An Energy-Enhanced Design of Experiments Method

With the rapid development of IC technologies, topics of 3D stacked IC packages are now being studied vastly around the world. In 3D stacked IC technologies, many electrical characteristics have been proved to have great improvements, but their corresponding thermo-mechanical problems are raising as well. Due to the reason of ICs stacking, thermo-mechanical problems are becoming more serious than those in traditional single IC package. These problems include the heat dissipation, die breaking, interfacial delamination, via cracking and so on. These corresponding problems not only cause failures in 3D stacked IC packages but also have significant influences on reliability. For the sake of realizing critical stress distributions in 3D stacked IC packages, the three dimensional finite element analysis (FEA) modeling has been employed in this paper. The 3D-WLP (wafer-level-package) with ten layer chips stacking is selected as our test vehicle. By using three dimensional FEA modeling, thermal induced stress distributions in 3D-WLP when subjected to a uniform temperature change can be illustrated. Further, the design of experiments (DOE) analysis for design optimization has also been used to obtain the sensitivities of geometry and material properties of 3D-WLP. Several geometric dimensions and material properties are selected as main design factors and the average value of maximum von Mises stress in copper vias and chips is chosen as the response to be optimized. Through the DOE analysis, the optimum geometry and material properties of 3D-WLP and this result in smaller von Mises stresses in copper via and chip configurations can be obtained. These results can be most effectively used as design guidelines to engineers when optimum stress solutions in 3D-WLP are required.

<div class="htmlview paragraph">A DoE analysis was carried out to investigate the effects of the compression ratio, injection timing, injector nozzle hole size and number on performance and emissions in a diesel marine engine, aiming to find out the optimal combination between all the abovementioned parameters.</div> <div class="htmlview paragraph">The study was performed on a six cylinder in line, 100 liter total displacement, diesel marine engine, by means of a 1-D engine simulation fluid-dynamic code, coupled with a multi-zone combustion model for oxide of nitrogen (NOx) and particulate (PM) prediction.</div> <div class="htmlview paragraph">A preliminary detailed validation process, based on an extensive experimental data set, was carried out on the engine model concerning, in particular, the predicted heat release rate, the in-cylinder pressure trace and NOx emissions for several operating points of a propeller load curve.</div> <div class="htmlview paragraph">Afterward a full factorial Design of Experiments (DoE) analysis was carried out in order to find out the optimal combination between compression ratio, injection timing, injector nozzle hole size and number aiming to reach the lowest brake specific fuel consumption value while complying with NOx emissions and peak firing pressures constraints.</div>

The purpose of this study was to investigate the effect of globe and optic nerve (ON) morphologies and tissue stiffnesses on gaze-induced optic nerve head deformations using parametric finite element modeling and a design of experiment (DOE) approach. A custom software was developed to generate finite element models of the eye using 10 morphological parameters: dural radius, scleral, choroidal, retinal, pial and peripapillary border tissue thicknesses, prelaminar tissue depth, lamina cribrosa (LC) depth, ON radius, and ON tortuosity. A central composite face-centered design (1045 models) was used to predict the effects of each morphological factor and their interactions on LC strains induced by 13 degrees of adduction. Subsequently, a further DOE analysis (1045 models) was conducted to study the effects and potential interactions between the top five morphological parameters identified from the initial DOE study and five critical tissue stiffnesses. In the DOE analysis of 10 morphological parameters, the 5 most significant factors were ON tortuosity, dural radius, ON radius, scleral thickness, and LC depth. Further DOE analysis incorporating biomechanical parameters highlighted the importance of dural and LC stiffness. A larger dural radius and stiffer dura increased LC strains but the other main factors had the opposite effects. Notably, the significant interactions were found between dural radius with dural stiffness, ON radius, and ON tortuosity. This study highlights the significant impact of morphological factors on LC deformations during eye movements, with key morphological effects being more pronounced than tissue stiffnesses.

A design of experiment (DOE) is used in many industrial sectors in the development and optimization of manufacturing processes. DOE is a more effective way to determine the impact of two or more factors on a response. In this paper, a Two-Level Fractional Factorial design was employed to develop the important factors that significantly affect new promising OT Rubber recycling machine using a DOEs analysis. Central composite design (CCD) and response surface methodology (RSM) were used to optimize the isolating screen size. The CCD considered five factors with two-level full factorial design. CCD experiments using RSM was proved to be an optimal tool for optimization.

The concept of quality by design (QbD) was introduced to the pharmaceutical industry about a decade ago. Design of experiments (DoE) is an excellent and important tool for a QbD approach. This project’s aim is to obtain an overview of how DoE is being applied to assist pharmaceutical development in New Drug Application (NDA) and Abbreviated New Drug Application (ANDA) submissions for oral solid dosage forms including immediate release (IR) tablet, extended release (ER) tablet, IR capsule, and ER capsule. A total of 131 NDA submissions and 606 randomly selected ANDA submissions with submission dates between 2012 and 2016 were chosen based on the Biopharmaceutics Classification System (BCS) of drug substances. The ratios of applying DoE studies in NDA and ANDA submissions were calculated and compared based on the BCS classes of the active pharmaceutical ingredients (APIs). For the Reference Listed Drug (RLD)-based cluster ANDA submissions, the percentage of applying DoE studies in BCS II ANDA submissions is statistically higher than those of the ANDA submissions in the other three BCS classes. Some common issues of the DoE studies were found in the selected submissions. DoE has been used as an important tool for QbD approach in NDA submissions but has not yet become a routine common practice to assist the implementation of QbD approach during the pharmaceutical development for NDA and ANDA submissions for oral solid dosage forms. By conducting DoE studies, researchers can gather critical information (i.e., CMAs, CQAs, CPPs, potential interactions) during the pharmaceutical development which can help to improve the quality of applications.

The impact of enzymatic hydrolysis at 8ᵒC of liquid whey protein concentrate (WPC35) derived from acid casein manufacture using Prolyve 1000®, a microbial protease preparation, under free-fall pH conditions on the physicochemical and the thermal stability properties of the resultant hydrolysates was investigated. The hydrolysis process was optimised using a design of experiments (DOE) approach. Eleven hydrolysates (H1–H11) were generated using 3 factors x 2 levels, i.e., enzyme:substrate (E:S) 0.25–1.00% (v/w), starting pH 7.5–9.0 and incubation time 10–96 h. Hydrolysate degree of hydrolysis (DH) values ranged from 0.75 (H10) to 4.74% (H6) which increased to 1.91 (H10) and 7.24% (H6) following subsequent thermal processing (mimicking the evaporation process) at 54ᵒC x 15 min and 64ᵒC x 10 min. The apparent viscosity (ηapp) of all hydrolysates was measured to assess their heat stability during heating at 85ᵒC for up to 20 min, this was shown to be E:S and pH-dependent. While the unhydrolysed samples formed a gel on heating at ∼74-80ᵒC. Following DOE analysis, it was found that E:S had a significant impact on the DH, the extent of intact protein degradation (%Deg) and the thermal stability. The %Deg following processing at 64ᵒC showed a strong correlation (R2 = 0.924; p < 0.001) with ηapp, and thus this parameter may be used to predict the thermal stability of the hydrolysate samples. The optimised hydrolysis conditions for the generation of heat stable WPC35 hydrolysates during 8°C incubation were achieved using an E:S = 0.625% at a starting pH = 8.65. Performance of protein hydrolysis reactions at low temperature has potential to enhance process sustainability.

A thin, chloride-containing electrolyte film can be established on surfaces in many marine environments, due to splash/spray, rain, or salt-enabled deliquescence [1]. Defects in the corrosion protection system are common and inevitable due to the intense operating/maintenance conditions of ships and aircraft. Such defects are likely intensified at complex component joining/fastener locations. Furthermore, the geometry of faying surfaces and fastener holes inherently aid in the trapping/wicking of the electrolyte into tight crevices typical of these component joining locations. This geometry leads to a severe localized corrosion environment where a galvanic cell can be established, for example, between aluminum alloy components and stainless steel fasteners.The overall goals of this work are to develop a quantitative scientific understanding of the effects of important external variables on the electrochemical potential and current distributions that develop in fastener hole configuration involving a realistic thin film/galvanic couple configuration between a 7050- T7451 component and a CRES 316 fastener. The earlier modeling of atmospheric localized corrosion [2-4] will serve as a framework, but needs to be extended to more complicated geometries.A combination of experimental and modeling approaches are being used to characterize key processes and important external factors in atmospheric localized corrosion. Regarding the modeling framework, two aspects require definition: the geometry to be studied, and the differential equation to be solved. The generic thin film/galvanic couple configuration of interest is shown in Figure 1. There are a substantial number of external variables describing the geometry. Determination of the significance of each of these geometric variables has been accomplished using a Design of Experiment (DOE) method. From DOE analysis, geometric parameters W1, G1, W2, L1 and L4 are confirmed to be the most important. The Laplace's Equation is used to model steady-state current and potential distributions under thin-electrolyte conditions, ignoring ion species diffusion and changes in solution chemistry. The use of the Laplace's Equation relies on a knowledge or estimation of the electrolyte characteristics (primary conductivity) and its dependence on position and other experimental variables. FEM modeling was applied to numerically determine the potential and current distributions in the thin film at steady state for the range of geometries and environments. To accomplish this objective, the appropriate electrochemical kinetics for the CRES 316 and 7050-T7451 alloys will be determined experimentally. The electrochemical kinetics so determined will serve as the boundary conditions for solving the Laplace's Equation. In the current work, electrochemical kinetics from a related study [4] were used for the boundary conditions. The results of the DOE matrix and its implications for localized corrosion and the mitigation of such attack will be discussed. Acknowledgement This work has been supported by the Office of Naval Research (ONR) Grant N00014-14-1-0012. Mr. William Nickerson, Technical Officer at Office of Naval Research is gratefully acknowledged.

Application of statistical design of experiments to assess pre-treatment parameters in forensic hair analysis for amphetamine

Effect of disintegrants on the properties of multiparticulate tablets comprising starch pellets and excipient granules

This laboratory exercise teaches students the application of design of experiments (DOE) for optimizing a trypsin activity assay using the artificial substrate Nα-benzoyl-l-arginine-p-nitroanilide (BAPNA). The response surface modeling (RSM) approach is exploited to design and evaluate the combined effects of relevant factors on the inhibition of trypsin by the competitive inhibitor benzamidine. RSM matrices and statistics are generated using commercial software. Experimental data are compared with Michaelis–Menten theory. The predicted values are in good agreement with the experimental data. The comprehensive analysis of data provides deep insight into the relationship between substrate, inhibitor concentration, and assay sensitivity in the context of high-throughput drug screening. Data analysis reveals also unexpected but explainable interactions between the substrate and the pH value in the applied enzyme activity assay. The combined design, performance, and analysis of practical experiments demonstrates that DOE is an excellent tool to explore the relationship between several parameters affecting the enzyme activity and to optimize functional enzyme activity assays in a variety of applications.

Simulation and experimental study in determining injection molding process parameters for thin-shell plastic parts via design of experiments analysis

Investigating the interactions of amino acid components on a mannitol-based spray-dried powder formulation for pulmonary delivery: A design of experiment approach

Anhydride-containing oligomer-crosslinked gelatin microparticles: crosslinking process understanding using design of experiments

The paper presents modeling and Design of Experiments (DOE) analysis for a simple recuperated s-CO2 closed loop Brayton cycle operating at a maximum temperature of 600°C and a compressor inlet temperature of 45°C. The analysis highlights the impact of isentropic efficiencies of the turbine and compressor, decoupled in this case, on other equipment such as recuperator, gas cooler and heater, all of which have a bearing on the overall performance of the s-CO2 Brayton cycle. A MATLAB program coupled with REFPROP is used to perform the thermodynamic analysis of the cycle. A design space exploration with a Design of Experiments (DOE) study is undertaken using I-sight™ (multi-objective optimization software), which is coupled with the MATLAB code. The outcome of the DOE study provides the optimal pressure ratios and high side pressures for maximum cycle efficiency in the design space. By varying pressure ratios along with a floating high side pressure, the analysis reveals that the cycle performance exhibits a peak around a pressure ratio of 2.5, with cycle efficiency being the objective function. A further interesting outcome of the DOE study reveals that the isentropic efficiencies of the compressor and turbine have a strong influence not only on the overall cycle efficiency, but also the optimum pressure ratio as well as the threshold pressures (low as well as high side pressure). An important outcome of this exercise shows that the isentropic efficiency of the turbine has a much greater impact on the overall cycle performance as compared to that of the compressor.

To stay ahead of the competition companies often look at the product category for optimization. A consumer design of experiments study was conducted with various analyses to understand the best product feature combinations for maximizing consumer acceptance and purchase intent (PI) for makeup remover wipes. A blind, sequential monadic, 6‐weeks home use test with a balanced incomplete block design was conducted with 963 consumers in the United States and United Kingdom. Eighteen prototypes were selected with different combinations of four factors (formula, thickness, weight, and lotion add‐on). Each participant evaluated six of the 18 prototypes. Weekly online questionnaires were used to capture questions covering overall liking (OL), PI, skin feel, texture of the fabric, and so on. A simulation model was generated to identify the best factor combination with highest PI and OL for product optimization. Driver's analysis; sensitivity analysis, a new method not often used in the sensory and consumer research; and penalty analysis provided more in‐depth understanding of product performance. The learning from this study guided the product development team to determine the factor combination for the product optimization and provide direction on future planning for the category.Practical applicationsThe use of multiple analyses with studies such as a design of experiment or other category appraisal type studies can provide additional information to researchers and help to identify both those aspects that drive acceptance or purchase intent as well as those factors that could reduce consumer interest. Although the information sometimes may appear “at odds with each other,” careful study often provides insights that may have been lost without the additional analyses.