Statistical Experimental Design Techniques Research Articles

Optimization of welding parameters of hot plate welded PC/ABS blends by using the Taguchi experimental design method

This study aims to investigate the influence of welding parameters in hot plate welding (HPW) process of polycarbonate (PC)/acrylonitrile-butadiene-styrene (ABS) blends using Taguchi method. Three welding parameters, namely the plate temperature, heating time, and welding displacement, were optimized in terms of joint strength using the results of tensile tests. Taguchi experimental design method is implemented as a statistical design of experiment technique so as to set the optimum welding parameters and determine the optimal levels. For HPW of the specimens, the combination of process parameters based on three levels of L9 orthogonal array was utilized. The signal to noise ratio and the analysis of variance were employed to find the optimum levels and to indicate the impact of the welding parameters on joint strength after tensile tests of the welded joints were carried out. It was shown that it might achieve the improved joint strength using 290 °C of plate temperature, 1.25 mm of welding displacement,...

Statistical investigation of the full concentration range of fasted and fed simulated intestinal fluid on the equilibrium solubility of oral drugs

Upon oral administration the solubility of a drug in intestinal fluid is a key property influencing bioavailability. It is also recognised that simple aqueous solubility does not reflect intestinal solubility and to optimise in vitro investigations simulated intestinal media systems have been developed. Simulated intestinal media which can mimic either the fasted or fed state consists of multiple components each of which either singly or in combination may influence drug solubility, a property that can be investigated by a statistical design of experiment technique. In this study a design of experiment covering the full range from the lower limit of fasted to the upper limit of fed parameters and using a small number of experiments has been performed. The measured equilibrium solubility values are comparable with literature values for simulated fasted and fed intestinal fluids as well as human fasted and fed intestinal fluids. The equilibrium solubility data range is statistically equivalent to a combination of published fasted and fed design of experiment data in six (indomethacin, phenytoin, zafirlukast, carvedilol, fenofibrate and probucol) drugs with three (aprepitant, tadalafil and felodipine) drugs not equivalent. In addition the measured equilibrium solubility data sets were not normally distributed. Further studies will be required to determine the reasons for these results however it implies that a single solubility measurement without knowledge of the solubility distribution will be of limited value. The statistically significant media factors which promote equilibrium solubility (pH, sodium oleate and bile salt) were in agreement with published results but the number of determined significant factors and factor interactions was fewer in this study, lecithin for example did not influence solubility. This may be due to the reduction in statistical sensitivity from the lower number of experimental data points or the fact that using the full range will examine media parameters ratios that are not biorelevant. Overall the approach will provide an estimate of the solubility range and the most important media factors but will not be equivalent to larger scale focussed studies. Further investigations will be required to determine why some drugs do not produce equivalent DoE solubility distributions, for example combined fasted and fed DoE, but this simply may be due to the complexity and individuality of the interactions between a drug and the media components.

Designing Solutions by a Student Centred Approach: Integration of Chemical Process Simulation with Statistical Tools to Improve Distillation Systems

Projects thematically focused on simulation and statistical techniques for designing and optimizing chemical processes can be helpful in chemical engineering education in order to meet the needs of engineers. We argue for the relevance of the projects to improve a student centred approach and boost higher order thinking skills. This paper addresses the use of Aspen HYSYS by Portuguese chemical engineering master students to model distillation systems together with statistical experimental design techniques in order to optimize the systems highlighting the value of applying problem specific knowledge, simulation tools and sound statistical techniques. The paper summarizes the work developed by the students in order to model steady-state processes, dynamic processes and optimize the distillation systems emphasizing the benefits of the simulation tools and statistical techniques in helping the students learn how to learn. Students strengthened their domain specific knowledge and became motivated to rethink and improve chemical processes in their future chemical engineering profession. We discuss the main advantages of the methodology from the students’ and teachers perspective

Optimization of selective laser sintering process parameters to achieve the maximum density and hardness in polyamide parts

Density and hardness of selective laser-sintered parts are influenced by the different sintering parameters. The selection of sintering parameters plays a vital role to achieve the high precision of end use functional parts. These parts are widely used in the industries such as automobile, aerospace, and for medical applications [Sustarsic et al. (Mater Manuf Process 24:837–841, 2009), Shah et al. (Mater Manuf Process 25:1372–1380, 2010)]. In this study, laser power, scan spacing, bed temperature, hatch length, and scan count were the parameters taken into account for experimentation. Face-centered central composite design was used as a statistical design of experiment technique to set the optimal laser sintering parameters. A relationship between these parameters had also been developed with the generation of different mathematical models. The adequacies of these models were confirmed using analysis of variance. The study concluded that laser power, scan spacing, bed temperature, and hatch length have higher influence on density and hardness of polyamide laser-sintered parts. Among these parameters, scan spacing is the most significant parameter for both density and hardness measures. Laser power—24.05 mm, scan spacing—0.1 mm, bed temperature—173.65 °C, hatch length—114.64 mm, and scan count—2 are the optimum levels to maximize the density and hardness.

Abstract A30: Characterizing the non-linear dependency of the CDK5-Rb axis in non-small cell lung cancer

Abstract In spite of recent therapeutics advances and early detection, lung cancer is still the leading cause of cancer-associated deaths worldwide. The five-year survival rates for its two major subtypes, small-cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) are estimated to be 6% and 18%, respectively. This high mortality is due to its aggressive nature even when detected at an early stage. Besides its aggressive nature and tendency for early metastasis, another feature of lung cancer is the inactivation of the retinoblastoma protein (Rb) that is observed in both lung cancer subtypes. NSCLC exhibits Rb inactivation by hyper-phosphorylation. Rb is phosphorylated by cyclin dependent kinases (CDKs) and their cyclin regulatory partners. CDK5 is a unique CDK because its regulatory partners, p35 and p39, are not cyclins, hence its function is not cell cycle related. This work aims to employ empirical modeling and statistical experimental design techniques to gain a comprehensive mechanistic understanding of metastasis. Previous mass spectroscopy experiments performed in our laboratory on a panel of NSCLC cell lines identified five-residues (S249, S612, S807, S811, and T821) whose phosphorylation is associated with lack of E-cadherin expression, and therefore may be associated with metastasis. Our hypothesis is that Rb inactivation via phosphorylation due to CDK5 leads to the acquisition of the epithelial-to-mesenchymal transition (EMT) phenotype and the disruption of cell-cell adhesion that characterizes metastatic cells. As a first step to establish a mathematical model the dependency of the controllable variables, Rb residues and CDK5 expression was assessed. To this end, we used siRNA to knockdown CDK5 expression, which caused a decrease in phosphorylation of Rb in the five residues mentioned above and a subsequent decrease in E-cadherin expression. These data suggest that Rb phosphorylation in the five residues is dependent on CDK5 expression. This dependency in our controllable variables points to a nested experimental design. Our next step is to perform invasion assays and lung acini formation to quantify the invasion capacity and the malignant transformation. In the long term, at a clinical setting, a lung cancer tumor may be extracted from a biopsy and immunohistochemistry staining will be performed with antibodies of interest such as Rb phosphorylation residues, E-cadherin, and CDK5/p35 or CDK5/p39. This mathematical model would help provide a prognosis about the invasion capacity and a malignancy prediction of the lung tumor. Citation Format: Jaileene Perez-Morales, Mauricio Cabrera-Rios, Jonathan Gonzalez-Flores, Pedro Santiago-Cardona. Characterizing the non-linear dependency of the CDK5-Rb axis in non-small cell lung cancer. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A30.

Statistical experimental design techniques to investigate the strength of adhesively bonded T-joints

Statistical experimental design techniques were used to study the strength of ‘T’-Joints representative of various connections used to fabricate marine composite structures via a large test program. The effects of different surface preparations and cleaning methods, and adhesives were investigated. An analysis of variance was conducted, giving an extremely good fit to the experimental data. Importantly, the statistical methods identified significant interaction effects; the effect of each parameter varied considerably between the different levels of the other parameters. Interaction plots were found to be indispensable both in clearly presenting and understanding the complex relationships seen in the data, and in interpreting the results in terms of a number of practical engineering conclusions.

First and second order simplified models for the performance evaluation of low temperature activated desiccant wheels

Hybrid systems with a desiccant wheel, DW, are an alternative to heating, ventilation and air conditioning, HVAC, commonly used systems for dehumidification and humidity control in rooms with high latent loads.Currently, the experimental methodology used to study the behaviour of a DW requires a high number of tests. The aim of this study is to obtain a DW empirical model which accurately represents the behaviour of a DW activated at low temperature, values below 60°C, by conducting a reduced number of experimental tests. For this study, the statistical Design of Experiments technique, DOE, is used.The proposed models can be used to predict the influence of the inlet process air and inlet regeneration air, on the air process outlet temperature and humidity ratio. The accuracy obtained of the experimental models is more than acceptable, with R2 values greater than 97.4% for outlet temperature and 95.1% for outlet humidity ratio. The first order model was considered to be a good option due to the balance between accuracy and the low number of experimental tests required. However, the second order model allowed a deeper understanding of the behaviour of the air outlet conditions in the DW.

The Statistical Experimental Design for Chemical Reactors Modeling

The Statistical Experimental Design techniques are the most powerful tools for the chemical reactors experimental modeling. Empirical models can be formulated for representing the chemical behavior of reactors with the minimal effort in the necessary number of experimental runs, hence, minimizing the consumption of chemicals and the consumption of time due to the reduction in the number of experimental runs and increasing the certainty of the results. Four types of nonthermal plasma reactors were assayed seeking for the highest efficiency in obtaining hydrogen and ethylene. Three different geometries for AC high voltage driven reactors, and only a single geometry for a DC high voltage pulse driven reactor were studied. According to the fundamental principles of chemical kinetics and considering an analogy among the reaction rate and the applied power to the plasma reactor, the four reactors are modeled following the classical chemical reactors design to understand if the behavior of the nonthermal plasma reactors can be regarded as the chemical reactors following the flow patterns of PFR (Plug Flow Reactor) or CSTR (Continuous Stirred Tank Reactor). Dehydrogenation is a common elimination reaction that takes place in nonthermal plasmas. Owing to this characteristic, a paraffinic heavy oil with an average molecular weight corresponding to C15 was used to study the production of light olefins and hydrogen.

Taguchi Optimization of Process Parameters in Friction Stir Spot Welding of AA5754 and AA2024 Alloys

The feasibility of friction stir spot welding was studied on AA5754-H22 and AA2024-T3 aluminum alloys which have widespread applications in aircraft and automotive industries. The quality of the joint was evaluated by examining the characteristics of the joint as a result of lap-shear fracture load. Taguchi approach of the parameter design was used as a statistical design of experiment technique to set the optimal welding parameters. The experiments were arranged by using Taguchi’s L9 orthogonal array. The signal-to-noise ratio and the analysis of variance were utilized to obtain the influence of the friction stir spot welding parameters on the lap-shear fracture load. Finally, the results were confirmed by further experiments.

Modification of coconut fibers with polyaniline for manufacture of pressure‐sensitive devices

This article studies the modification of coconut fibers with polyaniline (PAni) with help of statistical experimental design techniques. The main factors studied here were the techniques used for particle dispersion (sonication vs. magnetic stirring) and the type of initiator (ammonium persulfate, APS, vs. ammonium cerium sulfate dihydrate, Ce(IV)). The obtained materials were characterized through low field nuclear magnetic resonance, small‐and wide‐angle X‐ray scattering, scanning electron microscopy, fourier transform infrared spectroscopy, and ultraviolet–visible spectroscopy. Additionally, the electrical resistivities and respective sensitivities to variations of the applied pressure were evaluated for all obtained samples, with help of standard volume resistivity measurements and electro‐mechanical tests. The materials prepared through magnetic stirring with APS presented the best electrical and electromechanical properties, although materials prepared through sonication with Ce(IV) also presented good electrical and electromechanical properties and could be prepared much faster. As a consequence, modification of coconut fibers with PAni, using sonication as the particle dispersion technique and Ce(IV) as initiator, constitutes a very promising procedure for manufacture of pressure‐sensitive devices. POLYM. ENG. SCI., 54:2887–2895, 2014. © 2014 Society of Plastics Engineers

Experimental investigation on flexural behavior of friction stir welded high density polyethylene sheets

Flexural strength is one of the main criteria in evaluation of the mechanical properties of polymeric joints. The flexural strength of thermoplastics, such as high density polyethylene (HDPE) sheets, is influenced by friction stir welding parameters. The determination of the welding parameters plays an important role in the weld strength. In the present study, the response surface method (RSM) was used as a statistical design of experiment technique to set the optimal welding parameters. The designed tool was consisted of a rotating pin, a stationary shoulder (shoe) and a heating system inside shoe. Rotational speed of the pin, tool traverse speed and shoe temperature were considered as varying parameters. Obtained results show a significant relationship between considered properties and processing parameters through an analysis of variance (ANOVA) study and the response surface method. It was found that welding at a high level of rotational speed and a lower level of tool travel speed increases weld flexural strength by reducing size of defects.

Modeling and multi-constrained optimization in drilling process of carbon fiber reinforced epoxy composite

The goal of this study is to present a methodology for the determination of the optimal cutting parameters (spindle speed, feed rate and tool point angle) during the drilling process of carbon fiber reinforced polymer composites (CFRP) to maximize the material removal rate by considering surface roughness, delamination and thrust force as the constraints through coupling Response Surface Method (RSM) and Genetic Algorithm (GA). In this regard, the advantages of statistical experimental design technique, experimental measurements, Response Surface Method (RSM) and the genetic optimization method are exploited in an integrated manner. To this end, the experiments on CFRP were conducted to obtain surface roughness, delamination factor and thrust force values based on the full factorial design of experiments, and then analysis of variance (ANOVA) is performed. The predictive models for outputs were created using Response Surface Method (RSM) taking advantage of the experimental data. Material removal rate constituted the main function for the genetic algorithm, and thrust force, delamination, and surface roughness were applied as the constraints of the GA function. The function was optimized by the GA code, and finally, the optimum variables were obtained, and the results of the GA were tested experimentally. It can be clearly observed that good agreement exists between the predicted values and the experimental measurements.

Process Parameter Optimization of AISI 316L(N) Weld Joints Produced using Flux-Cored Arc Welding Process

Bead on plate welds were carried out on AISI 316L(N) austenitic stainless steel using flux cored arc welding process. The bead on plates weld was conducted as per L25 orthogonal array with statistical design of experiment technique. In this paper, the welding parameters will be optimized based on the weld bead geometry such as depth of penetration, bead width and weld reinforcement. Grey relational analysis and desirability approach are used to optimize the input parameters like wire feed rate, voltage, travel speed and torch angle while considering the multiple output variables simultaneously. Confirmation experiment has also been conducted to validate the optimized parameters.

Optimization of Nd:YAG Laser Parameters for Microdrilling of Alumina with Multiquality Characteristics via Grey–Taguchi Method

In laser microdrilling, the formation of taper and the dimension of the heat-affected zone (HAZ) are important attributes that greatly influence the quality of a drilled hole. In this article, an experimental investigation into Nd:YAG laser microdrilling of alumina is carried out to produce desired high-quality microdrill. Four independently controllable process variables viz. lamp current, pulse frequency, air pressure, and pulse width are considered as input parameters, while hole taper and HAZ width are considered the output parameters. The Taguchi method combined with the grey relational analysis is used as a statistical design of experiment technique to set the optimal process parameters. The objective is set to minimize both quality characteristics, simultaneously. Grey relational analysis is applied to convert the multiple quality characteristics to a single performance characteristic, called grey relational grade. Optimal process parameters are then determined by the Taguchi method using grey relational grade as the quality index. Both of the quality characteristics of drilled holes are improved markedly at the optimal process condition, as verified by an additional confirmation test. This indicates the application feasibility of the grey-based Taguchi technique for continuous improvement of laser microdrilling quality in the manufacturing industry.

Artificial Intelligence Model of Surface Roughness for End Milling Operation of Steel and its Verification by Genetic Algorithm

Surface roughness is important for evaluating the machined surface quality. In this work, an Artificial Neural Network (ANN) surface roughness prediction model was developed by coupling it with Response Surface Methodology (RSM). For this interpretation, advantages of statistical experimental design techniques, experimental measurements, and artificial neural network were exploited in an integrated manner. Cutting experiments were designed based on small centre composite design technique to develop a RSM model. The input cutting parameters were: cutting speed, feed, and axial depth of cut, and the output parameter was surface roughness. The predictive model was created using a feed-forward back-propagation neural network exploiting the experimental data. The network was trained with pairs of inputs/outputs datasets generated by end milling medium carbon steel with TiN coated carbide inserts. The model can be used for the analysis and prediction of the complex relationships between cutting conditions and surface roughness, in metal-cutting operations, with the ultimate goal of efficient production. The ANN model was verified with the optimized parameters predicted by a coupled genetic algorithm (GA) and RSM technique also developed by the authors.

The optimization of friction stir welding process parameters to achieve maximum tensile strength in polyethylene sheets

The weld strength of thermoplastics, such as high density polyethylene and polyprophylene sheets are influenced by friction stir welding parameters. The determination of the welding parameters plays an important role for the weld strength. For the influential use of the thermoplastics joints, the weld should have adequate strength. The quality of the joint was evaluated by examining the characteristics of the joint efficiency as a result of ultimate tensile strength. In this study, the Taguchi approach of parameter design was used as a statistical design of experiment technique to set the optimal welding parameters. The experiments were arranged by using Taguchi’s L9 orthogonal array. The signal-to-noise ratio and the analysis of variance were utilized to obtain the influence of the friction stir welding parameters on the weld strength. Finally, the results were confirmed by further experiments.

Application of Taguchi approach to optimize friction stir spot welding parameters of polypropylene

This paper shows experimental and numerical results of friction stir spot welding of high density polypropylene. The determination of the welding parameters plays an important role for the weld strength. The experimental tests, conducted according to combinations of process factors such as tool rotation speed, plunge depth and dwell time at beginning welding, were carried out according the Taguchi orthogonal table L9 in randomized way. The Taguchi approach was used as a statistical design of experiment technique to set the optimal welding parameters. The results show coherence between the numerical predictions and experimental observations in different cases of weld strength. The signal-to-noise ratio and the analysis of variance were utilized to obtain the influence of the friction stir spot welding parameters on the weld strength. Finally, the improvement in the weld strength from the initial welding parameters to the optimal welding parameters was about 47.7%.

Evaluation of Machining Parameters of Hot Turning of Stainless Steel (Type 316) by Applying ANN and RSM

Stainless steel (Type 316) workpiece was heated by the mixture of Liquid Petroleum Gas (LPG) and oxygen gas, and it was machined in a lathe under different cutting conditions to study the hot machining characteristics. The orthogonal turning operations were carried out on stainless steel (Type 316) using tungsten carbide (WC) cutting tool insert. During machining the cutting speed (Vc), feed rate (fs), depth of cut (a p ), and temperature of the workpiece were varied in the range of 200°C, 400°C, and 600°C. Turning experiments were designed based on the statistical three-level full factorial experimental design techniques. An artificial neural network (ANN) and response surface model (RSM) have been developed, which can predict the surface roughness of the machined workpiece. The experimental results concur well with the results obtained from the predictive models.

Recent advances in optimized geophysical survey design

Survey design ultimately dictates the quality of subsurface information provided by practical implementations of geophysical methods. It is therefore critical to design experimental procedures that cost effectively produce those data that maximize the desired information. This review cites recent advances in statistical experimental design techniques applied in the earth sciences. Examples from geoelectrical, crosswell and surface seismic, and microseismic monitoring methods are included. Using overdetermined 1D and 2D geoelectrical examples, a minor subset of judiciously chosen measurements provides a large percentage of the information content theoretically offered by the geoelectrical method. In contrast, an underdetermined 2D seismic traveltime tomography design study indicates that the information content increases almost linearly with the amount of traveltime data (source-receiver pairs) considered until the underdeterminancy is reduced substantially. An experimental design study of frequency-domain seismic-waveform inversion experiments reveals that a few optimally chosen frequencies offer as much subsurface information as the full bandwidth. A nonlinear experimental design for a seismic amplitude-versus-angle survey identifies those incidence angles most important for characterizing a reservoir. A nonlinear design example shows that designing microseismic monitoring surveys based on array aperture is a poor strategy that almost certainly leads to suboptimal designs.

Iron and chromium sulfates from ferrochromium alloy for tanning

In this study we investigated the production of soluble iron and chromium sulfate complexes from high carbon ferrochromium alloy (Fe–Cr–HC) for utilization as a tanning agent. The temperature, sulfuric acid concentration, and the reaction time between Fe–Cr–HC and sulfuric acid were selected as independent variables for iron and chromium conversion. A quadratic response surface model was adjusted using the Box–Behnken statistical experimental design technique. The results obtained by solving multi-objective optimization problem have shown about 98.6–100% Cr and 86.9–89.1% Fe conversions. Perchloric acid and ammonium sulfate additions were investigated in order to determine the system limitations. The results have showed that an increase of perchloric acid concentration decreased the quantity of soluble chromium and iron compounds, while an ammonium sulfate addition improved the conversion of chromium up to 100%.