MR阻尼器设计关键技术研究

对MR阻尼器的基本工作模式和原理进行了分析，总结了MR阻尼器对磁流变液性能的基本要求，从阻尼间隙宽度、活塞有效长度、活塞及活塞杆直径等方面分析了MR阻尼器结构参数的设计原则，探讨了MR阻尼器的线圈缠绕方式确定、磁芯材料选择和磁路计算方法，概括了MR阻尼器设计中应注意的关键性技术问题，可为磁流变器件的设计提供技术参考和经验借鉴。     

Removal of boron from aqueous solutions by batch adsorption on calcined alunite using experimental design

In the present paper, boron removal from aqueous solutions by batch adsorption was investigated and 2(3) full factorial design was applied. Calcined alunite was used as adsorbent. In the study, three parameters affected the performance and two levels of these parameters were investigated. The chosen parameters were temperature (25 and 45 degrees C, respectively), pH (3 and 10) and mass of adsorbent (0.5 g adsorbent per 25 mL solution and 1g adsorbent per 25 mL solution). The significance of the effects was checked by analysis of variance (statistical software, MINITAB-Version 15). The model-function equation for boron adsorption on calcined alunite was obtained. The results showed that temperature, pH and mass of adsorbent affected boron removal by adsorption. Boron removal increased with increasing pH and adsorbent dosage, but decreased with increasing temperature. The optimum conditions were found as pH 10, adsorbent dosage=1g of calcined alunite per 25 mL solution and temperature=25 degrees C by using factorial design. In addition, the effects of parameters such as calcination temperature, pH, temperature, adsorbent dosage and initial boron concentration on boron removal were investigated. The adsorption isotherm studies were also performed. Maximum adsorbent capacity (q(0)) was calculated as 3.39 mg/g. Thermodynamic parameters such as change in free energy (DeltaG degrees), enthalpy (DeltaH degrees) and entropy (DeltaS degrees) were also determined.     

Robustness testing of a tablet formulation using multivariate design

A total of 45 experiments were carried out to evaluate the robustness of two similar tablet formulations—a product of two strengths—with respect to normal batch-to-batch variation of the excipients and the active pharmaceutical ingredient. The formulations consist of 10 ingredients. Because of the differing amounts of active pharmaceutical ingredients, the two formulations also differ in the amounts of two of the diluents and one of the binders. The excipients and active pharmaceutical ingredient were characterized in terms of multiple variables, and principal properties were calculated with principal component analysis. A Plackett and Burman design was applied to the principal properties. The relationships between the design factors and two responses, mean disintegration time and mean crushing strength, were evaluated by using regression methods. Both formulations were found to be robust under controlled conditions.     

Optimization of fluid bed formulations of metoprolol granules and tablets using an experimental design

Background: The granulation process of a metoprolol tartrate (very difficult to process active pharmaceutical ingredient) formulation in laboratory scale fluid bed equipment was studied. Aim: To study the influence of two formulation factors and three process parameters on the characteristics of the granules and subsequently of the tablets, in the case of fluid bed granulating of a powder mix containing metoprolol tartrate. Method: In order to study the influence of formulation factors (binder solution concentration and the silicon dioxide ratio) and process factors (atomizing pressure, the length of the final drying phase, and the inlet air temperature) on the technological and pharmaceutical properties of granules and tablets, a fractional factorial experimental design resolution V+ with five factors and two levels was used. Results: A high atomizing pressure allows us to obtain fine granules with large poly-dispersion index and granules with high tapped and untapped density, tablets with short disintegration time, short mean dissolution time, and a high percentage metoprolol tartrate release in the first 15 minutes. A lower concentration of binder solution allows us to obtain granules with very good flow properties, tablets which have no tendency to stick on the set punch of tabletting machine and no capping. The final drying time of granules has an influence only on the granule's relative humidity and tapped and untapped density, without any influence on the granules flow properties. Conclusions: The practical experimental results from the formulation processed in optimal working conditions were close to the predicted ones by Modde 6.0 software.     

NaLuF4:Yb,Tm up-conversion materials: Investigation of UV emission intensity by experimental design

NaLuF₄ doped Yb/Tm upconversion phosphor was synthesized by a facile hydrothermal method, using EDTA as a chelating agent. The influence of synthesis parameters was investigated on UV emission intensity through face-centered central composite design (CCD). Four parameters including F:RE ratio, pH value, reaction time and ethanol percent were considered as independent variables. It was found that pH value and F:RE ratio have the highest effect on emission intensity and the ethanol percent and the reaction time have mild and low influence on it. Furthermore, at pH 4, nano spherical particles with cubic phase were formed and change of other parameters had low influence on phase transformation. However, the hexagonal micro prisms with the hexagonal phase were predominant at pH?≥?6. The role of EDTA was indicated on phase transformation and aggregation of particles at the various value of pH. It was shown that the crystal phase, the surface smoothness and the particle size are influential factors on UV emission intensity.     

Factorial experimental design: Detecting an outlier with the dynamic variable and the Daniel''s diagram

This article describes how to be sure that there is, or not, an outlier in a two-level experimental design (16 runs or more) with no replicates. It also describes how to discover an outlier if there is one, and how to estimate the true value of this outlier. The method is based on the use of a dynamic variable and the “small effects” of the Daniel's diagram. The theoretical relationship between the “small effects” and the dynamic variable is established in the case of a two-level factorial design. The method is applied to two examples to show how the following three problems can be solved: whether there is, or not, an aberrant response, to detect an outlier when there is one and to estimate the value of the outlier as if it had not been aberrant.     

Simultaneous optimization of the microextraction of coffee volatiles using response surface methodology and principal component analysis

It is well known that no single experimental condition can be found under which the extraction of all the volatile compounds in a gas chromatographic analysis of roasted coffee beans by headspace-solid phase microextraction (HS-SPME) is maximized. This is due to the large number of peaks recorded. In this work, the scores vector of the first principal component obtained from PCA on chromatographic peak areas was used as the response to find the optimal conditions for simultaneous optimization of coffee volatiles extraction via response surface methodology (RSM). This strategy consists in compressing several highly correlated peak areas into a single response variable for a central composite design (CCD). RSM was used to identify an optimal factor combination that reflects a compromise between the partially conflicting behavior of the volatiles groups. This simultaneous optimization approach was compared with the desirability function method. The versatility of the PCA-RSM methodology allows it to be used in other chromatographic applications, resulting in an interpretable procedure to solve new analytical problems.     

Methodological approaches for histamine quantification using derivatization by chloroethylnitrosourea and ELISA measurement: Part I. Optimization of derivated histamine detection with coated-plates using optimal design

Using derivatization by chloroethylnitrosourea (CENU) a new strategy was used for raising antibodies directed against hapten (< 300 Da) and the quantification of these haptens by ELISA. After raising antibodies directed against histamine, they were characterized and used for ELISA measurements. The development of a quantitative method needs an optimization of both detection and derivatization step. Experimental design methodology has been applied to optimize the conditions of the detection of the derivatized histamine. Methods and results were closely related.     

Development of a fast,lean and agile direct pelletization process using experimental design techniques

A novel hot melt direct pelletization method was developed, characterized and optimized, using statistical thinking and experimental design tools. Mixtures of carnauba wax (CW) and HPMC K100M were spheronized using melted gelucire 50–13 as a binding material (BM). Experimentation was performed sequentially; a fractional factorial design was set up initially to screen the factors affecting the process, namely spray rate, quantity of BM, rotor speed, type of rotor disk, lubricant–glidant presence, additional spheronization time, powder feeding rate and quantity. From the eight factors assessed, three were further studied during process optimization (spray rate, quantity of BM and powder feeding rate), at different ratios of the solid mixture of CW and HPMC K100M. The study demonstrated that the novel hot melt process is fast, efficient, reproducible and predictable. Therefore, it can be adopted in a lean and agile manufacturing setting for the production of flexible pellet dosage forms with various release rates easily customized between immediate and modified delivery.     

Application of Taguchi methods to surface mount processes

This paper describes the implementation of a Taguchi experiment for the placement of surface mount components as part of a process at Mars Electronics. The justification for the experimental work, the practical problems in its implementation and the significance of the results obtained are described. The experiment is seen as part of a programme and the implications of the results obtained for subsequent experimentation are discussed.     

DEM simulation and experimental validation for mechanical response of ellipsoidal particles under confined compression

The representation of non-spherical particles in discrete element method (DEM) has not been addressed adequately. Although the multiple sphere method (MSM) is the most popular approach to describe non-spherical particle shape, the validity of the MSM has not been established yet. The purpose of this study is to examine the validity and adequacy of the MSM. A uni-axial confined compression test was designed and set up to study the mechanical behaviour of an ellipsoidal granular assembly under vertical loading and the load transfer to the contacting boundary. Four levels of multi-sphere approximation for an axi-symmetric ellipsoidal particle were employed in DEM simulation to investigate the adequacy of multi-sphere approximation. A comparison on compression characteristics between the numerical and experimental results was made and discussed in this paper. Most of the compared physical properties showed reasonable agreement, indicating that capturing the key linear dimensions of a non-spherical particle may be sufficient to predict reasonable results. A small number of sub-spheres (say, N?≥?5) for representing an axi-symmetric ellipsoidal particle can give plausible results. However, the DEM simulations also produced a certain extent of discrepancy in loading stiffness with experiments. Plausible explanations are provided and require further investigation.     

From hexafluorotitanate waste to TiO2 powder: Characterization and evaluation of the influence of synthesis parameters by the experimental design method

This paper was focused on the possible chemical synthesis routes to obtain titanium dioxide, TiO₂, from hexafluorotitanate waste and it was aimed to identify the parameters affecting the formation of crystalline titanium dioxide, TiO₂, phases (anatase or rutile). An experimental design method, inspired from the Taguchi approach, was used to assess the positive or negative impact of input factors on the formation of rutile and anatase, which were the output factors of interest. An experimental matrix was built up with coded values for each factor and coefficients were computed to point out a correlation between outputs and inputs. Particular attention was paid to the chemical compounds (decomplexing agents) added to precipitate TiO₂ from hexafluorotitanates and to the dehydration temperature used to obtain TiO₂ crystallized phases. The powders resulting from the syntheses were investigated by X-Ray diffraction analysis. Their chemical compositions were determined by Inductively Coupled Plasma Atomic Emission Spectroscopy. Data-matching revealed the best synthesis conditions in terms of crystallized TiO₂ content, and this was confirmed by calculating the processing yields. The results showed that silica and calcium hydroxide were the most efficient decomplexing agents leading to the formation of anatase.     

Evaluation of the influences of solution path length and additives concentrations on the solar photo-Fenton degradation of 4-chlorophenol using multivariate analysis

This study reports the photodegradation of 4-chlorophenol (4-CP) in aqueous solution by the photo-Fenton process using solar irradiation. The influence of solution path length, and Fe(NO(3))(3) and H(2)O(2) concentrations on the degradation of 4-CP is evaluated by response surface methodology. The degradation process was monitored by the removal of total organic carbon (TOC) and the release of chloride ion. The results showed a very important role of iron concentration either for TOC removal or dechlorination. On the other hand, a negative effect of increasing solution path length on mineralization was observed, which can be compensated by increasing the iron concentration. This permits an adjustment of the iron concentration according to the irradiation exposure area and path length (depth of a tank reactor). Under optimum conditions of 1.5 mM Fe(NO(3))(3), 20.0 mM H(2)O(2) and 4.5 cm solution path length, 17 min irradiation under solar light were sufficient to reduce a 72 mg CL(-1) solution of 4-CP by 91%.     

Power of experimental design studies for the validation of pharmaceutical processes: case study of a multilayer tablet manufacturing process

Experimental design studies (EDS) are already widely used in the pharmaceutical industry for drug formulation or process optimization. Rare are the situations in which this methodology is applied for validation purposes. The power of this statistical tool, key element of a global validation strategy, is demonstrated for a multilayer tablet manufacturing process. Applied to the Geomatrix® system generally composed of one compression and three granulation processes, time and strictness gains are non-negligible. Experimental design studies are not used in this work for modeling. Introduced at each important step of the process development, they allow for the evaluation of process ruggedness at pilot scale and specifications for full production. A demonstration of the complete control of key process parameters is given, identified throughout preliminary studies.     

A review of robust design methods for multiple responses

Problems in engineering design often involve determining design variable settings to optimize individual product performance for multiple criteria, which are often in conflict. We review mathematically rigorous techniques from the statistical literature for finding a vector x of design variable settings, which produces an optimal compromise solution among a group of prioritized response variables. The best compromise solution is typically gained by optimizing an objective function, which incorporates the prioritized demands of multiple responses. Since most multi-response objective functions are constructed by combining the functions used to optimize univariate responses, a review of the prominent univariate approaches is presented first. A multivariate approach from the engineering literature called the compromise Decision Support Problem is also reviewed. Finally a table comparing the relative merits of the different multivariate approaches summarizes the article in a concise and user-friendly fashion.     

A review of robust design methods for multiple responses

Problems in engineering design often involve determining design variable settings to optimize individual product performance for multiple criteria, which are often in conflict. We review mathematically rigorous techniques from the statistical literature for finding a vector x of design variable settings, which produces an optimal compromise solution among a group of prioritized response variables. The best compromise solution is typically gained by optimizing an objective function, which incorporates the prioritized demands of multiple responses. Since most multi-response objective functions are constructed by combining the functions used to optimize univariate responses, a review of the prominent univariate approaches is presented first. A multivariate approach from the engineering literature called the compromise decision support problem (cDSP) is also reviewed. Finally, a table comparing the relative merits of the different multivariate approaches summarizes the article in a concise and user-friendly fashion.     

Studies on the Reduction of Coefficient of Variation: A Case Study

In a spinning mill, yarn is the final product. Linear density expressed in terms of count is one of the important characteristics of yarn. Because variability of textile strands increases as the linear density increases, the variability in the count is often measured in terms of coefficient of variation (CV)%. The yarn with a high CV% of count leads to a higher end breakage rate during the spinning and subsequent weaving/knitting operations, and consequently, results in lesser productivity and poorer appearance quality of the woven/knitted fabric. When this woven/knitted fabric is dyed, uneven shades are generated. Because the production of yarn involves processing of raw cotton in multimachines at multistages, possible sources that lead to a high CV% of count are many. Enrick's (1960) analysis procedure, which is based on the modification of the range method for analysis of variance, is used conventionally for detecting the stages where excessive “between-machine” differences are present. When the CV% of count is inflated due to the generation of systematic variation in any machine or introduction of high variability by any machine, this inflation remains undetected when using Enrick's procedure. The case study presented here demonstrates that a step-by-step analysis of linear densities of different stage-outputs starting from yarn to card sliver, using appropriate nested design models along with Duncan's multiple range test, is very useful in detecting all possible sources of a high CV% of count of yarn.     

Multiblock analysis of environmental measurements: A case study of using Proton Induced X-ray Emission and meteorology dataset obtained from Islamabad Pakistan

This paper reports the analysis of a multiblock environmental dataset consisting of 176 samples collected in Islamabad Pakistan between February 2006 and August 2007. The concentrations of 32 elements in each sample were measured using Proton Induced X-ray Emission plus black carbon for both coarse and fine particulate matter. Six meteorological parameters were also recorded, namely maximum and minimum daily temperatures, humidity, rainfall, windspeed and pressure. The data were explored using Principal Components Analysis (PCA), Partial Least Squares (PLS), Consensus PCA, Multiblock PLS, Mantel test, Procrustes analysis and the R_V coefficient. Seasonal trends can be identified and interpreted. Using the elemental composition of the particulates it is possible to predict meteorological parameters. Based on the models from PLS, it is possible to use elemental composition in the airborne particulates matter (APM) to predict meteorological parameters. The results from block similarity measures show that fine APM resembles meteorological parameters better than coarse APM. Multiblock PLS models however are not better than classical PLSR. This paper also demonstrates the potential of multiblock approach in environmental monitoring.     

A new tolerance design method for a secondary rechargeable battery using design of experiments with mixture

Mixing errors in the manufacturing process of a mixture may cause a sizeable variation in the performance of the product, leading to the need for the tolerance design. Even though a variety of procedures have been proposed for the optimal tolerance design based on quality loss and manufacturing costs, there are no available tolerance design methods when mixing errors exist in the manufacturing process of a mixture. In this article, we propose a new tolerance design method for the case where mixing errors are involved in massive manufacturing process of a secondary rechargeable battery. Using an approximation method, we derive quality loss function, reflecting the effects of mixing errors on the product performances. Statistical design of mixture experiments is applied to build empirical models of performances as functions of component proportions in the corresponding quality loss function. A real‐life case study on the tolerance design of a secondary battery is provided for the illustration of the proposed method. The results show the efficiency of the proposed method in designing the tolerances to minimize the quality loss and manufacturing costs. Copyright © 2008 John Wiley & Sons, Ltd.