Factorial Experimental Design Method Research Articles

The importance of factorial design on the optimization of biosensor performance: immobilization of glucose oxidase as a case study.

Conventionally, the optimization of glucose biosensors is achieved by varying the concentrations of the individual reagents used to immobilize the enzyme. In this work, the effect and interaction between glucose oxidase enzyme (GOx), ferrocene methanol (Fc), and multi-walled carbon nanotubes (MWCNTs) at different concentrations were investigated by a design of experiments (DoE). For this analysis, a factorial design with three factors and two levels each was used with the software RStudio for statistical analysis. The data were obtained by electrochemical experiments on the immobilization of GOx-Fc/MWCNT at different concentrations. The results showed that the factorial DoE method was confirmed by the non-normality of the residuals and the outliers of the experiment. When examining the effects of the variables, analyzing the half-normal distribution and the effects and contrasts for GOx-Fc/MWCNT, the factors that showed the greatest influence on the electrochemical response were GOx, MWCNT, Fc, and MWCNT:Fc, and there is a high correlation between the factors GOx, MWCNT, Fc, and MWCNT:Fc, as shown by the analysis of homoscedasticity and multicollinearity. With these statistical analyses and experimental designs, it was possible to find the optimal conditions for different factors: 10mMmL-1 GOx, 2mgmL-1 Fc, and 15mgmL-1 MWCNT show a greater amperometric response in the glucose oxidation. This work contributes to advancing enzyme immobilization strategies for glucose biosensor applications. Systematic investigation of DoE leads to optimized immobilization for GOx, enables better performance as a glucose biosensor, and allows the prediction of some outcomes.

Experimental study on Corn Straw Fiber (CSF) toughening EPS concrete

The natural Corn Straw Fiber (CSF), it has the advantages of light weight, high strength, good toughness and renewable, can delay the cracking and improve the toughness of cement-based materials. The effects of different mass fractions of CSF and Expanded-Polystyrene (EPS) particles on the compressive strength, flexural strength, splitting tensile strength and their failure modes, load-displacement curves and toughness of EPS concrete were analyzed by full factorial experimental design method. The compressive toughness index (I0, I1) and fracture energy (Gf) were defined to evaluate the effect of CSF on toughening EPS concrete. The results show that the addition of CSF can improve the compressive strength, flexural strength and cracking toughness of EPS concrete to a certain extent. The maximum compressive strength occurred in the E1F3 specimen with a CSF content of 3 % in Group I, which was 1.12 MPa, and the improvement rate was also the highest among the four groups, reaching 69.7 %. The compressive toughness index I1 also reached its maximum in the E1F3 specimen; The maximum flexural strength occurred in the E3F4 specimen with a 4 % CSF content in Group III, which was 0.885Mpa, with the highest improvement rate of 127.38 %. The maximum fracture energy Gf reached 0.827 in the E3F4 specimen. However, another additive, EPS particles, did not significantly improve the physical and mechanical properties of concrete. According to the SEM images and toughening mechanism analysis, it was discovered that tight adhesion between EPS particles and CSF with cement matrix, and the failure mode of CSF was tensile fracture, which could maximize the effect of CSF high tensile toughness. On the basis of mechanical properties and toughening effect, the relationship formulas between variable factors and strength, toughness index were fitted, and the optimal content of EPS and CSF were determined to be 1.3 % and 3 %, respectively.

Factorial experimental design based on multiple factors for sensors and actuators development

Factorial experimental design based on multiple factors for sensors and actuators development

Study on the relationship between structure and moisturizing performance of seamless knitted fabrics of protein fibers for autumn and winter

Abstract With dry weather and low humidity in autumn and winter, human skin is usually prone to dryness, even leading to itchy skin and other problems, so it is important to do a good job of skin moisturizing. The fabrics produced by using protein fiber have a certain moisturizing effect on human skin. Five types of yarn including collagen fiber, cheese protein fiber, silkworm pupa protein fiber, cashmere protein fiber, and viscose are chosen as veil materials, while nylon/spandex composite fiber is chosen as inner yarn material. Three fabric structures including the weft plain stitch, 1 + 1 mock rib, and 1 + 3 mock rib are selected for the study. Based on the full factorial experimental design method, 15 samples of seamless knitted fabrics are produced using a circular knitting machine. In order to investigate the effects of different veil materials and fabric structure of seamless knitted fabric on skin moisturizing performance, the skin moisture content test and the trans-epidermal water loss test were carried out before and after the fabric samples were wrapped around the skin of 20 participants. The results show that both the veil materials and the fabric structure have significant effects on the skin moisture content. The use of collagen yarn as the veil material and 1 + 1 mock rib as the fabric structure results in better moisturizing effects on human skin. In terms of the trans-epidermal water loss test, the fabric structure has significant effects on the results, while the veil material has no significant effect on it. However, the value of trans-epidermal water loss of the fabric with protein yarn is smaller than that of the fabric with ordinary viscose. Therefore, using cheese protein yarn as the veil material and 1 + 1 mock rib as the fabric structure results in a smaller trans-epidermal water loss value.

Machining efficiency and geometrical accuracy on micro-EDM drilling of titanium alloy

ABSTRACT In the current study, micro-electric discharge drilling (µEDD) is conducted on a titanium grade 2 alloy using a tungsten carbide (WC) tool electrode of 496 µm diameter. Capacitance, voltage, and feed rate are selected as machining variables to conduct the experiments based on the full factorial experimental design method. Overcut, material removal rate (MRR), circularity, and hole taper are considered as performance measures. Furthermore, overall evaluation criteria (OEC) is utilized for multiple-objective optimization by allotting varying and equal weight percentages to each response measure. The results of OECs are compared with a revolutionary heuristic multi-objective genetic algorithm (MOGA), resulting in a similar optimal parametric combination and close response measures are obtained. Micrographic investigation demonstrates that at lower capacitance and voltage levels, there is less burr formation, recast layer, and circularity error. Moreover, FESEM and EDS analyses are employed to investigate the machined surface topology and elemental composition respectively.

Peningkatan pH dengan Pemberian Bahan Organik pada Pengelolaan Air Asam Tambang Menggunakan Metode Passive Treatment

Mining is the process of extracting beneficial minerals from the surface of the earth that have an impact on the formation of acid mine drainage (AMD). One method of passive AMD management is passive treatment. This study used the Nested Factorial Experiment Design method. The types of organic matter used were empty fruit bunch oil palm (EFB) and cow dung, with doses of 0 Mg ha-1 (control), 50 Mg ha-1, 100 Mg ha-1, 150 Mg ha-1 and 200 Mg ha-1. Each treatment was three repeats so that 30 units of experimental units were obtained. The pH value of AMD in the untreated (control) reactor was 3.67. The initial reaction (pH) of AMD (0 days) with EFB application at a dose of 50 – 200 Mg ha-1 ranged from 3.63 – 4.28 and the initial pH of cow dung was 3.84 – 4.13. The reaction (pH) of the 1st to 4th weeks of AMD after adding EFB organic matter at a dose of 50 – 200 Mg ha-1 show a pH range (6.38 – 7.59) and cow manure at a dose of 150 – 200 Mg ha-1 show a pH (6.09 – 7.01). The conclusion are that the application of EFB organic matter on constructed wetland media for 4 weeks had a very real effect on increasing the pH of the AMD dose of 100 – 200 Mg ha-1 while cow dung 150 – 200 Mg ha-1 are the most effective against increasing pH.

Prediction of large deflection of chromium nanobeams using a hybrid meta-heuristic algorithm

In this paper, the prediction of large deflection of the chromium nanobeams has been studied using hybrid meta-heuristic methods. At first, using the full factorial design of experiment method, 100 experiments were designed in which the length and force applied to the nanobeams were considered as input variables at 25 and 4 levels, respectively. Also, the deflection of the nanobeam was considered as the output. The nanobeam’s deflection was estimated through the regression models by first, second, and third-order equations, respectively. The preliminary results demonstrated that the third-order regression model predicts the deflection with high accuracy and its error is less than the other models. In the following, to reduce the number of required experiments, two levels of the applied force (8 and 11 nN) were used to predict the deflection. Accordingly, the new equations were used for interpolation and extrapolation of the deflection in other levels of forces i.e., 9.5 and 12.5 nN. Finally, the coefficients of both third-order equations obtained by 4 and 2 levels of forces were optimized using the meta-heuristic algorithms i.e., Big Bang-Big Crunch (BBBC) and Ray Optimization algorithm (ROA). Comparing the results showed that by using the BBBC and RAO methods, the error value decreases by 10% and 20%, respectively. The results of this paper showed that the deflections of the chromium nanobeam can be estimated by algebraic formulas with high accuracy and fewer experiments, time, and cost.

Factorial Design of Experiment Method to Characterize Bioprinting Process Parameters to Obtain the Targeted Scaffold Porosity

Factorial Design of Experiment Method to Characterize Bioprinting Process Parameters to Obtain the Targeted Scaffold Porosity

The Effect of Aluminium Injection Parameters on the Mechanical Properties of the Material Produced by High Pressure Die-Casting

Aluminium is one of the basic materials used in many sectors, especially in automotive, defence and aviation. Generally, aluminium parts are manufactured by using injection molding methods in many sectors, such as automotive, etc. Injection presses that are used for die-casting material have a lot of parameters, affect the molded parts’ properties. In this study, the effect of injection parameters on the mechanical properties was investigated. Firstly, a test part that is shaped currently on the injection press machine in a sector was found out. An aluminum alloy, named Al〖Si〗_12 Cu (EN AC 47000), that is used widely in die-casting techniques was preferred. Three injection parameters, such as, injection velocity (m/s), time of the mold opening (s) and molten metal temperature (0C), were selected. And all works were planned with the full factorial experimental design method. Thus, the test parts were manufactured by using an injection molding machine. Moreover, many tests, such as hardness and tensile, were performed on the test parts to investigate the effect of injection parameters on the mechanical properties of the material. The tests were analysed with the full factorial and ANOVA method. As a results of the analysis, the highest hardness value was obtained as 85 HB when the molten metal temperature was 750 ℃, the injection velocity was 1.3 m/s, the mold opening time was 10 s, and the highest breaking strength was obtained as molten metal temperature 725 ℃, injection velocity 4 m/s, when the mold opening time was 12 s was found to be 264 MPa.

Experimental optimization of tribological properties of aluminum bronze alloys made by the forging method

Aluminum bronze alloys produced by various methods are preferred materials in many fields of the industry due to their high wear resistance and good sliding properties. This study investigated the tribological properties of aluminum bronze alloys produced by forging from Cu, Al, Fe, and Mg elements. Dry sliding wear tests were carried out on a pin-on-disc wear device. Three tribological properties, wear, friction coefficient, and temperature of aluminum bronze alloys were investigated. Experimental studies were carried out for different loads, sliding speeds, and sliding ways. The factorial experiment design method was applied in the MINITprogram. A SEM visualized the samples microstructures to examine the material wear characteristics. As a result of the study, it was deter-mined that the applied load, sliding speed, and sliding way were effective parameters on the amount of wear and friction coefficient. The maximum amount of wear was 0.352 mg at 100 N load, 3 m/s sliding speed, and 3000 m sliding way conditions. The maximum temperature between materials under these conditions is 299 oC. The minimum amount of wear was obtained when 25 N load, 1 m/s sliding speed, and 1000 m sliding way were applied.

The Influence of Diamond Burnishing Process Parameters on Surface Roughness of Low-Alloyed Aluminium Workpieces

This study describes the determination and optimization of burnishing process parameters and their effects on surface roughness of EN AW-2011 aluminium alloy workpieces. The process has a low environmental load and the chip-free burnishing process improves the integrity of the machined surface, but to achieve this, the different burnishing parameters, for example, burnishing force, feed rate, speed and number of passes, must be properly defined according to the material of the workpiece. In our research, a full factorial experimental design method is used to plan and carry out the experiments and to determine the most appropriate parameter range for this material quality.

Control Strategies of Plastic Biodegradation through Adjusting Additives Ratios Using In Silico Approaches Associated with Proportional Factorial Experimental Design.

Plastics, as a polymer material, have long been a source of environmental concern. This paper uses polystyrene plastics as the research object, and the relative contribution of each component of plastic additives to plastic degradation is screened using the molecular dynamics method. The factorial experimental design method is combined with molecular dynamics simulation to adjust the additive composition scheme, analyze the mechanism of interaction between the additive components, and select the plastic additive combination that is most readily absorbed and degraded by microorganisms. Seven different types of plastic additives, including plasticizers, antioxidants, light and heat stabilizers, flame retardants, lubricants, and fillers, are chosen as external stimuli affecting the biodegradability of plastics. Using molecular dynamics simulation technology, it is demonstrated that plastic additives can promote the biodegradability of plastics. The factorial experimental design analysis revealed that all plastic additives can promote plastic biodegradation and plasticizer is the most favorable factor affecting plastic degradation, that hydrophobicity interactions are the primary reason for enhancing plastic degradation, and that screening No. 116–45 (plasticizer A, light stabilizer C, flame retardant E) is the most advantageous combination of biodegradable plastic additives. The plastic biodegradation effect regulation scheme proposed in this study is based on optimizing the proportion of additive components. To continue research on aquatic biodegradable plastics, the optimal combination of plastic components that can be absorbed and degraded by microorganisms is recommended.

Improving the poor texture and technological properties of chicken wooden breast by enzymatic hydrolysis and low-frequency ultrasound.

Wooden breast (WB) is a recurrent myopathy in fast‐growing birds, which alters the appearance, functionality, and the texture of the breast muscle. The objectives of this study were (i) to evaluate the effect of a combined use of papain enzyme and ultrasound on the texture of WB chicken using response surface methodology and (ii) to assess the effect of marinating on the quality of WB chicken meat. Full factorial experimental design method was used to obtain the ideal conditions to soften the WB meat. The independent variables were the concentration of papain (0.1%–0.3%) and the time in ultrasonic bath (10–30 min); shear force (SF) was the dependent variable. The optimum results were obtained at a concentration of 0.2% papain and 20 min on ultrasound. Papain enzyme had a great influence on the texture of WB meat, reducing its hardness. However, the effect of the ultrasound time on the SF response was not observed. The marinated WB meat showed similar SF values and texture profile than those from normal (N) meat, with reduction in the parameters of protein and lipid oxidation. The use of papain without ultrasound bath proved to be an efficient means for improving the tenderness of WB breasts.Practical ApplicationThis study shows the efficiency of the application of two technological procedures (enzymatic treatment and ultrasound) to improve the texture profile and technological properties of chicken breasts affected by the wooden breast myopathy. The economic loss caused by the world‐wide occurrence of wooden breast is enormous, and the application of papain has been found to counteract the impaired properties of this abnormal chicken breasts. Since papain is already widely used in the food industry to tenderize meat, its application in improving the quality of WB meat is straightforward.

An Experimental Study of Downfacing Surfaces in Selective Laser Melting

This article presents an investigative study to evaluate the effect of process parameters on surface roughness and dimensional accuracy of downfacing surfaces. The material used in the study is Corrax steel and is fabricated using selective laser melting (SLM) technology. The fabrication process of the downfacing surface is different from the fabrication of the main or core region due to the poor thermal conductivity of loose powder particles beneath each layer. The processing parameters, namely, laser scanning speed, laser power, and layer reference, are investigated using a full factorial design of experiments method to discover their influence on surface roughness and dimensional deviation. Results show that the investigated factors are significantly affecting the quality of downfacing surfaces and controlling them will greatly influence achieving required surface properties.

Influence of contact geometry over the filament bond of polylactic acid blends

Fused Filament Fabrication is one of the most common Additive Manufacturing technologies among industrial and domestic users because of the satisfying quality of parts and the great variety of thermoplastic polymers available on the market. New possibilities were provided along with the equipment with multiple extrusion systems, referring to multi-colour and multi-material components. Besides part orientation during the manufacturing process, filament bond influences the mechanical properties of parts produced through Fused Filament Fabrication technology. This paper aims to investigate if the bond performance for polylactic acid-based polymers can be enhanced by designing new contact geometries, different from the current surface-to-surface approach. To comprehensively understand the influence of the designed bonding geometries over the tensile strength, all specimens were produced according to a factorial design of experiment method and contact geometries constrained with function related to the nozzle size.

Parametric study of electric discharge machining of titanium grade 2 alloy in distilled water

The current article provides a detailed discussion on the machining of titanium grade 2 alloy in an electric discharge machine (EDM). Copper is taken as a tool electrode, and distilled water is taken as dielectric for machining purpose. Machining with hydrocarbon oil in EDM causes environmental pollution and severe threats to the operator's health. Machining is carried out in distilled water to replace the hazardous hydrocarbon oil. The full factorial experimental design method is adopted to realize the outcome of input parameters on the output parameters. The consequence of current (Ip) and pulse-on time (Ton) are analyzed on response measures viz. material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR). The cause of change in MRR, TWR, and SR trends is discussed. All the response measures show a rising trend with a rise in the value of process parameters. Analysis of Variance is implemented to notice the contribution fraction of each control variable on the response measures. Optical microscopic images are analyzed at lower and higher energy settings to observe the difference in surface morphology. MRR varies from 2.142 to 10.116 mg/min, TWR from 0.251 to 1.356 mg/min, and SR from 4.1 to 9.6 µm, respectively. Overall evaluation criteria are used to obtain input parameters to optimize the performance parameters.

Experimental study and prediction model of a liquid desiccant unit for humidification during the heating season

Liquid-desiccant-assisted air conditioning systems have attracted considerable interest owing to their potential to save energy and enhance performance through decoupled control of latent and sensible loads. In addition, several studies have suggested using the regenerator of a liquid desiccant system for humidification during the heating season; however, its performance under the winter weather condition has not yet been established. Therefore, the goal of this study is to develop the prediction models of the humidification performance of liquid desiccant systems during the heating season. Experiments were conducted to collect performance data based on the factorial experimental design method. Using the response surface method, two empirical models for the effectiveness of regeneration (R2 = 0.927) and enthalpy exchange (R2 = 0.934) were developed and experimentally validated under the actual conditions during the heating season within 10% error bounds. Significant parameters included the liquid-to-gas ratio and desiccant solution concentration and temperature. Moreover, the prediction model of the Sherwood number was developed which can be used for the numerical simulation. Additionally, the suitable operation settings of the regenerator for humidification were investigated to obtain higher energy and exergy efficiencies based on the developed prediction models. From the results, a higher liquid-to-gas ratio and lower concentration and temperature of the desiccant solution could be recommended considering both energy and energy efficiencies and the practical application of liquid desiccant systems.

EFFECTS OF AIR-COOLING-HOLE GEOMETRIES ON A LOW-PRESSURE DIE-CASTING PROCESS

A significant precondition for the production of high-quality castings is keeping an optimum temperature of the respective parts of the die cavity surface. This temperature depends on the temperature of the material, the quantity of metal, the method of cooling the casting die, the thermal conductivity of the die material, and the time during which the casting remains in the die. In addition, the cooling characteristics of alloy steel dies, used in the production of aluminum-alloy wheels with the low pressure die casting (LPDC) method, have critical effects on the mechanical and metallurgical properties of the product. Ducted air coolers are widely used for the cooling of these alloy steel dies. However, the geometrical designs of the air-cooling holes are limited. In this study, we define the effects of the geometry of the cooling holes on the cooling power of the die, the efficiency of the air consumption with the Full Factorial Experimental Design method and to determine the optimum values for LPDC. Pilot production has been carried out on an industrial scale to verify the data obtained by experimental design. The experimental and real data were compared based on the values of the yield strength and the secondary dendrite arm spacing in the microstructure.

Maximum Negative Poisson’s Ratio of Double-Core Helical Auxetic Yarns Under Uniaxial Loading: A Study on the Effect of Structural Parameters via Full Factorial Experimental Design Method

Auxetic textiles have been attracted the attention of many researchers due to their enhanced mechanical behavior during loading condition. The developed Double-core helical auxetic yarn (DC-HAY) is a structural material with negative Poisson’s ratio (NPR) behavior. It consists of two similar soft yarns with a higher diameter and a stiff yarn with a lower diameter. The stiff yarn has been twisted around the soft yarns, alternatively. In this paper, the effect of structural parameters including, the initial helical angle of wrap component with five levels, diameter ratio of components with three levels, and modulus ratio of components with two levels, on Poisson’s ratio of DC-HAY, has been investigated through the full factorial experimental design method. SPSS software has been used for analyzing the results. The results showed that the highest maximum NPR belongs to the sample with the lowest initial helical angle, highest diameter ratio of components, and highest modulus ratio of components. Also, it has been found that all the main factors have a statistically significant effect on Poisson’s ratio of DC-HAY at a 95% of confidence level.

Effect of ultrasonic-assisted turning on geometrical tolerances in Al 2024-T6

ABSTRACT In this research, the effect of ultrasonic vibrations in the turning process on geometric tolerances has been investigated. This has always been one of the most important challenges in the production of high-quality and precision parts. One of the important applications of the turning process is making parts with high dimensional accuracy. In this study, by applying ultrasonic vibrations to different machining parameters, we investigated the surface quality, runout, total runout, and straightness tolerance of a 2024-T6 aluminum workpiece. In the second stage, the effect of the presence of ultrasonic vibrations was investigated. The full factorial experiment design method was used, and 18 experiments were performed with this method. After that, the results were analyzed, and they are as follows. Compared to other machining parameters, the cutting speed has the highest effect on the runout, total runout, straightness tolerance, and surface roughness. Ultrasonic vibrations reduce all four output parameters of runout, total runout, straightness tolerance, and surface roughness. In particular, the surface roughness in ultrasonic turning decreased compared to conventional turning. Also, the formation of chips was investigated. This technique is suitable in manufacturing industries that require high dimensional accuracy.