Taguchi Design Research Articles

Optimization of the synthesis parameters and analysis of characteristics of 1,1-diamino-2,2-dinitroethylene

2,2-Dinitroethene-1,1-diamine (FOX-7) is a low-sensitive explosive suitable for various energy-material applications. It can be synthesized based on the nitration and hydrolysis of heterocyclic precursors derived from 2-methylimidazole-4,5-dione (MID) or 2-methylpyrimidine-4,6-diol (MPD). However, more information about its optimal synthesis parameters during production from MPD as a starting material is needed. In this study, Taguchi's experimental design method was used to improve the yield of FOX-7. Verification of the results shows that the optimal synthesis parameters are as follows: the molar ratio of HNO3/MPD is 8, the reaction time is 180 minutes, and the reaction temperature is 15°C; the maximum yield of FOX-7 can reach 79.14%. Furthermore, the synthesized FOX-7 was identified and characterized by nuclear magnetic resonance (NMR) spectroscopy analysis, Fourier transforms infrared spectroscopy (FTIR), Raman spectroscopy analysis, and powder X-ray diffraction (PXRD).

Optimizing γ-aminobutyric acid content of fermented mulberry leaves by using Taguchi design and analyzing antioxidant capacity of whole extract

Optimizing γ-aminobutyric acid content of fermented mulberry leaves by using Taguchi design and analyzing antioxidant capacity of whole extract

Implementation of specifically designed deep neural networks for the prediction and optimization of tensile properties of aluminum-copper alloy

Alloys are engineered materials aimed at enhancing mechanical properties. Extensive research has focused on identifying the optimal metal composition for alloys with superior tensile strength. This study validates the stiffness and strength values of an aluminum-copper alloy through a comparison with a molecular dynamics simulation. Subsequently, 100 data points were obtained from the simulation, and a deep neural network (DNN) with three hidden layers was employed. The DNN was trained, tested, and its structure optimized using the Taguchi design of experiment. The proposed DNN structures successfully predicted the maximum values of the stiffness and strength, which were further verified using molecular dynamics simulation. Notably, the results demonstrated the complete reliability of the Taguchi-designed DNN algorithm in this application.

Binary color adsorption by zinc@magnetite nanocomposites: Robust parametric optimization using Taguchi method

AbstractThe goal of the current study was to determine the optimal level (value) of adsorption process variables for the adsorption of color from binary aqueous solution. The impact of key adsorption factors, including adsorbent dose, initial color concentration, and contact time, on the color removal effectiveness of Zinc@magnetite nanocomposites (Zin@Fe3O4(ME) produced from bacterial extracts and Zin@Fe3O4(M) produced from bacterial cell mass), has been examined. Utilizing an L9 orthogonal array (OA), average values and the SN ratio for each variable at three diverse points are calculated. ANOVA has determined the most advantageous optimum conditions for raw and SN data. According to the study, the adsorbent dose is shown to be the most important parameter for color adsorption, while contact duration is determined to be the least important factor based on Pareto chart analysis. The percentage of color removal at optimal values for Zin@Fe3O4(M) and Zin@Fe3O4(ME) nanocomposites, respectively, was found to be 81% and 73%. The optimal parameters were found to be 12.5 mg of adsorbent, 125 mg/L initial dye concentration, and 90 min of contact time at pH 7, room temperature. The confirmatory experiments conducted under optimized conditions revealed a higher percentage of color eliminated than was optimized in each test run of the Taguchi design, proving the credibility of the process variables optimized within the designated experiments.

Aerodynamic Performance Evaluation of a Coaxial Octocopter Based on Taguchi Method

Abstract The design and optimization of propellers for unmanned aerial vehicles (UAVs) are essential for optimal performance and high efficiency. This study presents a numerical investigation of the aerodynamic performance of coaxial octocopters using openfoam as flow solver. While the aerodynamic performance is affected by many parameters, the current study focuses on four main parameters: the propeller type, the horizontal and vertical separation distances between the propellers, and the ratio between the rotational speeds of the upper propeller and the lower one. To find the minimum number of simulations to be performed within defined limits, and reduce the number of computational fluid dynamics (CFD) simulations that cause high computational cost, Taguchi method was employed. In this study, average thrusts were calculated for the preliminary design of the octocopter by examining an isolated single propeller and dual- and quad propellers taking their rotation directions into account. The Taguchi design matrix revealed that for all cases investigated, the propeller type is the most dominant design parameter followed by the velocity ratio of the upper propeller to the lower one (nU/nL) and vertical (z/D) and horizontal (ℓ/D) orientation of coaxial propellers. However, it was shown that ℓ/D and z/D may play a significant role in vortex formation and pressure fluctuations which should be considered as design criteria for coaxial octocopters associated with flow attributes. The results showed that the aerodynamic performance parameters are not dependent on all the selected parameters, and demonstrated that the selected propeller designs improved aerodynamic performance.

Modeling and analysis of TiO2 filler's impact on specific wear rate in flax fiber-reinforced epoxy composite under abrasive wear using Taguchi approach

PurposeThis study explores how titanium oxide (TiO2) filler influences the specific wear rate (SWR) in flax fiber-reinforced epoxy composites (FFRCs) through a Taguchi approach. It aims to boost abrasive wear resistance by incorporating TiO2 filler, promoting sustainable and eco-friendly materials.Design/methodology/approachThis study fabricates epoxy/flax composites with TiO2 particles (0–8 wt%) using hand layup. Composites were tested for wear following American Society for Testing and Materials (ASTM) G99-05. Statistical analysis used Taguchi design of experiments (DOE), with ANOVA identifying key factors affecting SWR in abrasive sliding conditions.FindingsThe study illuminates how integrating TiO2 filler particles into epoxy/flax composites enhances abrasive wear properties. Statistical analysis of SWR highlights abrasive grit size (grit) as the most influential factor, followed by normal load, wt% of TiO2 and sliding distance. Grit size has the highest effect at 43.78%, and wt% TiO2 filler contributes 15.61% to SWR according to ANOVA. Notably, the Taguchi predictive model closely aligns with experimental results, validating its reliability.Originality/valueThis paper integrates TiO2 filler and flax fibers to form a novel hybrid composite with enhanced tribological properties in epoxy composites. The use of Taguchi DOE and ANOVA offers valuable insights for optimizing control variables, particularly in natural fiber-reinforced composites (NFRCs).

Using Bayesian Regularized Artificial Neural Networks to Predict the Tensile Strength of Additively Manufactured Polylactic Acid Parts

Additive manufacturing has transformed the production process by enabling the construction of components in a layer-by-layer approach. This study integrates Artificial Neural Networks to explore the nuanced relationship between process parameters and mechanical performance in Fused Filament Fabrication. Using a fractional Taguchi design, seven key process parameters are systematically varied to provide a robust dataset for model training. The resulting model confirms its accuracy in predicting tensile strength. In particular, the mean squared error is 0.002, and the mean absolute error is 0.024. These results significantly advance the understanding of 3D manufactured parts, shedding light on the intricate dynamics between process nuances and mechanical outcomes. Furthermore, they underscore the transformative role of machine learning in precision-driven quality prediction and optimization in additive manufacturing.

Purification, functional characterization and enhanced production of serratiopeptidase from Serratia marcescens MES-4: An endophyte isolated from Morus rubra

Serratiopeptidase, a proteolytic enzyme serves as an important anti-inflammatory and analgesic medication. Present study reports the production and purification of extracellular serratiopeptidase from an endophyte, Serratia marcescens MES-4, isolated from Morus rubra. Purification of the enzyme by Ion exchange chromatography led to the specific activity of 13,030 U/mg protein of serratiopeptidase, showcasing about 3.1 fold enhanced activity. The catalytic domain of the purified serratiopeptidase, composed of Zn coordinated with three histidine residues (His 209, His 213, and His 219), along with glutamate (Glu 210) and tyrosine (Tyr 249). The molecular mass, as determined by SDS-PAGE was ∼51 kDa. The purified serratiopeptidase displayed optimal activity at pH 9.0, temperature 50°C. Kinetic studies revealed Vmax and Km values of 33,333 U/mL and 1.66 mg/mL, respectively. Further, optimized conditions for the production of serratiopeptidase by Taguchi design led to the productivity of 87 U/mL/h with 87.9 fold enhanced production as compared to the previous conditions.

Study of Processing Conditions during Enzymatic Hydrolysis of Deer By-Product Tallow for Targeted Changes at the Molecular Level and Properties of Modified Fats.

In most cases, the unused by-products of venison, including deer tallow, are disposed of in rendering plants. Deer tallow contains essential fatty acids and can be used to prepare products for everyday food and advanced applications. This work aimed to process deer tallow into hydrolyzed products using microbial lipases. A Taguchi design with three process factors at three levels was used to optimize the processing: amount of water (8, 16, 24%), amount of enzyme (2, 4, 6%), and reaction time (2, 4, 6 h). The conversion of the tallow to hydrolyzed products was expressed by the degree of hydrolysis. The oxidative stability of the prepared products was determined by the peroxide value and the free fatty acids by the acid value; further, color change, textural properties (hardness, spreadability, stickiness, and adhesiveness), and changes at the molecular level were observed by Fourier transform infrared spectroscopy (FTIR). The degree of hydrolysis was 11.8-49.6%; the peroxide value ranged from 12.3 to 29.5 µval/g, and the color change of the samples expressed by the change in the total color difference (∆E*) was 1.9-13.5. The conditions of enzymatic hydrolysis strongly influenced the textural properties: hardness 25-50 N, spreadability 20-40 N/s, and stickiness < 0.06 N. FTIR showed that there are changes at the molecular level manifested by a decrease in ester bonds. Enzymatically hydrolyzed deer tallow is suitable for preparing cosmetics and pharmaceutical matrices.

Sensitivity analysis of near solidus forming (NSF) process with digital twin using Taguchi approach

AbstractForging at near solidus material state takes advantage of the high ductility of the material at the semi solid or soft-solid state while keeping most of the mechanical properties of a forged part. The technology is at maturity level ready for its industrial implementation. However, to implement the process for complex cases the development of an appropriate digital twin (DT) is necessary. While developing a material model, a strong experimental and DT is necessary to be able to evaluate the accuracy of the model. Aimed at having a reliable DT under control, for future material model validations, the main objective of this work is to develop a sensitivity analysis of three NSF industrial cases such as Hook, R spindle and H spindle to develop an adequate DT calibration procedure. Firstly, the benchmark experimentation process parameter noise and experimentation boundary conditions (BCs) parameter uncertainty are identified. Secondly, the three industrial benchmark DTs are constructed, and a Taguchi design of experiments (DoEs) methodology is put in place to develop the sensitivity analysis. Finally, after simulations the results are critically evaluated and the sensitivity of each benchmark to the different inputs (process parameter noise and BC parameter uncertainty) is studied. Lastly, the optimum DT calibration procedure is developed. Overall, the results stated the minimum impact of the material model in terms of dies filling. Nevertheless, even if the material model is the highest impacting factor for the forging forces other inputs, such as heat transfer and friction must be under control first.

Circular closed-loop supply chain network design considering 3D printing and PET bottle waste

AbstractOne of the most critical pillars of Industry 4.0 (I4.0) is Additive Manufacturing (AM) or 3D Printing technology. This transformative technology has garnered substantial attention due to its capacity to streamline processes, save time, and enhance product quality. Simultaneously, environmental concerns are mounting, with the growing accumulation of plastic bottle waste, offering a potential source of recycled material for 3D printing. To thoroughly harness the potential of AM and address the challenge of plastic bottle waste, a robust supply chain network is essential. Such a network not only facilitates the reintegration of plastic bottle waste and 3D printing byproducts into the value chain but also delivers significant environmental, social, and economic benefits, aligning with the tenets of sustainable development and circular economy. To tackle this complex challenge, a Mixed-Integer Linear Programming (MILP) mathematical model is offered to configure a Closed-Loop Supply Chain (CLSC) network with a strong emphasis on circularity. Environmental considerations are integral, and the primary objective is to minimize the overall cost of the network. Three well-known metaheuristics of Simulated Annealing (SA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) are employed to treat the problem which are also efficiently adjusted by the Taguchi design technique. The efficacy of our solution methods is appraised across various problem instances. The findings reveal that the developed model, in conjunction with the fine-tuned metaheuristics, successfully optimizes the configuration of the desired circular CLSC network. In conclusion, this research represents a significant step toward the establishment of a circular supply chain that combines the strengths of 3D printing technology and the repurposing of plastic bottle waste. This innovative approach holds promise for not only reducing waste and enhancing sustainability but also fostering economic and social well-being.

Parametric optimization of a drone mounted sprayer to maximize the swath width using Taguchi design

Parametric optimization of a drone mounted sprayer to maximize the swath width using Taguchi design

Optimization of Hazardous Malachite Green Dye Removal Process Using Double Derivatized Guar Gum Polymer: A Fractional Factorial L9 Approach

The dye molecules are one of the water-polluting agents among other contaminants in water bodies and impart unsuitability. In recent years, bio-based materials have attracted considerable attention for varied industrial applications due to their abundant availability on a sustainable basis, biodegradability, cost and energy efficiency. The present study hypothesized to synthesize carboxymethyl-hydroxypropyl guar gum (CMHPGG) dual derivative to remove malachite green dye from an aqueous medium using Taguchi's L9 design. The 73 % dye adsorption was achieved using CMHPGG, comprising carboxymethyl (DS 0.58) and hydroxypropyl (0.128 %) groups. The temperature, pH of the medium and amount of CMHPGG were selected as dye adsorption process control factors. The optimized reaction conditions comprise pH 5, CMHPGG-2, 250 mg/100 mL, and a temperature of 45°C. The characteristic asymmetric (1643 cm−1) and symmetric (1590 cm−1) absorption bands (-COO¯) were observed in the CMHPGG. The roughness was observed on the surface that was increased on derivatization. The thermal behaviour revealed better thermal stability compared to native GG.

Investigation of flow behaviour in the nozzle of a Pelton wheel: Effects and analysis of influencing parameters

The performance of a Pelton wheel is influenced by the jet created by the nozzle. Therefore, a Computational Fluid Dynamics (CFD) simulation was proposed. In this study, the significant output parameters (outlet velocity, outlet pressure, and tangential force component) and input parameters (different pressure and spear locations) were examined. In addition, the influencing parameters and their contributing percentages to the performance of the Pelton wheel were calculated using different optimisation techniques such as Taguchi Design of Experiments (DoE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA) and Criteria Importance Through Intercriteria Correlation (CRITIC). The effect of input factors on the output response was examined with DoE, and the results show that the inlet pressure had the most significant impact (97.38%, 99.18%, and 97.38%, respectively, for all different spear sites with a 99% confidence level). In terms of preference values, the TOPSIS and GRA results are comparable (best ranks for simulation runs #24 and #25 and least ranks for simulations #2 and #3, respectively). The CRITIC results for the pressure parameter are in good agreement with the Taguchi ANOVA analysis. The last spear location (5 mm after the nozzle outlet), with an inlet pressure of 413685 Pa generated the best result when employing the TOPSIS and GRA techniques. The outlet pressure of the nozzle was found to have a significant impact on the flow pattern of the Pelton Wheel based on the analysis of the CRITIC, Taguchi, and CFD results.

Polyol synthesis of cobalt doped zinc oxide green nano-pigments: Colorimetry assessments and chemical synthesis parameters optimization

Cobalt-doped zinc oxide nanoparticles were synthesized as inorganic nano-pigments by the Polyol chemical preparation method, which is a simple and cost-effective method. Results showed that ethylene glycol (EG) should be utilized for synthesis of nanoparticles with smaller average crystallite size and better crystallinity. Other factors such as molar ratio of cobalt nitrate(Co(No3)2) to zinc acetate(Zn(Ac)2, reaction time, molar ratio of water and sodium hydroxide(NaOH) to the zinc acetate, surfactant and its molar ratio to the zinc were optimized via Taguchi design. The optimum sample was prepared under conditions such as the cobalt nitrate to zinc molar ratio of 0.01, reaction time of 5h, and Triton X100 (molar ratio of 0.2). X-Ray diffraction analysis demonstrated that average crystallite size of the optimum sample was 11 nm. FESEM revealed the uniformity of the powders having nearly a rod-like structure with low aspect ratios. Besides, the impacts of the effective synthesis factors on the colorimetric properties were optimized. Accordingly, the optimum sample revealed a green region with brightness of 58.89(L*), color purity (a* = −22.82), and color hue of 166.89(h°). Average crystallite size, amorphous phase percentage and colorimetric properties correlations have been investigated for the first time. Placement of more cobalt atoms in the ZnO structure raises the brightness coordinate and results more greenness in the color and increase of the crystal size does not directly affect the brightness coordinate.

A Taguchi Optimization of Stir Casting Process Parameters for graphene Nanoplatelets/ A356 Alloy Composite

Aluminum metal matrix composite (AMC) is a potential material for diverse applications in the field of automotive and aerospace owing to their superior mechanical properties, lightweight behavior, and low thermal expansion. Graphene nanoplatelets (GNP) have emerged as the preferred reinforcement in AMC. They are incorporated into the matrix by stir-casting methods to generate semi-solid feedstock suitable for thixoforming. The effects of the stirrer parameter and GNP content were examined using Taguchi design of experiments with an L8 (23) orthogonal array. The parameters tested were stirring speed (300-500rpm), GNP content (0.3- 0.7 wt%) and stirring time (5-10 minutes). The signal-to-noise ratio (S/N) and hardness of the GNP /A356 composite were used as response variables. The contribution of three factors in enhancing hardness has been identified. The optimum parameter obtained with stirring speed, GNP content, and stirring time is 500rpm, 0.7wt.%GNP and 5 min respectively.

Taguchi Design for Development of Lipid-Polymer Effervescent Floating Tablets for Metformin Prolonged Release

TFloating drug delivery systems (FDDS) formulated with hydrophilic polymers and effervescent agents are a promising gastro retentive tool for prolonged drug release, especially with drug with low bioavailability and low solubility. Lately, it has been reported that the combination of lipids with hydrophilic polymers in the development of blends or composite hybrid materials may bring together the properties of individual components. This study proposed four formulations of effervescent lipid-polymer FDDS through a Taguchi experimental design for metformin’s prolonged release. Tablets were obtained by wet granulation, and the effect of HPMC, Compritol®, and sodium bicarbonate was studied. All formulations were evaluated with pharmacotechnical and biopharmaceutical properties such as in-vitro drug delivery, flotation, swelling, erosion and release kinetics. Effervescent lipid-polymer FDDS were obtained with prologued release until 24 hours. Formulation F1 meets the acceptance criteria of USP extended delivery. Compritol®, combined with HPMC and sodium bicarbonate, impacted release behavior and buoyancy properties. Formulations with high amounts of HPMC and Compritol® were found to have the lowest release rates and followed the Peppas-Sahlin kinetic model. Successful preparation of effervescent lipid-polymer was achieved and evaluated through a Taguchi experimental design, expected to result in prologued release and better therapeutic behavior

Optimization of Bacterial Cellulose Production by Komagataeibacter rhaeticus K23

The use of bacterial cellulose (BC), having high purity, a high degree of crystallinity, water-holding capacity, tensile strength and adaptability on a broad scale is limited because of the low yield. In this study, the optimal conditions for bio-cellulose production by Komagataeibacter rhaeticus K23 were investigated. Optimal values for temperature, pH, inoculum concentration and incubation time were determined via Taguchi design. The maximum BC production, 9.1 ± 0.66 g·L−1 (dry weight), was obtained from 32 °C, pH 5.5, 8 log CFU·mL−1 and 14 days of incubation. The inoculum concentration was the most significant factor affecting BC yield. A value of 8 log CFU·mL−1 and 14 days of incubation led to significantly higher levels of BC yield than other concentrations (8.5, 9, 9.5, 10 and 10.5 log CFU·mL−1) (p &lt; 0.002) and days (15, 16, 17, 21 and 28) (p &lt; 0.001). The studied features, namely absorption peaks (Fourier transform infrared spectroscopy), pattern and the crystallinity index (X-ray diffraction analysis) of the BC obtained in this study were all in parallel with the characteristics of cellulose I. The study demonstrates that optimized parameters were effective in producing BC with high water-holding capacity, tensile strength, elongation and Young’s modulus (mechanical tests) by K. rhaeticus K23.

Application of Taguchi design of experiments in the food industry: a systematic literature review

The optimal utilization of available resources is critical for industrial experimentation. In addition, a structured approach with reliable and reproducible results and robust predictability is paramount to achieving profitability, waste reduction, and improvements in the food industry. The Taguchi design of experiments (DOE) is a practical approach that optimizes the critical characteristics using minimum time and resources – reviewing its application in the food sector assists in determining research gaps that could provide sustainable solutions to academia, industry, and policymakers. This research provides a systematic review of the literature on the Taguchi DOE application for the past two decades in the food industry. The systematic review considered articles published in peer-reviewed journals indexed in Scopus, Web of Science, and PubMed databases. The research categorized the relevant articles into three core themes and 31 sub-themes. This study identified only 31 relevant articles despite the significant advantages of applying the Taguchi DOE in the food industry. Most applications did not explore the true potential of the Taguchi DOE approach to obtain robust and scalable solutions. Also, the analysis determined that a structured approach is missing in most studies, with a lack of utilization of essential tools during the research.

Enhancing tribological performance in PM Vanadis 6 steel through optimization of cryogenic and tempering treatment

Vanadis 6, which gained popularity for industrial applications due to increased strength and wear resistance, benefited from cryogenic treatment. This study investigated the influence of cryogenic and tempering treatments on the tribological properties of Vanadis 6 cold-work tool steel, crucial for cost-effective and durable tooling. Dry sliding wear experiments using Taguchi design under varying loads and sliding velocities revealed that cryogenic treatment at − 140 °C followed by 170 °C tempering resulted in the lowest wear rate, friction coefficient, smoothest worn surfaces, and the highest transition load. Microstructural analysis supported these findings, indicating reduced retained austenite and increased carbide count in cryogenically processed steel at − 140 °C.