Analysis Of Variance Table Research Articles

Using Regression Model to Study the Significant Differences in the Number of Covid-19 Infections

Multiple linear regression modeling was used to analyze Covid-19 data, which represents the number of infections in Iraq for the year 2019, in order to find occupational discrepancies between the dependent variable (age) and the independent factors under discussion. This was carried out in addition to the correlation value. Following statistical analysis, a significant correlation was discovered between the independent factors and the dependent variable, age. The age dependent variable and the research's independent variables are evidently different from one another in a substantial degree, as indicated by the analysis of variance table. This is in addition to comparing the number of infections between boys and females for each of the study's variables (blood pressure, oxygen rate, sugar rate, and D-Dimer), and we discovered that there are no appreciable variations in the quantity of infections between males and females based on the factorial experiment analysis.

Effect of energy density on quality and properties of 18Ni300 laser clad layers by laser cladding

By preparing the 18Ni300 laser clad layers at different energy densities, the pores of the laser clad layers were measured and analyzed by using the image method, and the effect of energy density on the porosity was explored by combining the experimental data. The experimental results show that the cross-sectional pores of the laser clad layers are regular in shape and do not intersect with each other, and most of the pores are gathered at the top edge of the fused cladding layer. The influence of process parameters on the morphology of the laser clad layer is obvious. The study shows that the influence of process parameters on porosity is in the order of laser power, scanning speed, and powder feeding voltage; combined with the analysis of variance table and response surface diagram, the interaction between the parameters is obvious, and combined with the change, it can achieve the purpose of reducing porosity. Porosity first increases and then decreases with the increase in the energy density, and the distribution of the energy density and porosity is divided into regions, and larger porosity can be avoided by selecting the regions. The hardness of the laser clad layer can be increased by the choice of energy density. The laser clad layer with good test results was observed to contain Co, α-Fe, and Fe7Ni3 intermetallic compounds. The microstructure is transformed from fine grains at the top to columnar dendrites at the bottom.

OPTIMIZATION OF MACHINING PARAMETERS ON THE SURFACE ROUGHNESS OF ALUMINUM IN CNC TURNING PROCESS USING TAGUCHI METHOD

In this research, Taguchi method is employed by focusing on spindle speed, feed rate, and depth of cut to optimize the CNC turning parameters for aluminum alloy 6063. The main goal of this study is to improve the surface roughness of the material. A L9 orthogonal array is used for experimentation, and the results are subsequently analyzed using ANOVA (Analysis of Variance). A spindle speed of 1300 rpm, a feed rate of 0.5 m/min, and a depth of cut of 1.5 mm are the optimal conditions to achieve the minimum average surface roughness (Ra). The main effect plot of the signal-to-noise (S/N) ratio provides significant evidence supporting the primary research goal. Furthermore, the ANOVA table reveals that spindle speed contributes 59.71%, feed rate contributes 29.80%, while depth of cut only contributes minimally at 0.72%. Based on the research findings, spindle speed and feed rate can be adjusted to control surface roughness. Both factors are highly significant in influencing the surface roughness of the material. The prediction equation from the linear regression analysis is Ra = 1.745 – 0.001024 spindle speed + 0.3000 feed rate – 0.0233 depth of cut. A coefficient of determination or R-squared value of 0.9115 indicates that the independent variables can explain 91.15% of the variation in the dependent variable. The experimental and predicted surface roughness (Ra) values have a predicted error percentage of 2.26%.

Response of Wheat Cultivars to Combinations of Chemical, Bio and Nano Fertilizers and their Effect on Vegetative Growth Traits

Wheat cultivar response to chemical, bio, and nano fertilizer combinations and their effect on vegetative growth traits were investigated in a field experiment with three replicates arranged in a split-plot in The Randomized Complete Block Design (RCBD) at Al-Qasim Green University during the 2022-2023 growing season. The main plots consisted of three different types of wheat, while the sub plots tested various fertilizer mixes. Wheat cultivars and fertilizer combinations both had a substantial effect on the attributes we measured, and there was also a significant interaction between the two, as shown in the analysis of variance table. The averages of wheat cultivars show that IPA 99 is superior to the other two cultivars by providing the tallest plants by an average of 104.21 cm, while Bohuth 22 provides the shortest times to 100% flowering (108.66 days) and physiological maturity (146.14 days). Baghdad variety yielded the highest mean The trait states that the flag leaf area is 42.94 cm2, the leaf chlorophyll concentration is 49.51 Spad, and there are 449.52 tillers per square meter. The average fertilizer combinations showed that plant height was best at 98.96 cm, flag leaf area at 44.47 cm2, leaf chlorophyll content at 50.08 Spad, and tiller density at 417.56 tillers m-2 with the fertilizer combination of 50% compound fertilizer + 50% bio-fertilizer + 50% nano-fertilizer. However, the optimal results were achieved using the specified fertilizer compound with nano fertilizer, which required only 109.88 days to achieve 100% blooming and 147.33 days to reach physiological maturity. With a mean flag leaf area of 47.73 cm2, the Baghdad cultivar emerged victorious in the study of cultivar by fertilizer combination interactions. When using a fertilizer mixture of 50% compound fertilizer, 50% bio-fertilizer, and 50% nano-fertilizer, the chlorophyll content of the leaves was 53.76 spad and the number of tillers was 470.67 strands m-2.

Optimization of Green Synthesis Parameters of Silver Nanoparticles with Factorial Design for Dye Removal

In this study production of silver nanoparticles (AgNPs) from collard greens were optimized by the design of experiments (DOE). A 24 full factorial design was employed to evaluate the effects on two responses. The optimized values for AgNP production were 1:7 leaf to water, 1:4 extract to AgNO3, 5 molar AgNO3, and a leaf size of <1 mm. For dye removal efficiency, the optimized values were changed to 1:15 of leaf to water and 1:10 of extract to AgNO3, while the other two parameters remained the same. SEM (scanning electron microscopy) showed that optimizing the process for dye removal led to smaller AgNP production with increased surface area, resulting in higher absorbency. ANOVA (analysis of variance) tables were used to interpret each parameter's main and effects on interaction. Additionally, reaction rate kinetics were estimated, and dye removal showed a slightly higher R-square of pseudo second-order than NP production, which fits the pseudo first-order reaction model.

Exact neutrosophic analysis of missing value in augmented randomized complete block design

The augmented randomized complete block design (ARCBD) is widely used in plant breeding programs to screen numerous new treatments. The error variance is estimated based on the replicated control treatments run over a randomized complete block design and is used to test the new treatments that are administrated each once in the extended units of the blocks. However, one or more observations corresponding to the control treatments may be missed in experiments, making difficulties, e.g., biased estimates. An approximate common approach to deal with this problem is the imputation of the estimated value which is with some uncertainties. Moreover, in real-life experiments, there are more sources of uncertainty that cause conflict-indeterminate, vague, imprecise, and erroneous data that increases the complexity of the analysis. In this paper, an exact scheme is utilized to deal with a missing control treatment in ARCBD. To overcome the problem of indeterminacies in data, a novel neutrosophic analysis approach is proposed. Specifically, the problem of a missing value in an ARCBD for an uncertain environment is resolved analytically by considering an augmented incomplete block design in the framework of neutrosophic statistics so-called neutrosophic augmented randomized complete block design (NARCBD). In this approach, by proposing the neutrosophic model, the neutrosophic estimations as well as the mathematical neutrosophic adjusted sums of squares are derived and the analysis of variance table is provided. The new model is applied to the neutrosophic genotype data example of safflower and assessed by a simulation study. Furthermore, a code in the R software was written to analyze the data based on the proposed approach to fill the calculation gap for data analysis in NARCBD with a missing value. In light of the results observed, it can be concluded that the neutrosophic exact proposed method performs better than the classic in the presence of uncertainty.

Demystifying omega squared: Practical guidance for effect size in common analysis of variance designs.

Omega squared (ω^2) is a measure of effect size for analysis of variance (ANOVA) designs. It is less biased than eta squared, but reported less often. This is in part due to lack of clear guidance on how to calculate it. In this paper, we discuss the logic behind effect size measures, the problem with eta squared, the history of omega squared, and why it has been underused. We then provide a user-friendly guide to omega squared and partial omega squared for ANOVA designs with fixed factors, including one-way, two-way, and three-way designs, using within-subjects factors and/or between-subjects factors. We show how to calculate omega squared using output from SPSS. We provide information on the calculation of confidence intervals. We examine the problems of nonadditivity, and intrinsic versus extrinsic factors. We argue that statistical package developers could play an important role in making the calculation of omega squared easier. Finally, we recommend that researchers report the formulas used in calculating effect sizes, include confidence intervals if possible, and include ANOVA tables in the online supplemental materials of their work. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Optimization of Biofuel Production Process Using Design of Experiments (Doe)

This study focuses on optimizing the process of biofuel production from citrus peel using the Design of Experiments (DOE) technique. This study aims to determine the optimal values for the variables that have a significant impact on the production of biofuel. The variance within and between data groups was determined using the analysis of variance (ANOVA) table. The ANOVA table shows how much of the response variable's variation (biofuel production) can be explained by the independent variables (A, B, C, D, E, AB, AC, AD, AE, and BJ) and how much is caused by random error. The ANOVA table comprises of three primary parts: the F-statistic, the p-value, the df, the mean square (MS), the source of variation, and the sum of squares (SS). The wellspring of variety alludes to the beginning of the information variety, which can be either the lingering or the model. The amount of squares estimates the information's changeability, with the absolute amount of squares addressing the amount of the squared deviations of the genuine qualities from the mean worth. The residual is the sum of the squared deviations from the predicted values of the actual values, while the model's sum of squares is the sum of the squared deviations from the mean of the predicted values. The model has 10 degrees of freedom (the number of independent variables) and the residual has 4 degrees of freedom (the number of observations minus the number of independent variables). These degrees of freedom represent the number of independent pieces of information used to estimate a parameter. The mean square, which indicates the typical amount of variation for each variation source, is calculated by dividing the sum of squares by the degrees of freedom. The degree to which the model explains the variation in the data is indicated by the F-statistic, which is the ratio of the model's mean square to the residual's mean square. The probability of obtaining an F-statistic that is as large as the one observed if the null hypothesis is true is represented by the p-value. The independent variables' insignificant impact on biofuel production is the null hypothesis in this instance. The model's p-esteem in this study is under 0.05, demonstrating that the free factors essentially affect biofuel creation and that the model is genuinely huge. In addition, the model is significant because the F-statistic is relatively large in comparison to the F-distribution for the 10 and 4 degrees of freedom, respectively. The estimated coefficients for the linear regression model used to investigate the production of biofuel from citrus peel can be found in the ANOVA coefficients table. The table provides a list of the intercept and independent variables' coefficients, standard errors, t-values, and p-values. When all of the independent variables are zero, the intercept has a coefficient of 0.0672, indicating the estimated value of the response variable. The fact that the intercept does not differ significantly from zero is supported by the fact that its p-value is not significant. The fact that the coefficients of the independent variables A, E, AC, AD, AE, and BJ are not statistically significant indicates that these variables have little impact on the response variable. On the other hand, the positive coefficients and significant p-values of the independent variables B and C suggest that an increase in their values could result in an increase in the production of biofuel from citrus peel. In conclusion, the key variables that influence the production of biofuel from citrus peel have been identified thanks to the use of the Design of Experiments (DOE) method. According to the findings of this study, an increase in the production of biofuel from citrus peel may result from an increase in the values of the independent variables B and C. The development of environmentally friendly energy sources and the optimization of biofuel production processes will benefit greatly from these findings

The Response of Fig to Foliar Application of GA Combination (GA4+GA7) and Nutrition Liquid PRO-SOL on Some of the Growth Parameters

For the growing season (25 February – 30 October 2021), the College of Agriculture at Tikrit University conducted an experiment to convert the wooden canopy to a lath house. Spraying fig seedlings with a Gibberellin acid mixture and Pro-sol nutritional solution allowed researchers to examine the effects on the seedlings’ vegetative development characteristics and chemical content at 0, 25, and 50 mg.L-1. Plants were exposed to three different PRO-SOL nutritional solution concentrations ( 0, 75 and 150 mg.L-1.) There were three separate dates for the addition and distribution: the first on 15 March 2021, the second 15 days later, and so on for the third. A completely randomized block design was used for this study (RCBD). S.A.S., a pre-made statistical program, was used to evaluate the components and their interactions, and the findings were examined using an analysis of variance table. At the 0.05 probability level, the L.S.D. was determined to be the minimal detectable difference. Here is a quick rundown of the study’s findings: The growth rate of the plant, the number of leaves, the diameter of the stem, the number of new branches, the Chlorophyll, Carbohydrate, Nitrogen, and the ratio of Carbohydrates to Nitrogen, Protein, Potassium, and Phosphorous content of the leaves, all reached 46.89 cm, 13.44 sheets after being sprayed with a Gibberellin mixture, especially at the level of 50 mg.L-1 (GA2). One seedling, 16.00 mm in height, with 3.89 limbs. Seedling-1 had a SPAD value of 24.38, and its corresponding percentages were 2.69, 1.26, 2.36, 0.16, and 1.38. PRO-SOL 150mg, which is the maximum recommended dosage. The rate at which the plants in the study increased in height, number of leaves, stem diameter, number of new branches, chlorophyll content, carbohydrates, nitrogen, and the ratio of carbohydrates to nitrogen, protein, and potassium all increased significantly in response to L-1 (Pr2). 50.33 inches, or 14.44 sheets, of phosphorus. One seedling, 17.3mm in diameter, with 4.67 branches. Seedling-1 had the lowest average for the aforementioned characteristics in the comparative treatment (25.38 SPAD units, 3.26 percent, 1.39 percent, 2.10 percent, 0.20 percent, and 1.58 percent). The binary interaction between the Gibberellin mixture and nutrient solution Pro-sol showed significant differences, especially the GA2 Pr2 treatment, which gave the highest rates for all studied traits.

Application of Analysis of Variance and Taguchi Method for the Identification of Key Parameters and their Impact on Sound Measurement

This work is done to measure the sound density and improve its quality. And this is done bymeasuring the sound intensity in different situations and surroundings. To determine the effect of significantparameters throughout the sound measurement. The results of the various experiments of the soundmeasurement are viewed by applying some tools in Design of Experiments (DOF), Such as Taguchi methodand Analysis of Variance (ANOVA) [1]. In these experiments there are four factors considered, they aretemperature, distance, wind speed and angle of the sensor. These factors were chosen because they are themost parameters that can affect the quality of the sound. The results show that the factor speed is the mostsignificant factor with percentage 1.79% according to the ANOVA table. Therefore, this work is consideredas an effective tool to find the important parameters and their effect in sound measurement

Growth Response and Production of Sweet Corn (Zea mays L. saccharata Sturt) Perkasa F1 Variety with Application of POC and Humic Acid

The purpose of this study was to determine the growth response and production of sweet corn (Zea mays L. saccharata Sturt) variety Perkasa F1 with the application of LOF and humic acids. This research was carried out in March-June 2022 at a location in Donganti Village, Plosoklaten District, Kediri Regency with an altitude of ± 60 meters above sea level and a pH of 6.8. The experimental method used is RCBD. The first factor is LOF (P) consisting of 5 levels: control, 50 ml / l, 75 ml / l, 100 ml / l, 125 ml / l. The second factor is humic acids (A) consists of 4 levels: control, 5 kg / ha, 10 kg / ha, 15 kg / ha. Data analysis using analysis of variance tables (ANOVA) by advanced test of Least Significant Difference (LSD) 5%. The results showed that the application of the combination of LOF and humic acids gave a very significant effect on plant height of 35 DAP, and stem diameter of 35 DAP and also gave significant effect on the number of leaves of 35 DAP, stem diameter of 35 DAP, weight of cobs with cornhusk. The application of humic acids at a dose of 10 kg/ha shows significant effect on the ingratiating levels.

Performance enhancement of selective layer coated on solar absorber panel with reflector for water heater by response surface method: A case study

In solar thermal applications, the performance of a solar absorber panel with a reflector is critical. In sense, different absorbers are used to enhance thermal efficiency. In addition to this, various coatings on solar absorber panels are introduced, and the performance of the same coated panels are examined with experimental study by design of experiment concept. For the reason, this work utilized the black-chrome coating (BC) and nickel-cobalt-coating (Ni-Co) on copper solar absorber panel. The reflectors were also used to maximize the incident solar radiation on the absorber. In this experiment the process variables are flow rate, collector angle, and reflector angle and the thermal efficiency of solar panel is the response. The response surface methodology with Box Behnken design is used to collect the experimental data from experimental setup. The collected data from designed experiment are analyzed by using Analysis of Variance Table (ANOVA). From this the coating on the absorber panel and reflectors are improved the thermal efficiency up to 89.3% of the Black – Chrome solar flat plate collector than Ni-Co panel.

Analyze and Optimize the Welding Parameters of the Process by Pulsed Tubular Wire (FCAW - Flux Cored Arc Welding) Based on the Geometry of the Weld Beads Resulting from each Test

Abstract: This study aimed to analyze and optimize deposition welding parameters using a pulsed tubular wire process (FCAW - Flux Cored Arc Welding), where the influence variables adopted were the average current, the pulsation frequency, the welding speed and the contact-tip-workpiece distance, with each variable being tested at three different levels. The geometric characteristics evaluated, that is, the response variables, are width, reinforcement, penetration, reinforcement area, penetration area and dilution. The geometric characteristics evaluated, that is, the response variables, are the width, the reinforcement, the penetration, the reinforcement area, the penetration area, the contact-tip-workpiece distance and the dilution. In order to achieve the proposed objective, statistical techniques were used as analysis tools, and, in the first phase, the robust design method (Taguchi) was used to establish which combinations of parameters would be performed in each test, providing us with an L9 matrix. In a second phase, analysis of variance tables (ANOVA) were constructed to select the most significant parameters.

Experimental Study on Reinforced Aluminium Metal Matrix Composites with B<sub>4</sub>C through Different Techniques

Recently, aluminum alloys are extensively used in automobile and aeronautical industries due to its low density and excellent mechanical properties. The aim of this research work is to focus on develop an aluminum matrix composite reinforced with boron carbide particulates under different weight percentages by squeeze casting route. To obtain better results, it is essential to control the process variables involved in the process. The primary work focused to optimize the process variables involved in the fabrication of the composites using full factorial design. The experiments were carried out with various input parameters like squeeze pressure of 50, 100 and 150Mpa, melting temperature of 700, 750 and 800°C and weight fraction of reinforcement of 6, 8 and 10% using L27 orthogonal array. The significant parameters were identified by analysis of variance table and regression analysis was used to model the mathematical relationship for obtaining better mechanical properties. Final results reveal that, mechanical properties of 218VHN hardness and 412MPa tensile strength had been obtained based on the optimum combination levels. Also AA7075-B4C composites produced through this route with enhanced properties could be used as an alternative material for high strength structural applications like connecting rod, control arms, steering knuckle and other parts.

Razvoj i ocena performansi miksera (mešača) sa motorom za hranu

A tumble barrel food /feed mixer was designed and fabricated. It has a volumetric capacity of 0.33 m3 . The tumble barrel mixer consists of a hopper, a stainless steel barrel with baffles. It is mounted on a steel framework and driven by a shaft connected to stirrers inside the baffles. The baffles are alternatively placed in the barrel in such a way that they do not touch the stirrers during operation. The shaft is driven by a 3HP (2,25 kW) variable speed electric motor. Performance tests were conducted on the machine after fabrication using the ASAE (R2006) test standards, and also Completely Randomized Design (CRD). Three speeds of the mixer, 100,150 and 200 rpm (min-1 ) ( and four mixing times of 5,10,15 and 20 minutes were studied as they affected the Degree of Mixing (DM) of ground and shelled corn samples in the mixer. Results obtained showed, there was an increase in the degree of mixing as the speed of the machine increased from 100 to 200 rpm (min-1 ). Also the degree of mixing increased as the time of mixing increased from 5mins to 20 minutes for the three speeds studied. From the Analysis of variance tables, the calculated F-values were very much higher than the tabulated values at 5% probability. These indicate a high significance of the effect of speeds of mixing on the degree of mixing of the tumble barrel mixer. The speed of 150 rpm (min-1 ) gave the highest effect in the tumble mixer. From the difference of means tables, there were significant differences in the degree of mixing for 100 and 150 rpm (min-1 ) speeds for all the different time of mixing durations. However, in the 200 rpm (min-1 ) speed, there was no significant difference in the DM between the 15 to 20 minutes mixing time duration.

Studies of kerf width and surface roughness using the response surface methodology in AA 4032–TiC composites

A substantially developed machining process, namely wire electrical discharge machining (WEDM), is used to machine complex shapes with high accuracy. This existent work investigates the optimization of the process parameters of wire electrical discharge machining, such as pulse on time ( Ton), peak current ( I), and gap voltage ( V), to analyze the output performance, such as kerf width and surface roughness, of AA 4032–TiC metal matrix composite using response surface methodology. The metal matrix composite was developed by handling the stir casting system. Response surface methodology is implemented through the Box–Behnken design to reduce experiments and design a mathematical model for the responses. The Box–Behnken design was conducted at a confident level of 99.5%, and a mathematical model was established for the responses, especially kerf width and surface roughness. Analysis of variance table was demarcated to check the cogency of the established model and determine the significant process. Surface roughness attains a maximum value at a high peak current value because high thermal energy was released, leading to poor surface finish. A validation test was directed between the predicted value and the actual value; however, the deviation is insignificant. Moreover, a confirmation test was handled for predicted and experimental values, and a minimal error was 2.3% and 2.12% for kerf width and surface roughness, respectively. Furthermore, the size of the crater, globules, microvoids, and microcracks were increased by amplifying the pulse on time.

Effect of Experimental Blocking on the Suppression of Spatial Dependence Potentially Attributable to Physicochemical Properties of Soils

One of the basic principles of experimental design is blocking, which is an important factor in the treatment of the systematic spatial variability that can be found in the edaphic properties where agricultural experiments are conducted. Blocking has a mitigating or suppressing effect on the spatial dependence in the residuals of a model, something desirable in standard linear modeling, specifically in design models. Some computer programs yield a p value associated with the blocking effect in the analysis of variance table that in many cases has been incorrectly used to discard it, and although it may improve some properties of the analysis, it may affect the independence assumption required in several models. Therefore, the present research recommends the use of the H statistic associated with the corrected blocking efficiency to show the role of blocking in modeling with the incorporation of an additional advantage rarely considered related to the suppression or mitigation of spatial dependence. With the use of the Moran index, the spatial dependence of the residuals was studied in a simple factorial design in a completely randomized and blocking field layout, which evidenced the advantages of blocking in the mitigation or suppression of the spatial dependence despite the apparently little or no importance it seems to show in the analysis of variance table.

Assessment of Bioanalytical Method Validation Data Utilizing Heteroscedastic Seven-Point Linear Calibration Curves by EZSTATSG1 Customized Microsoft Excel Template.

Bioanalytical methods developed in accredited forensic toxicology laboratories need to be validated according to the ISO/IEC 17025 standards to demonstrate that a method is fit for the intended use. The evaluation of the validation data can be a time-consuming process without a streamlined procedure on a common platform or the aid of a specific software package. The objective of this work was to develop a Microsoft (MS) Excel (Redmond, WA, USA) template, which can rapidly generate all the required numerical and statistical validation results of a quantitative bioanalytical assay with minimal data entry and to provide documented traceability of the validation data directly to the instrument raw data. Evaluation of method validation data can be done easily by taking advantage of the power of statistical tools available within Excel. The three key features of the template were the development of six pertinent weighted linear calibration models, the variance in instrument response as a function of concentration and integrated one-way analysis-of-variance (ANOVA) tables. None of the ANOVA tables in this template need to be recreated whenever the source data changes, which is a major time savings when a method contains several dozen analytes. It takes ∼60 minutes per analyte to enter all the instrument raw data manually from the chromatograms. The final method validation results are summarized in a two-page validation summary report, whereas the associated data tables and graphs are presented in an additional 65 pages of digital information, which can be saved for electronic records using portable document format (PDF). This EZSTATSG1.xltm customized MS Excel method validation template and a completed PDF example are being provided as downloadable files in the Supplementary data link to offer an option to the scientific community for expediting the evaluation of validation data.

Investigation of effect of process variable on dimensional accuracy of FDM component using response surface methodology

Purpose Nowadays, rapid prototyping is emerging as end use product in low volume. The accuracy of the fabricated components depends on various process parameters. Process parameters used in this investigation are layer thickness (150, 200 and 250 µm), infill pattern (linear, hexagonal and star fill), raster angle (0°, 45° and 90°) and infill density (40, 60 and 80%). Linear and radial dimension of knuckle joint are selected for the response factor. Design/methodology/approach The experiments are design by using response surface methodology (RSM). Four design variables at three levels are used to examine their influence on percentage error in linear dimension and radial dimension of the component. A prototype Knuckle joint is selected as component. Minitab-14 software is used for the design of experiments. Findings Experimental measure data is analyzed by using “smaller is better” quality characteristics. A regression model for the forecasting of percentage error in linear and radial dimension is developed. The developed model is within precision range. The optimum level of process for linear and radial dimensions are obtained: layer thickness of 150 µm, Infill pattern of linear, Raster angle of 90° and infill density of 40%. Research limitations/implications It proves that both the mathematical model is significant and can be able to approximate the desired output value close to the accurate dimensions. While comparing the calculated F-values for both linear and radial dimension with the standard table (F-table, 0.05), it is found that at the given set of degree of freedom the standard F-values (6.61) is lower for that regression, linear, square and interaction source of the predicted model, for which p-values have already less than 0.05. It is desirable for significant process parameters. Practical implications The dimensional accuracy with respect to average percentage error of FDM produced knuckle joint is successfully examined. The effect of process parameters, namely, layer thickness, infill pattern, raster angle and infill density on average percentage error was investigated by RSM and analysis of variance table. Social implications The novelty of this work lies in the fact that only few studies are available in archival literature related to influence of these process parameters on percentage error in linear and radial dimension for Polycarbonate (PC) material. Originality/value The novelty of this work lies in the fact only few studies are available in archival literature related to influence of these process parameters on percentage error in linear and radial dimension for Polycarbonate (PC) material.

Identification of the main factors in the 3-D simulation of laser-induced thermal damage in choroidal melanomas

Computational numerical simulation is a valuable tool for studying processes that involve living tissues, since it is not invasive, safer, and cheaper than in vivo experiments. The study of heat transfer within human eyes raises special interest given the numerous existing treatments that involve exposing the eye to external heat sources. Furthermore, there is not much blood flow in most tissues of the eye, which means there is a limited cooling effect and a higher chance of severe thermal damage. Choroidal melanomas are malignant ocular tumors that arise in the choroid, that can be treated by a variety of thermal procedures, among other techniques. Transpupillary thermotherapy (TTT) is one of these treatments, which consists of irradiating the tumor with diode laser, thus heating the tumor within a specific temperature range. In our previous studies, the influence of some parameters on the temperature and thermal damage within the human eye following TTT treatment was studied– the parameters were Vitreous Humor (VH) viscosity, laser output power, and the size of the tumor. Since the data available that are needed for mathematical modeling are scarce and uncertain, the quality of the results was also uncertain. In this study, the main goal was to perform sensitivity analyses to identify which thermal-physical properties significantly influence the results of simulations. A 3-D model of the human eye with a small choroidal melanoma was used. The Navier-Stokes equations were included to consider natural convection inside the VH. A numerical strategy was used to represent tumor shrinkage due to thermal damage. A fractional factorial design of experiments was adopted, and the results were analyzed by building ANOVA (analysis of variance) tables for each case. Our results indicate that the radiation absorption coefficient for the tumor and for the choroid are the only parameters that significantly influence the results among those analyzed ones. This suggests that the uncertainties of most thermophysical properties do not substantially harm the predictions of the simulations. Also, this reinforces that the level of melanin on the tumor should be carefully assessed in order to decide the treatment protocol, since this level is directly related to the absorption coefficient.