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Ultrasonic welding (UW) is a joining of plastics through the use of heat generated from high-frequency mechanical motion, which is known as an efficient process in many applications, such as textile, packaging, or automotive. UW of thermoplastics has been widely employed in industry since no polymer degradations are found after UW. However, the trial-and-error approach is frequently used to study optimum UW process parameters for new 3C plastic power cases in current industry, resulting in random efforts, wasted time, or energy consumption. In this study, Taguchi methods are used to study optimum UW process parameters for obtaining high weld strength of a plastic power case. The most important control factor influencing the weld strength is amplitude, followed by weld pressure, hold time, and trigger position. The optimum UW process parameters are amplitude of 43.4 µm, weld pressure of 115 kPa, hold time of 0.4 s, and trigger position of 69.95 mm. Finally, the confirmation experiments are performed to verify the optimum process parameters obtained in this study.

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Performances of hybrid Natural Fiber-Reinforced Composites (NFRCs) from E-glass, Nacha (Hibiscus macranthus Hochst. Ex-A. Rich.), and Sisal (Agave sisalana) fibers are investigated for wind turbine blades applications. The process of composite manufacturing was getting started with harvesting and extracting the fibers from undesired constituents. To improve the interfacial interaction between fibers, it was further treated with 5% of NaOH and remnants removal. The experiment was performed based on the Taguchi method, specifically with L16 orthogonal array. Four levels of a natural fiber weight ratio (i.e. 5%, 10%, 15 %, and 20%) were considered during the composite preparations process while the weight of glass fiber was maintained at 5% and 10%. The composites are manufactured using the hand lay-up method, and the test specimens are as per American Society for Testing and Materials (ASTM) standards. Then, tensile, compressive, and flexural tests were carried out using a universal testing machine (UTM). Analysis of variance (ANOVA) was employed to determine the factors which affect the experimental responses. Hence, in the main effect, it was confirmed that Nacha fiber (%wt of N) significantly contributes to tensile, compressive, and flexural strength at a 95% level of confidence. Furthermore, the optimal fiber compositions of composites are determined based on a higher signal-to-noise ratio (S/N) for the corresponding strengths.

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Indium tin oxide (ITO) thin films on polycarbonate (PC) substrates were patterned using the laser direct-write (LDW) technique to form an isolation line. The effect of the LDW parameters (power, pulse repetition rate, and defocusing distance) on the isolation line width, depth and roughness of the PC within the line was investigated. Additionally, the Taguchi method of experimental design was applied to determine the optimal parameters of LDW. Results showed that increasing the power led to an increase in the isolation line width and decrease in the surface roughness of the PC within the line. The increase in the pulse repetition rate and defocusing distance caused a decrease in the isolation line width. The optimal parameters were found to be A2B3C3, consisting of power of 5 W, pulse repetition rate of 100 kHz, and defocusing distance of +3 mm. Under these parameters, we obtained an isolation line width of 48.4 µm, and a surface roughness of Ra 38 nm of the PC within the isolation line. We confirmed that the ITO films separated by the isolation lines attained electrical isolation.

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This study focuses on applying intelligent modeling methods to different injection molding process parameters, to analyze the influence of temperature distribution and warpage on the actual development of auto locks. It explores the auto locks using computer-aided engineering (CAE) simulation performance analysis and the optimization of process parameters by combining multiple quality characteristics (warpage and average temperature). In this experimental design, combinations were explored for each single objective optimization process parameter, using the Taguchi robust design process, with the L18 (21 × 37) orthogonal table. The control factors were injection time, material temperature, mold temperature, injection pressure, packing pressure, packing time, cooling liquid, and cooling temperature. The warpage and temperature distribution were analysed as performance indices. Then, signal-to-noise ratios (S/N ratios) were calculated. Gray correlation analysis, with normalization of the S/N ratio, was used to obtain the gray correlation coefficient, which was substituted into the fuzzy theory to obtain the multiple performance characteristic index. The maximum multiple performance characteristic index was used to find multiple quality characteristic-optimized process parameters. The optimal injection molding process parameters with single objective are a warpage of 0.783 mm and an average temperature of 235.23 °C. The optimal parameters with multi-objective are a warpage of 0.753 mm and an average temperature of 238.71 °C. The optimal parameters were then used to explore the different cooling designs (original cooling, square cooling, and conformal cooling), considering the effect of the plastics temperature distribution and warpage. The results showed that, based on the design of the different cooling systems, conformal cooling obtained an optimal warpage of 0.661 mm and a temperature of 237.62 °C. Furthermore, the conformal cooling system is smaller than the original cooling system; it reduces the warpage by 12.2%, and the average temperature by 0.46%.

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Synovial fluid is dynamic in vivo with biological components changing in ratio and size depending on the health of the joint space, making it difficult to model in vitro. Previous efforts to develop synthetic synovial fluid have typically focused on single organic-tribological interactions with implant surfaces, thus ignoring interplay between multiple solution components. Using a Taguchi orthogonal array, we were able to isolate the individual effects of five independent synovial fluid composition variables: ratios of (1) hyaluronic acid to phospholipids (HA:PL) and (2) albumin to globulin (A:G), and concentrations of (3) hydrogen peroxide (H2 O2 ), (4) cobalt (Co2+ ) and (5) chromium (Cr3+ ) ions on macrophage viability and reduced glutathione production, local solution pH and the comprehensive CoCrMo alloy electrochemical response. While no single synovial fluid variable significantly affected the collective response, HA:PL ratio resulted in the largest impact factor (Δ) on 12 of the 13 measured responses with significant effects (p < .05) on the average macrophage survival rate and electrochemical capacitive state of the CoCrMo surface. Cluster analysis separated significant responses from all trials into three groups, corresponding to healthy, mild, or severely inflamed fluids, respectively; with the healthy synovial fluid composition having mid-range HA:PL ratios with no Co2+ ions, and the severely inflamed fluids consisting of low and high HA:PL ratios with H2 O2 and Co2+ ions. By utilizing the Taguchi approach in combination with cluster analysis, we were able to advance our knowledge of complex multivariate synthetic synovial fluids influence on macrophage and electrochemical behavior at the cell-solution-metal interface.

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In this study, the degree of mechanical anisotropy was investigated through tensile testing of specimens built in different orientations and designed according to the ASTM D638 standard. The mechanical properties that were evaluated include Young's modulus, ultimate tensile strength (UTS), and percentage elongation. Additionally, physical properties, such as mean surface roughness (Ra), density and dimension of the cross-sectional area, were also measured. These properties were then compared with the available standard data to see how SLA performs comparing to the traditional manufacturing methods. The obtained modulus of elasticity and UTS values of the printed samples were 2481 ± 50 MPa and 51.9 ± 1.3 MPa respectively, which were very similar to the standard data (2550 and 52 MPa, respectively) as provided by the material suppliers. The percentage elongation values (4.8% ± 0.4%) were a bit lower than the expected value of 6%. However, the surfaces of all the printed samples were quite smooth, with a surface roughness range of 2.28 ± 0.59 µm. A design of experiments was created to study the influence of the independent variables such as build orientation and angular orientation on the mechanical properties. Extensive statistical analysis, using the Taguchi method and analysis of variance (ANOVA), was performed to examine the effect of these independent variables on the mechanical properties. The SLA printed parts can be classified as isotropic since the build orientation and the angular orientation did not have a statistically significant impact on the mechanical properties. The effect of aging on the mechanical properties was also evaluated and it shows that the specimens that had been aged for a longer time resulted in superior mechanical properties. For example, the UTS increased from 24 to 54 MPa when the sample aligned parallel to the XY plane was aged from 1 week to 6 months, respectively. This significant increase implies that aging has a substantial effect on the mechanical properties of the parts fabricated by stereolithography. The resin used for this study, Visijet Sl Clear, produced very consistent mechanical properties in different directions.

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In this study, the antifungal activity rate of alginate-CuO bionanocomposite was assessed against Aspergillus niger using colony forming units (CFU) and disc diffusion methods. Employing the Taguchi method, nine experiments were designed for the synthesis of alginate-CuO nanocomposite with the highest antifungal activity. The nanocomposite synthesized under the conditions of experiment 5 (4 mg/mL CuO nanoparticles and 1 mg/mL alginate biopolymer with stirring time of 90 min) showed the greatest inhibition rate on fungal growth (83.17%). In the optimum conditions for the synthesis of alginate-CuO nanocomposite with the highest antifungal activity the second level of CuO NPs (14.14%), alginate biopolymer (8.16%) and stirring time (5.63%) showed the best improvement performance on inhibiting the fungal growth. The results of ultraviolet-visible spectroscopy (UV-vis), transmission electron microscopy (TEM) and X-ray powder diffraction (XRD) confirmed the formation of alginate-CuO nanocomposite. Thermogravimetric analysis (TGA) and differential thermal analysis (DTA) indicated that the thermal stability of alginate biopolymer and CuO nanoparticles were improved by the formation of the nanocomposite. Due to the favorable properties of alginate-CuO nanocomposite, its antifungal feature can be used in various biomedical fields.

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In this paper, the effects of geometric parameters on the development of stress in custom cementless hip implant have been studied. Taguchi methods and analysis of variance (ANOVA) were used to find out which geometric parameters are statistically significant for the maximum von Mises stresses in the hip implant. The multiple regression analysis was also performed, to replace the FE solver and accurately and quickly predict the stress values for new patients. Three parameters horizontal offset (HO), vertical offset and neck shaft angle (NSA), with three levels have been selected. Based on L9 orthogonal array, nine hip implant shapes with three different geometric parameters were modelled. Stress analysis was carried out by using finite element analysis. ANOVA results showed that HO has the maximum impact on von Mises stresses followed by the NSA. It is shown that as the HO increases, the stress at the given region increases, however, as the neck shaft (NSA) increases the stress at the given region decreases. Good agreement is found between von Mises stresses, calculated from multiple regression analysis and obtained from FE analysis. To redesign customised hip implant for the minimum stresses, the results of this work will be important.

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Biogas production from food waste has been used as an efficient waste treatment option for years. The methane yields from decomposition of waste are, however, highly variable under different operating conditions. In this study, a statistical experimental design method (Taguchi OA9) was implemented to investigate the effects of simultaneous variations of three parameters on methane production. The parameters investigated were solid content (SC), carbon/nitrogen ratio (C/N) and food/inoculum ratio (F/I). Two sets of experiments were conducted with nine anaerobic reactors operating under different conditions. Optimum conditions were determined using statistical analysis, such as analysis of variance (ANOVA). A confirmation experiment was carried out at optimum conditions to investigate the validity of the results. Statistical analysis showed that SC was the most important parameter for methane production with a 45% contribution, followed by F/I ratio with a 35% contribution. The optimum methane yield of 151 l kg-1 volatile solids (VS) was achieved after 24 days of digestion when SC was 4%, C/N was 28 and F/I were 0.3. The confirmation experiment provided a methane yield of 167 l kg-1 VS after 24 days. The analysis showed biogas production from food waste may be increased by optimization of operating conditions.

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BACKGROUND: A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. METHODS: To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. RESULTS: The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. CONCLUSION: The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors.

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BACKGROUND: A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. METHODS: To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. RESULTS: The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. CONCLUSION: The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors.

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Taguchi's catalog of orthogonal arrays is based on the mathematical theory of factorial designs and difference sets developed by R. C. Bose and his associates. These arrays evolved as extensions of factorial designs and latin squares. This paper (1) describes the structure and constructions of Taguchi's orthogonal arrays, (2) illustrates their fractional factorial nature, and (3) points out that Taguchi's catalog can be expanded to include orthogonal arrays developed since 1960.