基于信噪比多元质量损失和制造成本的并行公差设计

质量损失是由于产品的功能波动所造成的,损失大小可由质量函数确定。在无量纲“标准化”多元质量损失函数的基础上,采用信噪比衡量各质量指标的波动,建立一般情形下的基于信噪比的多元质量损失模型,并把它表示成多个相关装配尺寸产品的工序公差函数。利用成本-公差函数和产品质量损失函数,给出基于产品最低制造成本和多个相关装配尺寸产品质量损失的并行公差设计优化模型,实现公差的并行设计,最后通过工程实例验证所提出的方法。     

基于多重相关特征质量损失函数的并行公差设计

基于多变量质量损失函数,推导了多重相关特征产品的质量损失与有关零件工序公差的函数关系,建立了基于制造成本-质量损失的并行公差设计的优化综合模型,其目的是寻求制造成本和质量损失之间的平衡,以实现相关特征产品的设计公差与工序公差并行优化分配,达到提高产品质量和降低成本的目的。圆锥齿轮装配的并行公差设计实例验证了所提方法的有效性。     

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。     

多工位装配过程夹具系统公差和维护综合优化设计

提出一种面向二维多工位装配过程、综合考虑装配夹具系统全寿命周期成本、产品零件孔制造成本和产品质量损失成本的公差和维护综合优化方法。分析多工位装配尺寸偏差传递关系,建立多工位装配过程产品质量损失模型。然后根据4-2-1夹具定位原则,构建考虑夹具磨损过程损失的夹具定位销副偏差统计数字特征模型。继而发展了以夹具系统全寿命周期成本、零件孔制造成本和和产品质量损失成本为装配总成本最小化的定位销公差、零件孔公差与更换周期优化模型。以汽车侧围装配过程为例,分别研究定位销公差、零件孔公差、定位销更换周期、配合间隙、平均磨损率和磨损率方差对装配总成本的影响,并优化设计定位销公差、零件孔公差和定位销更换周期。所提出的综合优化设计方法比采用定位销等公差设计、零件孔等公差设计、定位销与零件孔等公差设计和定周期更换设计的装配总成本分别减少了16.25%、11.31%、39.93%和13.54%。该方法为产品装配夹具系统高质量低成本设计提供了一种新的途径。     

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.     

一种设计和工序公差计算机辅助并行设计方法的研究

提出一种计算机辅助设计公差和工序公差并行设计的数学模型，以成本公差函数作为目标函数，以装配功能要求、加工方法、加工余量、工序制造公差范围作为约束条件，并用蒙特卡洛法模拟尺寸装配、模拟退火算法用于优化求解，实现了设计公差和工序公差并行设计，缩短了设计周期。     

面向质量目标的再制造复杂机械产品装配分组优化配置方法

为提高再制造机械装配精度和装配质量稳定性,提出一种面向再制造质量目标的复杂机械产品装配分组优化配置方法。分析复杂机械再制造装配生产的特点,建立面向再制造质量目标的复杂机械产品分组优化配置方法总体架构;在质量公差精度分级和极值法尺寸链约束的基础上,结合质量损失-公差函数和装配成本函数,在保证质量和成本最小化的目标下,构建面向再制造质量目标的复杂机械产品装配分组优化约束函数,并给出基于模拟退火遗传算法的模型运算过程,求解出动态规划优化配置方案,规范化标准化装配过程,减少再制造装配过程不确定性,确保再制造产品质量;通过某再制造发动机装配过程实例验证该方法的可行性和有效性,为提高复杂机械产品再制造装配质量提供一种切实可行的解决方案。     

基于广义装配原理的产品生长型设计

通过研究生物生长与产品设计之间的相似性,提出了基于广义装配原理的生长型设计过程,研究了广义装配原理的三个理论构成。首先,在产品生长阶段,为实现生长过程中的自然选择,提出了以复杂度理论为控制因素的设计推理策略;其次,提出了功能公差设计理论,通过加工成本以及基于多因素的模糊质量损失成本体现广义装配成本,在确保产品功能的同时,以较低的装配与制造成本为公差的分配策略;在产品进化阶段,为保证产品良好的装配性能,采用了虚实结合设计技术。将以装配质量因素为核心的产品复杂度、精度以及制造、装配成本等众多设计因素并行集成于生长型设计过程中,实现了以全生命周期装配质量保障为核心的产品生长型设计。     

基于广义装配原理的产品生长型设计

通过研究生物生长与产品设计之间的相似性,提出了基于广义装配原理的生长型设计过程,研究了广义装配原理的三个理论构成.首先,在产品生长阶段,为实现生长过程中的自然选择,提出了以复杂度理论为控制因素的设计推理策略;其次,提出了功能公差设计理论,通过加工成本以及基于多因素的模糊质量损失成本体现广义装配成本,在确保产品功能的同时,以较低的装配与制造成本为公差的分配策略;在产品进化阶段,为保证产品良好的装配性能,采用了虚实结合设计技术.将以装配质量因素为核心的产品复杂度、精度以及制造、装配成本等众多设计因素并行集成于生长型设计过程中,实现了以全生命周期装配质量保障为核心的产品生长型设计.     

尺寸精度约束下再制造产品零部件选配优化方法研究

合理选配再利用件、再制造件、新件等不同来源形式的零部件,是保障再制造产品质量与成本的关键环节。针对待选配零部件尺寸公差对再制造产品质量损失、成本的双重影响特征,通过设计零部件尺寸公差的精度分级机制,实现再制造产品各零部件尺寸精度不低于原新品,获取可行选配方案集;进一步以产品尺寸链精度不低于原新品为约束,建立关于零部件尺寸公差的再制造产品尺寸链精度损失函数、再制造产品总成本函数,构建面向再制造产品成本与质量协同优化的多目标选配优化模型,采用协同进化算法获取最终的选配优化方案,实现在全面提升再制造产品及其零部件尺寸精度的同时,降低产品成本。最后以某机床的再制造进给箱零部件优化选配为例,验证了所提出方法能够有效解决零部件来源形式多、尺寸精度与成本差异性大环境下,以不低于新产品尺寸精度为约束的再制造零部件选配优化问题。     

Concurrent process tolerance design based on minimum product manufacturing cost and quality loss

In a concurrent design environment, a robust optimum method is presented to directly determine the process tolerances from multiple correlated critical tolerances in an assembly. With given distributions of multiple critical assembly dimensions, the Taguchi quadric quality loss function is first derived. The quality loss is then expressed as the function of pertinent process tolerances. A nonlinear optimal model is established to minimize the summation of manufacturing costs and product quality loss. An example illustrates the proposed model and the solution method .     

Concurrent tolerancing for design and manufacturing based on the present worth of quality loss

The quality loss function developed by Taguchi provides a monetary measure for the deviation of the product quality characteristic from the target value. Product use causes degradation on its quality characteristic, and since such a deviation can be changing over time, so can the quality loss. However, most studies on concurrent tolerancing theory do not consider the quality loss caused by the degradation. In this paper, the present worth of expected quality loss expressed as the function of the pertinent process tolerances in a concurrent tolerancing environment is derived to capture the quality loss due to product degradation over time as a continuous cash flow function under continuous compounding. A new tolerance optimization model, which is to minimize the summation of manufacturing cost and the present worth of expected quality loss, is established to realize the concurrent tolerance allocation for products with multiple quality characteristics. An example of the bevel gear assembly involving concurrent allocation of design and process tolerances is given, demonstrating that the proposed model is feasible in practice.     

Minimum-Loss Assembly Tolerance Allocation by Considering Product Degradation and Time Value of Money

In the optimisation of tolerance allocation for a mechanical assembly, much work has concentrated on the minimum cost– tolerance allocation without considering the quality of the final assembly. Cheng and Maghsoodloo combined the cost– tolerance function and quality loss function, to determine the optimal tolerances for individual components, so that the total assembly cost (including both tolerance cost and quality loss) might be minimised. The objective of this paper is to propose a model for optimal tolerance allocation by considering both tolerance cost and the present worth of quality loss such that the total assembly cost/loss is minimised. The proposed model takes into account the time value of money for quality loss and product degradation over time, and includes two new parameters: the planning horizon and the product user’s discount rate. From the result of this study, a longer planning horizon results in an increase in both tolerance cost and quality loss; however, a larger value of discount rate yields a decrease in both tolerance cost and quality loss.     

Tolerance design for products with correlated characteristics

This paper presents a design method for controlling dimensional tolerances of components with multiple functional characteristics. The discussions focus on the characteristics derived from common geometric dimensions. In order to approach the robust design, the tolerance design is achieved by minimizing the total expense, which is the sum of the manufacture cost and the quality loss. Since a product may fail because of any imperfect characteristic, the total quality loss includes all the contributions from individual losses. It is recommended that the losses in correlated characteristics be calculated in separate groups. The computation of the total loss involves the evaluation of the variances–covariance matrix of the related characteristics.     

A review of information flow diagrammatic models for product–service systems

Quality of an assembly of any manufactured product is mainly based on the quality of mating components. Due to random variations in sources such as materials, machines, operators, and measurements, mating components manufactured by even the same process may vary in their dimensions. When mating components are assembled linearly, the resulting assembly tolerance will be the sum of the mating components tolerances. All precision assemblies demand for a closer assembly tolerance. A significant amount of research has already been done to minimize assembly variation using selective assembly, when the dimensions of components follow normal distribution. However, in reality, the dimensions of components produced especially in smaller to medium size batches, invariably have some skewness (non-normality), which makes the methods developed and reported in the literature, often not suitable for practice. In this work, batch selective assembly methodology is proposed for components having non-normal distributions to minimize the assembly tolerance variations. The proposed method which employs a genetic algorithm for obtaining the best combination of mating components is able to achieve minimum variations in assembly tolerances and also maximum number of acceptable assemblies. 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 assembly variation.     

A hybrid method of artificial neural networks and simulated annealing in monitoring auto-correlated multi-attribute processes

In mechanical assemblies, individual components are placed together to deliver a certain function. The performance, quality, and cost of the mechanical assembly are significantly affected by its tolerances. Toleranced dimensions inherently generate an uncertain environment in a mechanical assembly. This paper presents a proper method for tolerance analysis of mechanical assemblies with asymmetric tolerances based on an uncertainty model. This mathematical approach is based on fuzzy logic and tolerance accumulation models such as worst-case and root-sum-square methods. A fuzzy-based tolerance representation is developed to model uncertainty of tolerance components in the mechanical assemblies. According to this scheme, toleranced components are described as fuzzy numbers with their membership functions constructed using the statistical distributions of manufactured variables. In this way, the uncertainty of assembly requirements and accumulation of tolerances are represented in the form of fuzzy number. In this paper, a new factor, the fuzzy factor, is introduced that helps converting the membership functions into fuzzy intervals that can be used for modal interval analysis. Equations for estimation of percent contributions of individual tolerances are introduced in terms of uncertainty parameter. These equations yield percent contributions of upper and lower bounds of independent variables (manufactured dimensions) on the upper and lower bounds of dependent variables (assembly dimensions). The proposed method is applied to an example, and its results are discussed.     

Optimal tolerance design of assembly for minimum quality loss and manufacturing cost using metaheuristic algorithms

Tolerance allocation is a design tool for reducing overall cost of manufacturing while meeting target levels for quality. An important consideration in product design is the assignment of design and manufacturing tolerances to individual component dimensions so that the product can be produced economically and functions properly. The allocation of tolerances among the components of a mechanical assembly can significantly affect the resulting manufacturing costs. In this work, the tolerance allocation problem is formulated as a non-linear integer model by considering both the manufacturing cost of each component by alternate processes and the quality loss of assemblies so as to minimise the manufacturing cost. Metaheuristics techniques such as genetic algorithm and particle swarm optimisation are used to solve the model and obtain the global optimal solution for tolerance design. An example for illustrating the optimisation model and the solution procedure is provided. Results are compared with conventional technique and the performances are analysed.