Minimizing clearance variations and surplus parts in multiple characteristic radial assembly through batch selective assembly

An assembly consists of two or more mating parts. The quality of any assembly depends on quality of its mating parts. The mating parts may be manufactured using different machines and processes with different standard deviations. Therefore, the dimensional distributions of the mating parts are not similar. This results in clearance between the mating parts. All precision assemblies demand for a closer clearance variation. A significant amount of research has already been done to minimize clearance variation using selective assembly. Surplus part is one of the important issues, which reduces the implementation of selective assembly in real situation. Surplus parts are inevitable while the assembly is made from components with undesired dimensional distributions. Batch selective assembly is introduced in this paper to reduce surplus parts to zero and it is achieved by using nondominated sorting genetic algorithm-II. For demonstrating the proposed algorithm, a complex assembly which consists of piston, piston ring and cylinder is considered as an example problem. The proposed algorithm is tested with a set of experimental problem datasets and is found outperforming the other existing methods found in the literature, in producing solutions with minimum clearance variations with zero surplus parts.     

Particle swarm optimization for minimizing assembly variation in selective assembly

Quality of a product is based on the quality of the mating parts. When the parts are assembled interchangeably, the assembly variation will be the sum of the component tolerances. If the assembly variation is to be less than the sum of the component tolerances, selective assembly is the only solution. In conventional selective assembly, the corresponding selective groups are assembled. In this paper, selective group combinations for assembling the mating parts is obtained using particle swarm optimization (PSO). The combination obtained has resulted in an appreciable reduction in assembly variation. The proposed algorithm has been demonstrated for a linear assembly, which consists of three components having equal dimensional distributions. The assembly variation obtained by interchangeable assembly is 36 μm. By implementing the proposed method, the assembly variations are reduced from 36 to 7.2 μm. However, this algorithm can be extended for assemblies with more number of components and with different dimensional distributions.     

Optimising tolerance allocation for mechanical components correlated by selective assembly

Selective assembly can enlarge the tolerances of mechanical components for easier manufacturing. However, the non-independent dimensions of correlated components make it difficult to optimise tolerance allocation for an assembly. This paper proposes a solution for this constrained optimisation problem consisting of tolerances and non-independent dimensions as design variables. The approach is to develop a simplified algorithm applying a Lagrange multiplier method to evaluate the optimal tolerances efficiently. The solution is shown to be a global optimum at the given correlation coefficients. The correlation coefficients are key elements in determining the optimal solution, which is demonstrated in the given examples. The results are helpful in designing tolerances for selective assembly.Notation A _j coefficient matrix off _j - B _i coefficient of cost function - C total manufacturing cost function - C _i manufacturing cost function forx _i - F _j thejth dimensional constraint function - f _j thejth quadratic constraint function - f quadratic constraint vector - H _j thejth Hessian matrix - J _kj element ofn×m Jacobian matrix - L Lagrangian - m number of assembly dimensions - n number of component dimensions - p number of equality dimensional constraints - T tolerance vector of component dimensions [mm] or [°] - tolerance ofx _i [mm] or [°] - tolerance ofZ _j [mm] or [°] - x component dimension vector - x midpoint vector - x _i component dimension [mm] or [°] - x _i midpoint ofx _i [mm] or [°] - Z _j assembly dimension [mm] or [°] - _j confidence coefficient forZ _j - _i confidence coefficient forx _i> - _j given design value ofZ _j [mm] or [°] - Lagrange multiplier vector - _j thejth Lagrange multiplier - * Lagrange multiplier vector at the optimum solution - correlation coefficient forx _i andx _k - _x standard deviation vector - _x ^* standard deviation vector at the optimum solution - _x ⁰ candidate point satisfying the constraintsf( _x ^* )=0 - standard deviation ofx _i      

零间隙装配轴套的分析与应用

通过引入零间隙的概念，论述了零间隙配合的基本原理，并结合矫直机中矫直辊与主轴零间隙装配轴套的结构图，分析了零间隙装配轴套的组成、结构和工作原理。还通过一个具体实例说明了该结构所具有的特点：精度高、操作简单方便、换辊时间短。零间隙装配轴套为冶金行业设备的设计提供了可借鉴的结构。     

A system for supporting rapid assembly modeling of mechanical products via components with typical assembly features

The objective of this study is to optimize the performance of discrete production systems by integration of computer simulation, design of experiment (DOE), and Tabu search (TS). Optimizing performance of a steelmaking workshop was considered as the case of this study, but it could be used to optimize the throughput of other production system. The simulation model is built by considering all major and detailed operations and interacting systems of the workshop. The results and the structure of the integrated simulation model are verified and validated by t test. To integrate simulation outputs with DOE, decision making parameters are defined as number of machines, operators, etc. (k factors). To estimate and assess the effects of each of the factors and their two-way interactions on response variable, a complete 3 ^k factorial design with lower and upper limits and a center point is considered. Furthermore, response surface methodology (RSM) is used to optimize the response variable. Because a first-order model may not be adequate for the RSM, a polynomial order regression equation is developed by least square method. By steepest ascent, the local optimum is identified. However, the global optimal solution is computed by Tabu search which uses a metaheuristic approach. Previous studies use integration of DOE and simulation to find optimum alternative. This is usually conducted by RSM and steepest ascent which locates local optimum solution. However, integration of DOE and TS locates global optimum solution.     

Design of grasping methodologies for rotational assembly components

This article describes a design methodology for grasping assembly components. Three heuristics are developed. The first determines feasible grasping configurations based on component geometric information. The second heuristic determines feasible grasping configurations by including gripper functional attributes. The third heuristic generates the final set of grasping configurations by including the area available for grasping a component. An interactive program written in Fortran 77 is developed to capture the user inputs, and a sample application is described. The methodology does not assume an initial feeding state of the component to the robot. The grasping configurations generated (if more than one) provide the designer with alternate feasible feeding methods.     

选配优化在复杂装配中的应用研究

对于结构复杂,装配尺寸精度要求高的产品装配时,为了得到最优的装配组合,考虑封闭环对装配尺寸的影响程度,给出了三种有利于复杂装配优化选配的方法,并行法、主次法和底层优先法.对复杂装配体的选配问题也进行了描述,分析了装配体的装配类型.     

碗形零件的自动化装配

在汽车生产线上有大量的碗形零件,都是采用人工装配。但单独设置一个操作工会造成人力资源的浪费。对于某些重要的碗形零件,人工操作时如果压装不到位,会影响设备的质量甚至造成设备早期损坏。文章描述了碗形零件自动化装配设备的结构和设计过程,在尽量简化结构的前提下,实现了碗形零件的全自动装配。     

面向多尺寸链的计算机辅助选择装配模型研究

针对现有计算机辅助选择装配的研究仅限于单一尺寸链,且质量损失模型只能用于对称公差带这一问题,提出一种新的面向多尺寸链计算机辅助选择装配的模型。该模型基于田口理论,建立了面向非对称公差带的质量损失评价规则。以遗传算法为基础,设计了可保持种群多样性的快速多目标优化算法,并通过加权巴莱托方法来描述偏好信息。将该模型应用于企业信息系统,并采用统计方法来验证其优化效率。计算实例表明,在相对短的时间内,随着迭代次数的增加,每代的非受控点逐渐收敛于巴莱托前沿,而且解的分布较为均匀,符合一个多目标优化算法的核心要求。     

差速器总成轴向游隙专用检具的设计

通过介绍差速器总成轴向游隙专用检具的设计结构、工作原理以及检测方法,以期实现差速器总成左右转向齿轮的轴向游隙快速、准确测量。     

泵体内轴轴向配合间隙的动态检测

研究泵体内轴(凸轮轴)装配及间隙动态检测方法,采用数字传感器与步进压入系统,在内轴(凸轮轴)动态旋转和轴向预紧的实际工况下,对内轴(凸轮轴)过盈配合装配实施自动的过盈量压装控制及动态间隙检测;通过误差消除技术,克服了静态以及零/部件误差离散性等因素对测量精度的影响,达到较高的重复精度.     

柔性薄壁件装配公差的分析

产品设计过程中需要根据零件公差计尊其装配公差，但是传统的方法均假定零件在装配过程中不发生变形。针对金属薄壁件刚性小，易变形等特点，利用根据数论方法产生的伪随机点对薄壁件的装配公差进行有限元计算。计算结果表明：该方法的计算量远小于Monte Carlo法。并利用正交实验分析方法分析了零件公差对装配误差的影响。     

基于Virtools的夹具元件虚拟装配仿真系统研究

首先对基于Virtools的夹具虚拟装配系统的总体设计思想进行了描述,然后通过3DMax平台建造了夹具元件的三维实体模型,在此基础上利用Virtools平台设计了夹具的动态装配,最后实现了夹具装配的虚拟演示．结果表明,该方法具有投资小,开发周期短,交互性好的特点．     

某齿轮齿圈拨动机构啮合相位优化研究

针对无连杆发动机中辅助启动用齿轮齿圈拨动机构出现的打齿现象,通过运动规律分析、动力学仿真计算,结果表明齿轮齿圈啮合过程符合周转轮系运动法则,而加工误差引起的啮合相位角偏差是导致断齿事故发生的根本原因,提高加工精度,优化啮合相位角,可使该问题得以解决。     

轿车车门装配位置优化

这里以坐标测量机为测量手段,分别测量轿车车门和车身配合面,利用ＵＧＩＩＣＡＤ平台对车门和车身装配间隙进行优化,确定轿车车门最佳装配位置。有效地提高了轿车车门装配质量。     

基于蚁群算法的选择装配

选择装配是一种由低加工精度零件获得高精度装配件的方法,可归纳为一个组合优化问题,蚁群算法是解决这类问题的有效方法.综合考虑选择装配中的匹配率和匹配精度,提出以综合装配质量指标为选择装配的目标函数.为了求解选择装配的组合优化问题,在蚁群算法的框架内提出一个考虑信息素分布为节点模式的蚁群算法解构造图模型,并详细讨论蚁群算法的实现过程.通过对实例的仿真计算,考证该方法的实效性.     

Optimum manufacturing tolerance to selective assembly technique for different assembly specifications by using genetic algorithm

Tolerance on parts dimension plays a vital role as the quality of the product depends on sub components tolerance. Thus, precision products that are manufactured reflect at high manufacturing cost. To overcome this situation, sub components of an assembly may be manufactured with wider tolerance, measured (using latest technologies like image processing) and grouped in partition and corresponding group components may be mated randomly. This present work is to obtain an optimum manufacturing tolerance to selective assembly technique using GA and to obtain maximum number of closer assembly specification products from wider tolerance sub components. A two components product (fan shaft assembly) is considered as an example problem, in which the subcomponents are manufactured with wide tolerance and partitioned into three to ten groups. A combination of best groups is obtained for the various assembly specifications with different manufacturing tolerances. The proposed method resulted nearly 965 assemblies produced out of one thousand parts with 15.86% of savings in manufacturing cost.     

含间隙卫星天线双轴机构动态磨损特性研究

卫星天线双轴驱动机构是天线系统实现精确定位的关键组件,磨损间隙是影响天线指向精度及寿命的主要因素.采用非线性弹簧阻尼模型建立了间隙处的接触碰撞模型,同时采用Coulomb摩擦模型考虑运动副间隙处的摩擦作用,进而建立了含间隙双轴机构的动力学模型,对其进行动力学仿真,提取出接触碰撞时的动力学参数,基于Archard's摩损模型计算运动副间隙的动态磨损量,从而得到间隙运动副的动态磨损特性,为进一步研究非规则时变间隙对卫星天线系统动态性能的影响提供基础.     

Optimal control of inventory accumulation in selective assembly processes

Assembly is a type of production process in which a number of components are combined to yield a final product. Although the concept of interchangeable parts has long been known as the fundamental principle of assembly processes, randomly picking some bulked components with dimensions varying in predefined tolerances may not be a valid approach to obtain special final products with considerably tighter tolerances. Therefore, each of the components needs to be measured and classified into dimensional groups in advance so that quality products can be obtained by matching components from suitable groups. This assembly scheme is called as “selective assembly.” In this work, we consider an assembly case with a pair of components in which one is manufactured on a given number of parallel processes whose settings can be changed to affect the dimensional distribution of the yield while the other component with a slightly bigger tolerance is manufactured on a single process with constant settings. In order to minimize the number of components which could not have been matched with their counterparts, we develop a nonlinear mathematical model to determine the optimal machine settings corresponding to the nominal mean of the component dimension which follows a normal distribution when it is machined. The solution of the mathematical model not only provides the individual settings for the parallel processes producing the same type of component but also the optimal batch sizes at each trial. We have finally used a simulation model of the whole production system, in order to prove that the solution of the mathematical model is able to provide the machine settings which minimize the number of unmatched parts at each trial.