Surface generation analysis in micro end-milling considering the influences of grain

The micro end-milling method is a universal micro manufacturing method used to fabricate micro parts and complex 3D micro structures with many materials. Although micrometer size is achieved, their surface quality is not satisfactory. In this paper, the influences of different metal phase grains are researched, and the micro end-milling process is described considering the workpiece with anisotropic properties in micro scope. In this research, the physical characteristics of different grains, specifically friction coefficient μ and elastic modulus E, are very critical to determine the processes of the chip formation and the surface generation. And the chips are often discontinuous because of the grain boundary effect. Through the micro end-milling experiment, the results of bottom surface correlate very well with the theoretical analysis.     

考虑不确定性因素的微电网经济运行的优化

本文针对微电网经济运行优化问题,考虑分布式可再生能源的输出功率具有随机性特点,提出了一种基于场景分解及场景策略聚合机制的优化方法.该方法针对所提出的优化问题中,统计信息不足以建立一个随机规划模型的难点,首先进行了场景分析,将原优化问题分解为多个场景子优化问题;其次引入场景束约束,将场景策略分为可容许策略、可实现策略和偶然策略,依照可用信息的进化机制,迭代修正每个场景子优化问题,并且采用动态规划方法求解每个场景子优化问题.然后,统计分析子优化问题最优解的主要特征和趋势,最终得到微电网经济运行优化问题的最优解.通过仿真验证了所提出方法的有效性.     

Simulation-based model for the optimization of machining parameters in a metal-cutting operation

To achieve a certain measurable performance in cutting machines, the machine parameters need to be optimized. Several constraints determine the possible values that these parameters can take. Although parameters are usually assumed to be deterministic, in practice, it is common to find variations on the characteristics of the products or the processes. Modeling machining parameters as stochastic factors provides a more realistic representation of cutting operations. Moreover, multiple operational objectives are of interest, in many real situations, these multiple objectives are conflicting. Consequently, the problem of setting the parameters becomes a trade-off situation. This paper presents a novel Simulation-based Multi-Objective Optimization (SimMOpt) solution procedure. The procedure is divided into two phases: (1) finding initial solutions and, (2) using a simulated annealing-based method for finding neighboring solutions. In the first phase, non-linear goal programming is used for finding high quality initial solutions. The second phase incorporates Pareto Archive Evolution Strategy (PAES) and hypotheses testing for searching near-optimal solutions for a set of stochastic parameters (i.e., cutting speed, feed rate, and depth of cut) in metal cutting operations. Three objectives are optimized (i.e., operation time, operation cost, and quality of the product). The results from implementing this procedure are analyzed and compared to a baseline methodology based on the Multi-Objective Simulated Annealing (MOSA) algorithm. The analysis demonstrates that the proposed method outperforms the Genetic Algorithm (GA), which was the benchmark algorithm, in terms of the solution quality of all the objectives. More importantly, the solutions from using the SimMOpt procedure outperform those obtained from using an enhanced MOSA-based approach (i.e., 4.71% improvement in the hypervolume approximation).     

Power density optimization for MEMS piezoelectric micro power generator below 100 Hz applications

Microsystem Technologies - In piezoelectric based micro-power generator (PMPG), electrical energy is generated from mechanical vibration by gaining on the piezoelectric effects. This study...     

Machine learning-based optimization of process parameters in selective laser melting for biomedical applications

Journal of Intelligent Manufacturing - Titanium-based alloy products manufactured by Selective Laser Melting (SLM) have been widely used in biomedical applications, owing to their high...     

面向组件重构的工艺信息模型的研究

阐述了CAPP系统的发展要求，分析了面向组件重构的现代工艺信息模型及其格式，描述了以产品为中心的信息管理模型，并介绍了一个面向组件重构的CAPP系统的模型实例。     

Miniaturized plastic micro plates for applications in HTS

This paper is focused on the development of plastic nano titer plates for applications in high throughput screening (HTS). For screening systems with integrated confocal microscopes plastic chips have been fabricated by injection molding and injection compression molding which contain micro wells with volumes of 0.9 μl and 1.4 μl and bottom plates with thicknesses of 120 μm and 200 μm. In addition, plastic chips with through holes have been joined with 160 μm glass plates by an adhesive printing process. First fluorescence correlation spectroscopy (FCS) measurements show that the plastic plates with glass bottoms are qualified as screening grade FCS nano titer plates. Received: 15 May 1999 / Accepted: 19 May 1999     

Query optimization for nontraditional database applications

Database query languages and their use for programming nontraditional applications, such as engineering and artificial intelligence applications, are discussed. In such environments, database programs are used to code applications that work over large data sets residing in databases. Optimizing such programs then becomes a necessity. An examination is made of various optimization techniques, and transformations are suggested for improving the performance of database programs. These transformations result in new equivalent database programs with better space and time performance. Several of these techniques apply to classical query languages, although extended query languages which include an iteration operator are specifically discussed     

Design and realization of micro structured surfaces for thermodynamic applications

The functionality of surfaces, especially for thermodynamic applications, can be enhanced by help of a specific surface modification. Therefore this study investigates different selected surface structures and their influence on the heat transfer capability. Specific micro geometries are in focus of this research. A systematic design and a determination of appropriate thermodynamic micro structures by the help of FEM multiphysics simulations were executed. Afterwards the investigated structures were fabricated applying electrochemical and laser beam machining. Furthermore a systematic analysis of the exactness and the surface quality was carried out, which underlines the potential of these procedures for micro structuring of surfaces for thermodynamic applications.     

Numerical study of a membrane-type micro check-valve for microfluidic applications

In this paper, we present a method to simulate membrane-type micro check-valve using finite element method with fluid structure interaction formulation. The designed micro check-valve which is analogue of semiconductor device, diode, allows the fluid to pass in forward-mode and blocks it in reverse mode. To have a better understanding on the valve design we also studied the effect of design dimensions on the valve performance. Our study shows the valve flow rate-pressure curve is similar to diode current–voltage characterization curve. A series of simulations were carried out by using two-way fully-coupled Fluid Structure Interaction (FSI) analysis. Using Arbitrary Lagrangian–Eulerian (ALE) method in combination with high viscosity region instead of solid valve-seat enables the designer to overcome simulations difficulties and reduces the amount of calculation time by not considering the contact phenomenon of the membrane and the valve seat. The results show the valve can withstand pressures of up to 11 kPa in reverse-mode regardless of membrane’s hole-size and length of chamber-inlet. Also, chamber-inlet size has high effect on valve opening threshold point in a way that increment of chamber-inlet area will reduce opening threshold point and vice versa.

     

A microreactor for hydrogen production in micro fuel cell applications

A silicon-chip based microreactor has been successfully fabricated and tested for carrying out the reaction of methanol reforming for microscale hydrogen production. The developed microreactor in combination with a micro fuel cell is proposed as an alternative to conventional portable sources of electricity such as batteries due to its ability to provide an uninterrupted supply of electricity as long as a supply of methanol and water can be provided. The microreformer-fuel cell combination has the advantage of not requiring the tedious recharging cycles needed by conventional rechargeable lithium-ion batteries. It also offers significantly higher energy storage densities, which translates into less frequent "recharging" through the refilling of methanol fuel. The microreactor consists of a network of catalyst-packed parallel microchannels of depths ranging from 200 to 400 /spl mu/m with a catalyst particle filter near the outlet fabricated using photolithography and deep-reactive ion etching (DRIE) on a silicon substrate. Issues related to microchannel and filter capping, on-chip heating and temperature sensing, introduction and trapping of catalyst particles in the microchannels, flow distribution, microfluidic interfacing, and thermal insulation have been addressed. Experimental runs have demonstrated a methanol to hydrogen molar conversion of at least 85% to 90% at flow rates enough to supply hydrogen to an 8- to 10-W fuel cell.     

面向微操作的显微视觉系统自动聚焦优化算法

研究了面向微操作的显微视觉系统自动聚焦评价函数和聚焦控制策略。首先,分析显微图像特点并做预处理;接着引入像素相关性指标,并结合梯度函数形成一种新的图形清晰度评价函数,改善了函数的灵敏度和抗噪性;最后对传统爬山算法进行改进,在粗调阶段以大步长搜索并用曲线拟合的方法快速定位到峰值点附近,精调阶段以小步长搜索到评价函数值下降点即可准确定位到焦平面,该算法避免了复杂的阈值设定问题,与传统爬山法相比,在一定程度上提高了聚焦速度,并大幅提高了聚焦成功率。     

Aeroelastic topology optimization of membrane structures for micro air vehicles

This work considers the aeroelastic optimization of a membrane micro air vehicle wing through topology optimization. The low aspect ratio wing is discretized into panels: a two material formulation on the wetted surface is used, where each panel can be membrane (wing skin) or carbon fiber (laminate reinforcement). An analytical sensitivity analysis of the aeroelastic system is used for the gradient-based optimization of aerodynamic objective functions. An explicit penalty is added, as needed, to force the structure to a 0–1 distribution. The dependence of the solution upon initial design, angle of attack, mesh density, and objective function are presented. Deformation and pressure distributions along the wing are studied for various load-augmenting and load-alleviating designs (both baseline and optimized), in order to establish a link between stiffness distribution and aerodynamic performance of membrane micro air vehicle wings. The work concludes with an experimental validation of the superiority of select optimal designs.     

Nonparametric gradient-less shape optimization for real-world applications

A nonparametric gradient-less shape optimization approach for finite element stress minimization problems is presented. The shape optimization algorithm is based on optimality criteria, which leads to a robust and fast convergence independent of the number of design variables. Sensitivity information of the objective function and constraints are not required, which results in superior performance and offers the possibility to solve the structural analysis task using fast and reliable industry standard finite element solvers such as ABAQUS, ANSYS, I-DEAS, MARC, NASTRAN or PERMAS. The approach has been successfully extended to complex nonlinear problems including material, boundary and geometric nonlinear behavior. The nonparametric geometry representation creates a complete design space for the optimization problem, which includes all possible solutions for the finite element discretization. The approach is available within the optimization system TOSCA and has been used successfully for real-world optimization problems in industry for several years. The approach is compared to other approaches and the benefits and restrictions are highlighted. Several academic and real-world examples are presented.     

适于高维空间搜索的自组织学习算法

提出了一种有别于当前优化算法框架的自组织学习算法(self-organizing learning algorithm,SLA),该算法融合遗传算法并行搜索与模拟退火串行搜索,结合粒子群学习机制和禁忌搜索机制,实现了系统与环境的交互学习,能够很好地处理传统优化方无法应对的高维非线性优化问题.SLA分自学习和互学习两个智能化学习阶段,先进行基于自学习机制的邻域禁忌搜索,保证局部极值的收敛,然后通过信息共享平台,进行基于互学习机制的广域禁忌搜索,保证全局极值的收敛.系统通过与环境交互学习而自适应地调整搜索策略和相关参数,使得搜索过程能够有效地避免盲目性,而具有相当的自组织性.最后,通过高维测试函数的对比仿真实验表明,SLA在由小型低维空间转入超大型高维空间时,仍能够与环境保持稳定,透明的交互学习,其全局搜索能力和整体稳健性明显优于其它搜索方法.     

Neural techniques for combinatorial optimization with applications

After more than a decade of research, there now exist several neural-network techniques for solving NP-hard combinatorial optimization problems. Hopfield networks and self-organizing maps are the two main categories into which most of the approaches can be divided. Criticism of these approaches includes the tendency of the Hopfield network to produce infeasible solutions, and the lack of generalizability of the self-organizing approaches (being only applicable to Euclidean problems). The paper proposes two new techniques which have overcome these pitfalls: a Hopfield network which enables feasibility of the solutions to be ensured and improved solution quality through escape from local minima, and a self-organizing neural network which generalizes to solve a broad class of combinatorial optimization problems. Two sample practical optimization problems from Australian industry are then used to test the performances of the neural techniques against more traditional heuristic solutions.     

Process observation for the assembly of hybrid micro systems

The automation of micro assembly is becoming more and more important in micro technology. Especially the demands on handling and process observation of hybrid micro systems with optical and mechanical functions are quite high. Because of this process monitoring is inevitably necessary for a better understanding of what is really happening in the micro world. Process visualisation is very important in (micro electronic and mechanical systems) MEMS but does not guarantee an operative micro system. Therefore, instruments for quality control are required to secure a safe and reproducible assembly. The aim of this article is to give an overview over so far used and new devices for process observation and quality control.The authors gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Centre (SFB) 440 Assembly of hybrid microsystems.     

Water wave optimization for combinatorial optimization: Design strategies and applications

Although the community of nature-inspired computing has witnessed a wide variety of metaheuristics, it often requires considerable effort to adapt them to different combinatorial optimization problems (COPs), and few studies have been devoted to reducing this burden. This paper proposes a systematic approach that consists of a set of basic steps and strategies for adapting water wave optimization (WWO), a simple and generic metaheuristic, to concrete heuristic algorithms for different COPs. Taking advantages of the generic algorithmic framework, designers can only focus on adapting the prorogation operator and the wavelength calculation method according to the combinatorial properties of the given problem, and thus easily derive efficient problem-solving algorithms. We illustrate and test our approach on the flow-shop scheduling problem (FSP), the single-objective multidimensional knapsack problem (MKP), and the multi-objective MKP, and then present an application to a machine utilization optimization problem for a large manufacturing enterprise. The results demonstrate that our approach can derive concrete algorithms that are competitive to the state-of-the-arts. Our approach also provides insights into the adaptation of other metaheuristics and the development of new metaheuristics for COPs.     

CAPP中工艺规程主干生成的约束匹配算法

工艺决策是CAPP系统开发的关键，文中提出了一种新的工艺规程主干生成的约束匹配算法，该算法将工艺决策任务分配为特征加工链生成、工序排序和工步排序三个相对独立的子任务，每个子任务只解决一个主要问题而与其它因素无关，并分别采取了不同的子任务求解策略，有效地缩小了排序规模，极大地降低了算法复杂度，该算法的关键技术在RJ-CAPP系统中得到实现。