Search results

This paper aims to determine the optimum parametric settings for yielding superior mechanical properties, namely, ultimate tensile strength (UTS), yield strength (YS) and percentage elongation (EL) of AZ91D/AgNPs/TiO₂ hybrid composite fabricated by friction stir processing.

An empirical model has been developed to govern crucial influencing parameters, namely, rotation speed (RS), tool transverse speed (TS), number of passes (NPS) and reinforcement fraction (RF) or weight percentage. Box Behnken design (BBD) with four input parameters and three levels of each parameter was used to design the experimental work, and analysis of variance (ANOVA) was used to check the acceptability of the developed model. Desirability function analysis (DFA) for a multiresponse optimization approach is integrated with response surface methodology (RSM). The individual desirability index (IDI) was calculated for each response, and a composite desirability index (CDI) was obtained. The optimal parametric settings were determined based on maximum CDI values. A confirmation test is also performed to compare the actual and predicted values of responses.

The relationship between input parameters and output responses (UTS, YS, and EL) was investigated using the Box-Behnken design (BBD). Silver nanoparticles (AgNPs) and nano-sized titanium dioxide (TiO₂) enhanced the ultimate tensile strength and yield strength. It was observed that the inclusion of AgNPs led to an increase in ductility, while the increase in the weight fraction of TiO₂ resulted in a decrease in ductility.

AZ91D/AgNPs/TiO₂ hybrid composite finds enormous applications in biomedical implants, aerospace, sports and aerospace industries, especially where lightweight materials with high strength are critical.

In terms of optimum value through desirability, the experimental trials yield the following results: maximum value of UTS (318.369 MPa), maximum value of YS (200.120 MPa) and EL (7.610) at 1,021 rpm of RS, 70 mm/min of TS, 4 NPS and level 3 of RF.

An optimized model is often deployed to reduce trial and error in experimental approach and obtain the multi-variant correlation. In this study, response surface methodology (RSM), namely, Box–Behnken design (BBD) approach, has been used to optimize the characterization of lubricant with additives. BBD is based on multivariate analysis whereby the effects of different parameters are considered simultaneously. It is a non-linear system which is more representative of the actual phenomenon. This study aims to investigate the effect of three independent variables, namely, speed, load and concentration of TiO₂, on the coefficient of friction (CoF).

RSM was applied to get the multiplicity of the self-determining input variables and construct mathematical models. Mathematical models were established to predict the CoF and to conduct a statistical analysis of the independent variables’ interactions on response surface using Minitab 16.0 statistical software. Three parameters were regulated: speed (X₁), load (X₂) and concentration of TiO₂ (X₃). The output measured was the CoF.

The result obtained from BBD has shown that the most influential parameter was speed, followed by concentration of TiO₂ nanoparticles and then normal load. Analysis of variance indicated that the proposed experiment from the quadratic model has successfully interpreted the experimental data with a coefficient of determination R² = 0.9931. From the contour plot of BBD, the optimization zone for interacting variables has been obtained. The zone indicates two regions of lower friction values (<0.04): concentration between 0.5 to 1.0 Wt.% for a speed range of 1,000 to 2,000 rpm, and load between 17 to 20 kg for a speed in the range of 1,200 to 1,900 rpm. The optimized condition shows that the minimum value of CoF (0.0191) is at speed of 1,782 rpm, load of 20 kg and TiO₂ concentration of 1.0 Wt.%.

In general, it has been shown that RSM is an effective and powerful tool in experimental optimization of multi-variants.

This study aims to investigate the effect of process parameters of blow room machines on openness degree and quality of cotton tufts in a blow room.

For this purpose, an experimental Box–Behnken design (BBD) was used, and the process parameters were the angles of the grid bars underneath the opening rollers of CVT3 beaters and the distance between feed roller of the first opening roller of CVT3.

It was found that the cotton tuft openness increased by increasing the angles of grid bars and by decreasing the distance between the feed roller and first opening roller on CVT3 beater. Further, the optimization procedure showed that an optimum value of cotton tuft openness (in laser method) was determined for specific levels of the process parameters.

The originality of this investigation is that it showed the individual effects and interactions of the most important factors in two tufting machines instead of only one machine. This study is important because it helps cotton yarn spinners to improve the quality of the final yarns by optimizing the levels of tuft openness which in turn improves fiber cleaning.

This study aims to investigation of the guar gum-manganese dioxide (GG/MnO₂) nanocomposite (NC) synthesized using an environment-friendly method and the degradation of reactive yellow (RY 145) dye in the UV system.

Characterization of the GG/MnO₂ NCs were conducted using field emission scanning electron microscopy, X-ray diffraction and Fourier-transform infrared spectroscopy. Experiments were conducted using a 1 L glass reactor coupled with Ultraviolet (UV-C) blue light bulb of wavelength 250 nm and power of 8 W.

The NC (2.25 g/L) displayed high RY 145 dye degradation (81%) with 10 mg/L of concentration at pH 3. The coefficient of determination (R² 0.99) also depicted that the model fits the experimental data. The analysis of variance (ANOVA) showed that the F-values of 464.75, 276.04 and 5.15 are related to the dose of GG/MnO₂ NCs, initial concentration of RY 145 dye and solution pH, respectively.

The GG/MnO₂ NCs followed by photo oxidation process (UV-process) could be used to degrade the RY 145 dye from synthetic wastewater.

There are two main innovations. One is that the novel process is performed successfully for RY 145 dye degradation. The other is that the optimized conditions are obtained by Box–Behnken design. Also, the effects of different variables on the RY 145 dye removal efficiency were investigated.

Surface roughness and vibration during machining are inevitable which critically affect the product quality characteristics. This paper aims to suggest the implementation of a multi-objective optimization technique to obtain the favorable parametric conditions which lead to minimum tool vibration and surface roughness of 6063-T6 aluminum alloy in computer numerically controlled (CNC) turning.

The case study has been accomplished according to response surface methodology RSM’s Box–Behnken design (BBD) matrix using Titanium Nitride-coated Tungsten Carbide insert in a dry environment. As the experimental results are quite nonlinear, a second-order regression model has been developed for the responses (surface roughness and tool vibration) in terms of input cutting parameters (spindle speed, feed rate and depth of cut). The goodness of fit of the models has also been verified with analysis of variance (ANOVA) results.

The significance efficacy of input parameters on surface roughness and tool vibrations has been illustrated through multi-objective overlaid 3D surface plots and contour plots. Finally, parametric optimization has been performed to get the desired response values under the umbrella of weighted aggregate sum product assessment (WASPAS) method and verified confidently with confirmatory test results.

The results of this study reveals that hybrid RSM with WASPAS method can be readily applicable to optimize multi-response problems in the manufacturing field with higher confidence.

This paper aims to focus on the optimisation of dyeing recipe for dyeing of silk fabric with semisynthetic azo dyes synthesised by chemical modification of areca nut extract.

The response surface model (Box–Behnken design) was used to establish the relation between the parameters of dyeing such as time, temperature and material to liquor ratio. Their output responses in terms of colour strength (K/S values) are reported. Their relationship was tested for predictability and the experimental values and found to match closely, which confirms the model suitability.

Dyed fabrics were tested for their fastness properties such as wash, rub and lightfastness. The results of the fastness tests indicate that modified dyes have good dyeability towards silk fabric. The dyed fabrics were also tested for ultraviolet protection factor and antimicrobial activity, which showed very promising results.

Banned amine testing was done, which confirms the absence of banned amine in synthesised dyes, which indicates the potential of its sustainability. Also, such an approach of modification of natural dyes as semi-synthetic dyes can be surely considered to be a step towards its widespread acceptability and further commercialisation.

This study aims to experimentally investigate the influence of considered process parameters, i.e. pulse on time, pulse off time, peak current and gap voltage, on tool wear rate (TWR) in electrical discharge machining (EDM) of iron (Fe)-based shape memory alloy (SMA) through designed experiments. The parametric optimization for TWR has also been attempted using the desirability approach and genetic algorithm (GA).

The response surface methodology (RSM) in the form of Box–Behnken design has been used to scheme out the experiments. The influence of considered process inputs has also been observed through variance analysis. The reliability and fitness of the developed mathematical model have been established with test results. Microstructure analysis of machined samples has also been evaluated and analyzed using a scanning electron microscope (SEM). SEM images revealed the surface characteristics such as micro-cracks, craters and voids on the tool electrode surface. SEM images provide information about the surface integrity and type of wear on the surface of the tool electrode.

The input parameters, namely, pulse on time and pulse off time, are major influential factors impacting the TWR. High TWR has been reported at large pulse on time and small pulse off time conditions whereas higher TWR is reported at high peak current input settings. The maximum and minimum TWR values obtained are 0.073 g/min and 0.017 g/min, respectively. The optimization with desirability approach and GA reveals the best parametric values for TWR i.e. 0.01581 g/min and 0.00875 g/min at parametric combination as pulse on time = 60.83 µs, pulse off time = 112.16 µs, peak current = 18.64 A and gap voltage = 59.55 V, and pulse on time = 60 µs, pulse off time = 120 µs, peak current = 12 A and gap voltage = 40 V, correspondingly.

Proposed work has no limitations.

SMAs have been well known for their superior and excellent properties, which make them an eligible candidate of paramount importance in real-life industrial applications such as orthopedic implants, actuators, micro tools, stents, coupling, sealing elements, aerospace components, defense instruments, manufacturing elements and bio-medical appliances. However, its effective and productive processing is still a challenge. Tool wear study while processing of SMAs in EDM process is an area which has been less investigated and of major concern for exploring the various properties of the tool and wear in it. Also, the developed mathematical model for TWR through the RSM approach will be helpful in industrial revelation.

The purpose of this paper is to analyze nano zero-valent iron (nZVI)-activated carbon/Nickel (nZVI-AC/Ni) by a novel method. The synthesized adsorbent was used to degrade reactive orange 16 (RO 16) azo dye.

The optimum conditions for the highest removal of RO 16 dye were determined. Characterization of nZVI-AC/Ni was done by scanning electron microscopy, Fourier-transform infrared spectroscopy, X-ray diffraction and energy-dispersive X-ray spectroscopy. The nZVI-AC/Ni were used for the removal of dye RO 16 and the parameters affecting were discussed such as pH, adsorbent dosage, contact time and concentration of dye. To investigate the variables and interaction between them, an analysis of variance test was performed.

The characterization results show that the synthesis of nZVI-AC/Ni caused no aggregation of nanoparticles. The maximum dye removal efficiency of 99.45% occurred at pH 4, the adsorbent dosage = 0.1 gL-1 and the dye concentration of 10 mgL-1. Among various algorithms of feed-forward backpropagation neural network, Levenberg–Marquardt with mean square error (MSE) = 9.86 × 10^–22 in layer = 5 and the number of neurons = 9 was selected as the best algorithm. On the other hand, the MSE of the radial basis function model was 0.2159 indicating the good ability of the model to predict the percentage of dye removal.

There are two main innovations. One is that the novel nZVI-AC/Ni was prepared successfully. The other is that the optimized conditions were obtained for the removal of RO 16 dye from an aqueous solution. Furthermore, to the best of the knowledge, no study has ever investigated the removal of RO 16 by nZVI-AC/Ni produced.

The physical, biomechanical and chemical properties of the composite biodegradable films are examined by their chemical composition, structure, processing conditions and economics. Therefore, the purpose of the study was to develop standard composite biodegradable films by optimizing the process (drying time and temperature) and composition (whey protein concentrate; WPC and sodium alginate; SA).

Composite WPC–SA films were developed using the Box–Behnken design of response surface methodology (RSM), with individual and interactive effects of process variables on the response variables (quality characteristics). Three independent factors at three different levels (WPC: 5–7 g, SA: 0.1–0.5 g and drying temperature: 35°C–45°C) were evaluated for their effects on physical and biomechanical properties, namely, thickness, penetrability, moisture content, water vapor transmission rate (WVTR), density, solubility, transmittance and color variables. The results were analyzed using ANOVA. For each response, second-order polynomial regression models and resulting equations were developed.

The response surface plots were constructed for representing a relationship between process parameters and responses. All responses were optimized as the best and desired, namely, thickness (180 µm), penetrability (7.63 N), moisture (28.05%), WVTR (1.87 mg/m²t), solubility (36.12%), density (1.33 g/ml), transmittance (40.55%), L* value (52.50), a* value (0.35) and b* value (13.70). The regression models exhibited “good fit” of experimental data with a high coefficient of determination. A close agreement was found between experimental and predicted values.

These biodegradable films can be promisingly used in the food packaging system without the problem of disposability.

The composite films with proteins and polysaccharides can be developed, which have improved physical and biomechanical properties.

This tribological investigation aims to identify the effect of WS₂ deposition on the Al 6061 surface and optimize the dry sliding conditions to enhance the friction and abrasion wear behavior.

WS₂-deposited Al 6061-T6 surface was considered for this tribological investigation. The design of the experiment was based on the Box–Behnken design of the response surface methodology approach, which is used to evaluate the interaction effect of input parameters on friction coefficient (COF) and specific wear rate (SWR). The abrasive wear behavior of WS₂ deposition against SiC emery sheet was explored through pin-on-disc experimentation by varying applied load (L), sliding velocity (V) and distance (D). Using analysis of variance and regression model, COF and SWR were predicted.

Based on composite desirability criteria, multi-objective optimization was performed to minimize the COF and SWR. The obtained optimal sliding conditions are L = 10 N, V = 2 m/s and D = 949.49 m. The validation test results indicate that the experimental and predicted data are in good conformance. For optimized conditions, worn surface characterization was done using a scanning electron microscope with energy dispersive spectroscopy, and X-ray diffraction analysis was performed to ensure the formation of WS₂ phases on worn-out surfaces. Furthermore, a counter body surface with collected wear debris has been analyzed.

Almost the industries are now focused on a new surface modification technique, which improves the surface and tribological characteristics. This research work specifically relates the tribological effect of WS₂ deposition on an Al 6061-T6 surface through a novel electrical discharge deposition approach and optimizes the dry sliding conditions to improve the frictional and abrasive wear resistance.