Performance Analysis and Improvement of Flat Torque Converters Using DOE Method

Automotive torque converters have recently been designed with an increasingly narrower profile for the purpose of achieving a smaller axial size and reducing weight. Design of experiment(DOE) and computational fluid dynamics(CFD) techniques are applied to improve the performance of a flat torque converter. Four torque converters with different flatness ratios(0.204, 0.186, 0.172, and 0.158) are designed and simulated first to investigate the effects of flatness ratio on their overall performance, including efficiency, torque ratio, and impeller torque factor. The simulation results show that the overall performance tends to deteriorate as the flatness ratio decreases. Then a parametric study covering six geometric parameters, namely, inlet and outlet angles of impeller, turbine, and stator is carried out. The results demonstrate that the inlet and outlet angles play an important role in determining the performance characteristics of a torque converter. Furthermore, the relative importance of the six design parameters is investigated using DOE method for each response(stall torque ratio and peak efficiency). The turbine outlet angle is found to exert the greatest influence on both responses. After DOE analysis, an optimized design for the flat torque converter geometry is obtained. Compared to the conventional product, the width of the optimized flat torque converter torus is reduced by about 20% while the values of stall torque ratio and peak efficiency are only decreased by 0.4% and 1.7%, respectively.The proposed new optimization strategy based on DOE method together with desirability function approach can be used for performance enhancement in the design process of flat torque converters.

Optimizing Bucket Elevator Performance through a Blend of Discrete Element Method, Response Surface Methodology, and Firefly Algorithm Approaches

This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization algorithms.Specifically,the study employs the firefly algorithm(FA),a metaheuristic optimization technique,to optimize bucket elevator parameters for maximizing transport mass and mass flow rate discharge of granular materials under specified working conditions.The experimental methodology involves several key steps:screening experiments to identify significant factors affecting bucket elevator operation,central composite design(CCD)experiments to further explore these factors,and response surface methodology(RSM)to create predictive models for transport mass and mass flow rate discharge.The FA algorithm is then applied to optimize these models,and the results are validated through simulation and empirical experiments.The study validates the optimized parameters through simulation and empirical experiments,comparing results with DEM simulation.The outcomes demonstrate the effectiveness of the FA algorithm in identifying optimal bucket parameters,showcasing less than 10%and 15%deviation for transport mass and mass flow rate discharge,respectively,between predicted and actual values.Overall,this research provides insights into the critical factors influencing bucket elevator operation and offers a systematic methodology for optimizing bucket parameters,contributing to more efficient material handling in various industrial applications.

Computer modeling of high-pressure leaching process of nickel laterite by design of experiments and neural networks

Due to the complex chemical composition of nickel ores, the requests for the decrease of production costs, and the increase of nickel extraction in the existing depletion of high-grade sulfide ores around the world, computer modeling of nickel ore leaching process be- came a need and a challenge. In this paper, the design of experiments （DOE） theory was used to determine the optimal experimental design plan matrix based on the D optimality criterion. In the high-pressure sulfuric acid leaching （HPSAL） process for nickel laterite in ＂Rudjinci＂ ore in Serbia, the temperature, the sulfuric acid to ore ratio, the stirring speed, and the leaching time as the predictor variables, and the degree of nickel extraction as the response have been considered. To model the process, the multiple linear regression （MLR） and response surface method （RSM）, together with the two-level and four-factor full factorial central composite design （CCD） plan, were used. The proposed re- gression models have not been proven adequate. Therefore, the artificial neural network （ANN） approach with the same experimental plan was used in order to reduce operational costs, give a better modeling accuracy, and provide a more successful process optimization. The model is based on the multi-layer neural networks with the back-propagation （BP） learning algorithm and the bipolar sigmoid activation function.

Design of Experiment (DoE): Implementation in Determining Optimum Design Parameters of Portable Workstation

In the modern era of manufacturing, it is important to optimize every design parameter in product development stage to reduce cost, material usage and to achieve the desired efficacy level. There are various models which serve those purposes, for instance, Design of Experiment (DoE) is used to check the parameters after adopting optimization tactics which results in reduced cost or saving operating time. In this regard, this research aims to construct a DoE model on a portable workstation to optimize its design parameters. The methodology of DOE would be a 2 level 3 factors full factorial DOE which is conducted to determine the optimal value for three design parameters (factors) which are material density, the length of the table and the length of the table stand in terms of the response which is the required time of fold ability function of the portable workstation. Based upon the evaluated interactions between the parameters, the optimized parameters are chosen for responses. Here, the resultant design parameters are at their lowest level, so the goal of time efficiency in fold ability function is achieved. This similar sort of DoE can be implemented in the furniture and other manufacturing industries who wish to optimize their material usage as well as increase efficiency and reduce cycle time.

Evaluation of Full Experimental Design Method against Fractional Design Method and Taguchi Design Method in Machining Operation

DOE （design of experiments） is a systematic, rigorous approach to engineering problem-solving that applies principles and techniques at the data collection stage so as to ensure the generation of valid, defensible, and supportable engineering conclusions. This paper presents a comparison of three different experimental designs （full experimental design, fractional design and Taguchi design） aimed at studying the effects of cutting parameters variations on surface finish. The results revealed that the effects obtained by analyzing both fractional and Taguchi designs were comparable to the main effects and two-level interactions obtained by the full factorial design. Thus, we conclude that full factorial design appear to be reliable and more economical since they permit to reduce by a factor the amount of time and effort required to conduct the experimental design without losing valuable information. Thus, we conclude that full factorial design appear to be reliable and more economical and without losing valuable information.

光学玻璃磨削亚表面损伤预测模型及DOE实验设计

为了掌握光学玻璃材料杯型砂轮研磨与表面粗糙度(SR)和亚表面损伤(SSD)机理,本文建立BK7光学玻璃杯型砂轮研磨表面粗糙度的预测模型,通过改变磨削参数来研究对表面粗糙度的影响。设计DOE试验,研究影响SR与SSD的显著性特征因子,并分析了各因子的交互作用。实验结果表明预测模型的可靠性,得到表面粗糙度的预测模型数据与实验数据的平均误差为5.47%。采用角抛光法,通过电子显微镜观测表面裂纹,并测量裂纹的深度。最后,基于Li的模型,建立基于磨削工艺参数的亚表面损伤的新预测模型。实验结果表明:实验和预测模型结果具有很好的一致性,模型数据与实验数据的平均误差为6.19%,并且新预测模型结果要优于Li的模型。

Application of quality by design in the current drug development

Quality by Test was the only way to guarantee quality of drug products before FDA launched current Good Manufacturing Practice. To clearly understand the manufacture processes, FDA generalized Quality by Design(QbD) in the field of pharmacy, which is based on the thorough understanding of how materials and process parameters affect the quality profile of final products. The application of QbD in drug formulation and process design is based on a good understanding of the sources of variability and the manufacture process. In this paper,the basic knowledge of QbD, the elements of QbD, steps and tools for QbD implementation in pharmaceutics field, including risk assessment, design of experiment, and process analytical technology(PAT), are introduced briefly. Moreover, the concrete applications of QbD in various pharmaceutical related unit operations are summarized and presented.

Applications of quality by design(QbD) and its tools in drug delivery

Quality by Test (Qb T) was the only way to guarantee the quality of drug products before FDA launches current Good Manufacturing Practice (c GMP)[1], which is an approach without clear understanding of the processes. In order to solve this problem,FDA generalized Quality by Design (QbD) in the field of pharmacy (2)In pharmaceutical industry, Qb D brings cost-efficiency and simplicity of manufacturing process into reality.

Design of experiment study on hardness variations in friction stir welding of AM60 Mg alloy

Identification of process parameters,their effects and contributions to the outcomes of the system using experimental approach could be a daunting,time consuming,and costly course.Using proper statistical methods,i.e.,Taguchi method,could significantly reduce the number of required experiments and statistical significance of the parameter can be identified.Friction stir welding is one of those welding techniques with many parameters which have different effects on the quality of the welds.In friction stir welding the tool rotational speed(RPM)and transverse speed(mm/min)influence the strength(i.e.,hardness distribution)of the stirred zone.In this study,these two factors are investigated to determine the effect they will have on the hardness in the stirred zone of the friction stir welds and how the two factors are related to one another for as-cast magnesium alloy AM60 with nominal chemical composition of Mg-(5.5-6.5)Al-(0.24-0.6)Mn-0.22Zn-0.1Si.Experimental data was taken at three different tool rotational speeds and three different transverse speeds.The data obtained was then analyzed using a 32 factorial design to find the contribution of these parameters.It was determined that both tool rotational speed and transverse speed possess significant effects on the stir zone hardness.Also,the interactions between the two factors were statistically assessed.

Influence of Operating Parameters on Unbalance in Rotating Machinery Using Response Surface Method

Wide range of rotating machinery contains an inherent amount of unbalance which leads to increase in the vibration level and related faults.In this work,the effect of different operating conditions viz.the unbalanced weight,radius,speed and position of the rotor disc on the unbalance in rotating machine are studied experimentally and analyzed by using Response Surface Methodology(RSM).RSM is a technique which consists of mathematical and statistical methods to develop the relationship between the inputs and outputs of a system by distinct functions.L27 Orthogonal Array(OA)was developed by using Design of Experiments(DOE)according to which experimentation has been carried out.Three accelerometer sensors were mounted to record the vibration responses(accelerations)in radially vertical,horizontal and axial directions.The responses recorded as root mean square values are then analysed using RSM.The relationship between response and operating factors has been established by developing a second order,non-linear mathematical model.Analysis of variance(ANOVA)has been performed for verification of the developed mathematical models.Results obtained from the analysis show that the unbalance weight and speed are most significant operating conditions that contribute the most to the effect the unbalance has on the rotating spindle.

Analytical quality-by-design approach for sample treatment of BSA-containing solutions

The sample preparation of samples conlaining bovine serum albumin（BSA）,e.g..as used in transdermal Franz diffusion cell（FDC） solutions,was evaluated using an analytical qualily-by-design（QbD）approach.Traditional precipitation of BSA by adding an equal volume of organic solvent,often successfully used with conventional HPLC-PDA,was found insufficiently robust when novel fused-core HPLC and/or UPLC-MS methods were used.In this study,three factors（acetonitrile（%）.formic acid（%） and boiling time（min）） were included in the experimental design to determine an optimal and more suitable sample treatment of BSAcontaining FDC solutions.Using a QbD and Derringer desirability（D） approach,combining BSA loss,dilution factor and variability,we constructed an optimal working space with the edge of failure defined as D〈0.9.The design space is modelled and is confirmed to have an ACN range of 83 ± 3% and FA content of 1 ±0.25%.

Combined Size and Shape Optimization of Structures with DOE,RSM and GA

In this paper,size and shape optimization problem of a machine gun system is addressed with an efficient hybrid method,in which a novel and flexible mesh morphing technique is employed to achieve fast parameterization and modification of complexity structure without going back to CAD for reconstruction of geometric models or to finite element analysis（ FEA） for remodeling. Design of experiments（ DOE） and response surface method（ RSM） are applied to approximate the constitutive parameters of a machine gun system based on experimental tests. Further FEA,secondary development technique and genetic algorithm（ GA） are introduced to find all the optimal solutions in one go and the optimal design of the demonstrated machine gun system is obtained. Results of the rigid-flexible coupling dynamic analysis and exterior ballistics calculation validate the proposed methodology,which is relatively time-saving,reliable and has the potential to solve similar problems.

Process Window Determination for Biofiltration by the Taguchi Method

Raw water from the Yantian Reservoir in Southern China was used for this study. Several process parameters of biofiltration, temperature, media, empty bed contact time, ozone dosage and concentration of geosmin and MIB, were adopted in order to determine their effects. Experiments were conducted using the Taguchi method and 9 experiments were needed to obtain the best process parameter settings and parameter effects. The results of these experiments indicate the use of biological filtration as a method of geosmin and MIB removal, to be satisfactory. In addition, the results show that temperature impacts the removal rate of both geosmin and MIB. Useful insights into the effects of the filter media on such as, empty bed contact time, ozone dosage and concentration of geosmin and MIB were also obtained.

Fighting Poor Quality Medicines: Development, Transfer and Validation of Generic HPLC Methods for Analyzing Two WHO Recommended Antimalarial Tablets

As serious but neglected public health problems, poor quality medicines, i.e. for antimalarial medicines, urged to be fought. One of the approaches is to consider the analytical chemistry and separative techniques. In this study, a generic liquid chromatographic method was firstly developed for the purpose of screening 8 antimalarial active ingredients, namely amodiaquine (AQ), piperaquine (PPQ), sulfalene (SL), pyrimethamine (PM), lumefantrine (LF), artesunate (AS), artemether (AM) and dihydroartemisinine (DHA) by applying DoE/DS optimization strategy. Since the method was not totally satisfying in terms of peak separation, further experiments were undergone applying the same development strategy while splitting the 8 ingredients into five groups. Excellent prediction was observed prior to correlation between retention times of predicted and observed separation conditions. Then, a successful geometric transfer was realized to reduce the analysis time focusing on the simultaneous quantification of two WHO’s recommended ACTs in anti-malarial fixed-dose combination (AM-LF and AS-AQ) in tablets. The optimal separation was achieved using an isocratic elution of methanol-ammonium formate buffer (pH 2.8;10 mM) (82.5:17.5, v/v) at 0.6 ml/min through a C18 column (100 mm × 3.5 mm, 3.5 μm) thermostated at 25℃. After a successful validation stage based on the total error approach, the method was applied to determine the content of AM/LF or AS/AQ in seven brands of antimalarial tablets currently marketed in West, Central and East Africa. Satisfying results were obtained compared to the claimed contents.

Practical Aspects for Designing Statistically Optimal Experiments

Due to operational or physical considerations, standard factorial and response surface method （RSM） design of experiments （DOE） often prove to be unsuitable. In such cases a computer-generated statistically-optimal design fills the breech. This article explores vital mathematical properties for evaluating alternative designs with a focus on what is really important for industrial experimenters. To assess ＂goodness of design＂ such evaluations must consider the model choice, specific optimality criteria （in particular D and I）, precision of estimation based on the fraction of design space （FDS）, the number of runs to achieve required precision, lack-of-fit testing, and so forth. With a focus on RSM, all these issues are considered at a practical level, keeping engineers and scientists in mind. This brings to the forefront such considerations as subject-matter knowledge from first principles and experience, factor choice and the feasibility of the experiment design.

Optimal Designs Technique for Locating the Optimum of a Second Order Response Function

A more efficient method of locating the optimum of a second order response function was of interest in this work. In order to do this, the principles of optimal designs of experiment is invoked and used for this purpose. At the end, it was discovered that the noticeable pitfall in response surface methodology (RSM) was circumvented by this method as the step length was obtained by taking the derivative of the response function rather than doing so by intuition or trial and error as is the case in RSM. A numerical illustration shows that this method is suitable for obtaining the desired optimizer in just one move which compares favourably with other known methods such as Newton-Raphson method which requires more than one iteration to reach the optimizer.

利用DOE实验设计方法模拟聚苯硫醚热氧处理的研究

文章研究了聚苯硫醚热氧处理的模拟预测,利用MSA方法对熔体质量流动速率(MFR)的测试系统进行评估,并使用DOE实验设计方法模拟了聚苯硫醚热氧交联工艺。结果表明,对MFR不超过1000 g/10 min的样品,可以使用现有MFR测试系统得到可靠数据;根据JMP软件模拟可以得到PPS热氧交联过程的模型和交联产物MFR的计算公式。交联MFR随热空气温度升高而降低,但热空气温度接近或超过PPS树脂初熔点时,PPS树脂容易部分熔融、黏附在设备内壁或结块,影响交联反应;通过单因子验证实验,确定了模型的使用范围是热空气温度200~240℃、热处理时间大于20 h,模型偏差为-6.0%~6.2%。利用JMP软件指导PPS树脂的交联品生产,并进行DOE扩充设计,进一步建立实际生产用热氧处理模型,用于技术指导。

基于DoE实验设计的硝酸铈溶液雾化特性研究

为满足喷雾热分解法制备氧化铈颗粒需求,使用两相流空气辅助雾化喷嘴,对不同浓度的硝酸铈溶液雾化特性进行了实验研究,并使用响应曲面法对硝酸铈溶液喷雾的雾化颗粒度SMD实验数据进行了定量分析,得到了雾化颗粒度SMD与溶液物理性质及雾化环境参数之间的定量关系。本实验中溶液质量浓度为0.334~0.462、溶液体积流量为0.05 m^(3)/h和0.12 m^(3)/h、雾化空气压力为0.2~0.5 MPa。根据对获得的定量关系式分析可知,对硝酸铈溶液雾化颗粒度SMD影响最显著的因素是溶液浓度,其次是雾化空气压力,溶液体积流量对雾化颗粒度SMD的影响较小;雾化颗粒度均随雾化空气压力的升高而减小,雾化空气压力对粘性较小溶液的影响更加显著。

基于DOE和改进模拟退火算法的消声器优化设计

为提高消声器的优化效率,在考虑流速对消声器传递损失数值建模的基础上,采用试验设计(DOE)中的拉丁超立方设计对消声器参数进行分析,结合改进模拟退火算法分别建立消声器在排气噪声峰值频率处传递损失的单目标和多目标优化模型,开展消声器的优化设计研究。研究结果表明:DOE方法能有效辨识出各参数对消声器传递损失贡献度的大小,简化了消声器的优化模型。消声器内气体的平均流速对消声器的优化结果影响较大。单目标优化可使相应峰值频率处的传递损失达到最大值,多目标优化能使全频段整体优化效果较好,优化设计后排气噪声最大降低31.73d B,优于单目标优化结果。研究结果为消声器的优化设计提供了新思路。

基于DOE及RSM的液力变矩器叶片数对性能的影响及优化

为解决一维束流理论难以有效地对液力变矩器叶片数进行优化的问题,建立液力变矩器三维流动设计分析平台,利用实验设计方法,研究了各叶片数对液力变矩器性能的影响,并在响应曲面基础上对叶片数进行了优化.结果表明,泵轮、涡轮叶片数对最高效率和起动转矩比有较大影响,泵轮、导轮叶片数对泵轮扭矩系数有较大影响.优化后,液力变矩器各性能指标均有提高.