基于宽容分层序列法的飞机装配公差稳健设计技术

飞机制造中由于工序能力指数和公差等设计变量存在变差,可能导致无法满足飞机装配质量要求以及制造成本波动较大的问题。运用稳健设计方法建立了飞机装配公差的可行稳健性和敏感稳健性两类设计模型。可行稳健设计考虑了公差等设计变量对装配可行性的影响,使其变差不影响装配功能的实现;敏感稳健性设计则考虑了公差等设计变量对制造成本和装配质量的影响,在目标成本较小的前提下使得目标成本和装配质量受设计变量变差的影响最小。提出了针对飞机装配公差可行敏感稳健设计的多目标优化问题的宽容分层序列求解算法。将公差设计中制造成本、装配质量波动、制造成本波动多个设计目标按照重要性依次排序。首先求解成本最小情况下的公差一般优化解,然后在成本最小值的宽容约束下,求得具有装配质量波动最小值的公差,最后在上述两个优化目标的宽容约束下,求得成本波动最小的最优公差。应用实例和分析结果表明了方法的有效性。       

Simultaneous optimal selection of design and manufacturing tolerances with different stack-up conditions using scatter search

The allocation of design and manufacturing tolerances directly influences the manufacturing cost and functionality of a product. Traditionally, it is carried out in two phases; CAD and CAPP, in a sequential manner. This approach has the drawbacks of more lead-time and sub-optimality. The present work reports on a procedure to simultaneously allocate both design and manufacturing tolerances based on minimum total manufacturing cost. The optimization model for tolerance design is a non-linear multivariable problem. Since such a problem may have a noisy surface, there is a need to apply an efficient global optimization technique. In the present work, scatter search, one of the recently emerged optimization techniques in the area of metaheuristics, is applied successfully to determine the optimal tolerances at the minimum manufacturing cost. An example is taken from the literature to explain the proposed methodology. The results exhibit the effectiveness of the proposed algorithm over other methods.     

Concurrent tolerance design for manufacture and assembly with a game theoretic approach

This paper proposes a game theoretic approach for concurrent tolerance design considering the practical manufacturing process and assembly process, to achieve lower manufacturing cost and good product assemblability. The optimization objectives and constraints for concurrent tolerance design for manufacture and assembly are discussed, and the key technologies for concurrent tolerance design with game theory are investigated, including the strategy set division, payoff calculation, and Nash equilibrium evolution. An optimization algorithm is proposed to achieve concurrent tolerance design with a game theoretic approach, and the genetic algorithm is used to conclude the Nash equilibrium of the game for manufacture and assembly. Finally, a case study is given to verify the proposed approach.     

Optimum tolerance design using component-amount and mixture-amount experiments

The tolerance design problem involves optimizing component and assembly tolerances to minimize the total cost (sum of manufacturing cost and quality loss). Previous literature recommended using traditional response surface methodology (RSM) designs, models, and optimization techniques to solve the tolerance design problem for the worst-case scenario in which the assembly characteristic is the sum of the component characteristics. In this article, component-amount (CA) and mixture-amount (MA) experiment approaches are proposed as more appropriate for solving this class of tolerance design problems. The CA and MA approaches are typically used for product formulation problems, but can also be applied to this type of tolerance design problem. The advantages of the CA and MA approaches over the RSM approach and over the standard, worst-case tolerance-design method are explained. Reasons for choosing between the CA and MA approaches are also discussed. The CA and MA approaches (experimental design, response modeling, and optimization) are illustrated using real examples.     

基于DFA和DFC的综合公差优化

公差是机械设计和制造过程中最重要的参数之一,其对加工成本和产品质量有很大的影响。本文采用 DFA和DFC的综合方法对制造过程中的装配精度进行分析和综合,建立了以公差为主的成本信息模型,对设计公 差和加工公差进行了系统分析,以最低制造成本为目标,根据成本 公差间的函数关系,建立了非线性的公差优化模 型,并采用遗传算法使这一问题得到了很好的解决。实例证明该方法是可行的。并为并行工程实施中其他的DFX 与DFC结合实现制造成本最低提供了良好的解决方案。     

一种基于制造环境的统计公差分析方法

在并行公差设计理论的基础上,提出基于制造环境的面向装配的统计公差分析方法,使得在公差设计中,考虑实际加工环境的加工状况,即各种加工方法的工序能力。在此基础上,建立基于工序能力的统计公差分析模型。在假定过程平均漂移为均匀分布和正态分布两种情况下,计算出制造偏差的概率密度函数,进而推导出线性装配相应函数的概率统计特性值,为统计公差优化设计奠定了基础．     

Simultaneous process mean and process tolerance determination with asymmetrical loss function

Process design involves process mean and process tolerance determination. Process mean determination is finding the best settings for product quality, without affecting manufacturing cost. However, process tolerance determination is a manufacturing process selection which generally affects manufacturing cost and product quality. In this study, asymmetric quality loss is considered in measuring product quality, and tolerance cost is adopted in representing manufacturing cost. To reflect the combined effect of process mean and process tolerance completely, failure cost is added to the category of manufacturing cost. Then, based on the sum of these three costs, a simultaneous optimization of process mean and process tolerance is determined for process planning in the early stages of development.     

基于绿色制造的公差设计

公差分析和公差分配是公差设计的两个重要方面。本文介绍了绿色制造的概念和关键技术,研究了绿色制造在公差设计中的应用,提出了在绿色制造技术下的公差分配优化的目标函数,并且论述了基于绿色制造的公差优化的方法。     

公差优化中的制造成本估算

以公差优化为目标进行制造成本估算是对公差———成本关系进行建模的基础问题。文章分析比较了传统的制造成本的计算方法,提出了已知制造系统状态时对公差———制造成 本关系的建模 方法———多参数公式法,详细阐述了该方法的使用环境以及提出该方法的必要性及合理性,并以实例对其可用性进行了说明和验证。     

A Metamodeling Method Based on Support Vector Regression for Robust Optimization

Metamodeling techniques have been used in robust optimization to reduce the high computational cost of the uncertainty analysis and improve the performance of robust optimization problems with computationaUy expensive simulation models.Existing metamodels main focus on polynomial regression(PR),neural networks(NN)and Kriging models,these metamodeis are not well suited for large-scale robust optimization problems with small size training sets and high nonlinearity.To address the problem,a reduced approximation model technique based on support vector regression(SVR)is introduced in order to improve the accuracy of metamodels.A robust optimization method based on SVR is presented for problems that involve high dimension and nonlinear.First appropriate design parameter samples are selected by experimental design theories,then the response samples are obtained from the simulations such as finite element analysis,the SVR metamodel is constructed and treated as the mean and the variance of the objective performance functions.Combining other constraints,the robust optimization model is formed which can be solved by genetic algorithm(GA).The applicability of the method developed is demonstrated using a case of two-bar structure system study.The performances of SVR were compared with those of PR,Kriging and back-propagation neural networks(BPNN),the comparison results show that the prediction accuracy of the SVR metamodel was higher than those of other metamodels under uncertainty.The robust optimization solutions are near to the real result,and the proposed method is found to be accurate and efficient for robust optimization.This reaserch provides an efficient method for robust optimization problems with complex structure.     

公差稳健优化设计的研究

为了解决产品加工成本与质量稳健的协调性问题,提出了一种新的公差稳健优化设计数学模型.依据公差稳健设计的思想,考虑产品质量的模糊性,以封闭环误差分布概率密度函数的方差和优质品概率之比为设计目标,建立了公差优化设计产品质量稳健性损失成本目标函数,并研究了优质品率和封闭环误差分布方差的确定方法.以加工成本和产品质量稳健性损失成本为目标,以模糊装配可靠度、可取公差极限范围为约束条件,建立了公差多目标优化数学模型.举例说明了文中所述的公差稳健优化设计方法的应用,采用遗传算法实现了公差的多目标优化设计.实例表明,该方法能够协调零件的加工成本和产品质量的稳健性损失成本,使优化指标的综合性能最佳.     

Particle swarm optimization (PSO) algorithm for optimal machining allocation of clutch assembly

Nowadays tolerance optimization is increasingly becoming an important tool for manufacturing and mechanical design. This seemingly, arbitrary task of assigning dimension tolerance can have a large effect on the cost and performance of manufactured products. With the increase in competition in today’s market place, small savings in cost or small increase in performance may determine the success of a product. In practical applications, tolerances are most often assigned as informal compromises between functional quality and manufacturing cost. Frequently the compromise is obtained interactively by trial and error. A more scientific approach is often desirable for better performance. In this paper particle swarm optimization (PSO) is used for the optimal machining tolerance allocation of over running clutch assembly to obtain the global optimal solution. The objective is to obtain optimum tolerances of the individual components for the minimum cost of manufacturing. The result obtained by PSO is compared with the geometric programming (GP) and genetic algorithm (GA) and the performance of the result are analyzed .     

基于容差模型和正交试验的四连杆变幅机构稳健优化设计

针对设计函数为隐函数或高度非线性函数的工程设计优化问题，提出了一种较为实用的、综合运用容差模型和正交试验法的稳健优化方法，并将该方法应用到四连杆变幅机构的优化设计中，结果表明，稳健优化后的变幅机构性能得到了改善，设计质量得到了提高。     

动车组传动齿轮模糊稳健修形设计

考虑到齿轮的修形参数和性能参数受制造和使用过程中各影响因素的扰动影响,提出了一种基于改进容差模型和模糊理论的动车组传动齿轮稳健修形设计方法.确定了齿轮稳健修形设计中的可控因素与不可控因素,结合正交试验设计与Romax运动仿真获取试验样本点;利用多项式函数拟合传动误差峰峰值的响应面近似模型.在此基础上,引入模糊理论,基于...     

The study of cost-tolerance model by incorporating process capability index into product lifecycle cost

To reduce the cost of manufacturing systems, many studies of cost minimization have been performed. Since tolerance design significantly affects the manufacturers’ cost, the optimization of cost-tolerance allocation will be an important issue for reducing these costs. Costs incurred in a product life-cycle include manufacturing cost and quality loss. However, most cost-tolerance optimization models frequently ignore the concept of quality loss and may not lead to an accurate analysis of the tolerance. Until now, process capability analysis has been the tool used to evaluate the adequacy of a production tool in meeting a quality target. Hence, the concept of process capability analysis should be included into the cost-tolerance optimization model. In this study, a flexible cost-tolerance optimization model will be constructed by integrating the process capability index into the product life-cycle cost function. The constructed cost-tolerance optimization model simultaneously considers the manufacturing cost of the components, the process capability of the manufacturing operations, and the quality loss of products. The decision-maker can apply the proposed cost-tolerance optimization model to determine a reasonable tolerance with minimum total cost including consideration of the process capability .     

Tolerance design optimization of machine elements using genetic algorithm

An important problem that faces design engineers is how to assign tolerance limits. In practical applications, tolerances are most often assigned as an informal compromise between functionality, quality and manufacturing cost. Frequently, the compromise is obtained iteratively by trial and error. A more scientific approach is often desirable for better performance. In this paper, a genetic algorithm (GA) is used for the design of tolerances of machine elements to obtain the global optimal solution. The objective is to design the optimum tolerances of the individual components to achieve the required assembly tolerance, zero percentage rejection of the components and minimum cost of manufacturing. The proposed procedure using GA is described in this paper for two tolerance design optimization problems: gear train and overrunning clutch assemblies. Results are compared with conventional techniques and the performances are analyzed.     

基于工序加工能力的并行公差优化设计

提出一种基于工序加工能力的并行工序公差优化设计方法。在产品的初步结构设计阶段，通过相配零件的加工工艺规划把装配功能公差表示为零件的工序公差，建立以加权制造总成本最小为目标，以并行公差链、标准化的工序公差系数、机床最大经济极限公差为约束的非线性并行公差优化设计模型，求解该模型得到最佳的工序公差。最后给出了并行公差优化设计的一个工程实例，结果表明，所提的方法具有比传统串行等精度方法更合理、工序公差数值更大的优点。     

基于多重相关特征质量损失函数的公差优化设计

在重点推导了具有多重相关特征产品的质量损失与尺寸公差的函数关系的基础上,提出了多重相关特征产品的公差优化设计方法,建立了基于制造成本一质量损失的公差优化设计的综合模型,建立该模型的目的是寻求制造成本和质量损失之间的平衡,实现旨在提高产品质量和降低成本的公差优化设计。应用实例验证了所提出方法的有效性。     

尺寸公差与形位公差混合优化分配

为解决尺寸公差与形位公差混合优化分配问题,提出了一种公差优化分配方法.根据成本-公差函数和尺寸公差与形位公差的关系,建立了以最小制造总成本为目标的非线性公差混合优化分配模型.该模型的约束包括装配尺寸链的功能要求和加工能力.求解该模型能同时得到优化的尺寸公差和形位公差.最后,分别用公差混合优化分配法和传统方法对一个实例进行公差分配,结果表明所提方法比传统方法更优越.     

Optimal Process Tolerance Balancing Based on Process Capabilities

An optimal approach for process tolerance balancing is presented. The new approach is based on process capabilities and is to be used in the stage of process planning. A nonlinear programming model is used to simultaneously optimise process tolerances of required operations. In the optimisation model, the objective function is to minimise the total manufacturing cost with different weighting factors. Using the estimated standard deviations of the dimensions and the manufacturing cost-tolerance functions, the constraint equations for the process tolerance chains and the manufacturing capability indices are established, together with a model for the economical tolerance bounds of machine tools. A practical example was used to verify the usefulness of the proposed approach. The results of the comparative study show that the proposed approach is more advantageous in relaxing tolerance requirements and in reducing scrap rates generally, compared with the existing methods. ID="A1"Correspondance and offprint requests to: Dr Y. Gao, Department of Mechanical Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong. E-mail: meygao@ust.hk