust production conditions. Through multiple actual production prediction experiments, it was determined that five control factors, “polypropylene new material ratio,” “T-die lips adjustment thickness”, “mirror wheel temperature stability”, “molding vacuum pressure time”, and “forming mold area design”, contribute to the maximization of the S/N ratio, i.e., minimizing variability. Statistical validation confirms a significant improvement in product quality and weight control. Noteworthily, the quality control model and experimental design parameters established in this study are also applicable to other plastic products and bio-based materials, such as PET, HIPS, and biodegradable PLA lids with added calcium carbonate. The results of the experimental production demonstrate its ability to consistently control product weight within the range of 3.4 ± 0.1 g, approaching the specified tolerance limits. This capability results in approximately 2.6% cost savings in product weight, contributing significantly to achieving a company’s KPI goals for environmental conservation, energy efficiency, and operational cost reduction. Therefore, the findings of this study represent a substantial and tangible contribution.

This study investigates the impact of arc length, current intensity, travel speed, and gas flow rate on surface hardness and line width during arc quenching process of S45C steel. The current intensity has the greatest influence on the surface hardness of S45C steel, followed by the travel speed, gas flow rate, and arc length. Using the Taguchi method, the optimal values of the parameters such as the arc length of 1.5 mm, the current intensity of 125 A, the travel speed of 250 mm/min and the gas flow rate of 12.5 l/min were calculated. The optimal surface hardness would be 379 HV, with a standard deviation of 46.4 HV. The current intensity is the most critical component in determining line width among these parameters. The arc length ranks second, followed by the TIG gun’s travel speed. The gas flow rate is the least significant factor. A longer arc length may result in a broader heat zone, which leads to a better line width. Increasing the arc length, current intensity, travel speed, and gas flow rate results in a similar pattern of surface hardness change caused by the low-heated and over-heated phenomena. The microhardness distribution showed a hardening zone of up to 2500 μm and a maximum hardness of 453 HV. The microstructure of arc quenching samples has three zones: hardening, heat-affected, and base metal. The hardening zone exhibits a martensite microstructure with a tiny needle shape and a residual austenite matrix.

This paper presents the optimization of cutting forces, average surface roughness, cutting temperature, and chip reduction coefficient in turning of Ti-6Al-4V alloy under dry and high pressure coolant (HPC) that is applied at the rake and flank surfaces simultaneously. The experimental design plan was conducted by the full factorial parameter orientation. The optimization has been conducted in two ways: firstly, by using signal-to-noise ratio-based Taguchi method as mono-objective optimization; secondly, by using gray relational analysis integrated with Taguchi method as multi-objective optimization. In either method, the cutting speed, feed rate, and cutting condition were considered as the inputs to the optimization. The mono-objective optimization concluded that the 156 m/min cutting speed and 0.12 mm/rev feed rate when run under HPC optimized the cutting forces and roughness, and when operated under dry optimized chip reduction coefficient, the cutting temperature was minimized at 78 m/min and 0.12 mm/rev feed rate. The multi-objective optimization concluded that Ti alloy turning system is optimized at 156 m/min cutting speed and 0.12 mm/rev feed rate under HPC.

Electrochemical synthesis method for fabrication of ZnO nanoparticles is widely used due to its simplicity, low temperature operation, low energy consumption and greater purity of the synthesized product. This paper proposed a process optimization method, namely, TOPSIS-Taguchi method, for electrochemical synthesis of ZnO nanoparticles with respect to productivity and consumption using TOPSIS and Taguchi methods. TOPSIS is used to convert multiple responses into a single integrated response (IR), and Taguchi method is used to design experiment and find optimal process parameters (PPs) to optimize the multiple responses. We determined the optimal PPs pH, concentration (CC), voltage (VL), and conductivity (CD) to maximize the productivity of ZnO nanoparticles and minimize the specific energy consumption and specific electrode consumption. The optimal PPs were pH of 5, CC of 0.05 M, VL of 8 V, and CD of 30ms/cm, and their effect ranking on the IR was CC (37.657%), CD (32.498%), pH (15.614%), and VL (14.231%). Moreover, we developed the multiple quadratic regression model that reflects the relationship between the IR and the PPs, and determined the optimal PPs using grid search optimization method. The result was perfectly the same to the proposed TOPSIS-Taguchi method. The proposed method could be widely used to not only electrochemical synthesis process optimization of ZnO nanoparticles but also various materials fabrication process optimization problems.