基于粒子群—遗传混合算法的装配操作优化

为通过装配工艺优化提高车身装配尺寸质量,针对车身众多几何可行装配顺序,应用多属性有向图描述零件间的优先关系和装配控制特征数量,来去除非工程可行装配顺序。以装配尺寸质量为目标函数,提出粒子群—遗传混合算法优化零件间装配操作,通过线性装配偏差分析模型进行装配偏差累积运算,获得了最优装配顺序。通过车身侧围装配体阐述了装配控制特征的优化过程,结果表明,不同的装配顺序将影响装配控制特征的选择,从而影响最终的产品装配偏差。     

粒子群算法在抽油机装配序列规划中的应用研究

在石油机械的产品的装配过程中,此类机械产品的装配顺序优化具有多目标和非线性的特点,针对传统算法在该问题求解上的不足,以及根据此类产品实际的装配规划问题的特点和要求提出一种新的通过粒子群优化算法进行抽油机的装配顺序优化。该方法重新定义了微粒的位置和速度以及相关的各种操作,综合考虑零件装配几何性、装配稳定性以及装配方向改变次数等信息对装配序列的影响,建立了适应度函数,并对装配序列进行了优化。以抽油机产品的装配为例,验证了技术的有效性。     

基于质量特征产品装配顺序规划的逆向推理算法探究

在Petri网柔性装配系统装配顺序规划中引入装配质量要素,并以装配零件的装配自由度,装配作业后稳定性,装配零件配合精度对装配质量的影响作为基本因子,提出装配质量置信度概念,解决柔性装配系统装配规划中装配质量及其定量化问题。根据装配形成的产品在Petri网装配状态图中表示为一个最终库所的特点,应用改进B树模型,提出仅以变迁信息的产品装配顺序规划Petri网逆向推理算法,简化装配顺序规划推理过程,对于多个变迁均可生成最终成品的情况,亦给出装配顺序规划的解决方案,并以摩托车发动机的装配为例,证明该算法是可行的。     

基于Kriging模型的复杂产品管线敷设顺序粒子群优化

复杂产品的管线布局问题十分复杂,除管路路径规划算法外,敷设顺序对管线整体敷设有着十分重要的影响.以往的研究大多将重点集中在管线路径规划方面,而对敷设顺序的研究还比较少.以航空发动机为例,提出一种基于Kriging模型的管线敷设顺序的规划方法.针对敷设顺序规划这一离散优化问题,通过论域连续化处理,建立粒子群算法优化相关函数参数的Kriging近似模型.在Kriging模型的基础上,应用离散粒子群算法搜索最优顺序,避免在优化过程中反复应用管线路径规划算法进行计算,显著提高规划效率.对离散粒子群算法的改进进一步提升算法的搜索性能.所提规划方法具有很好的通用性,仿真试验验证了方法的有效性与高效性.     

基于离散粒子群算法的装配序列规划

为解决复杂产品的装配序列规划问题,提出了一种基于离散粒子群算法的装配序列规划方法。针对装配序列规划问题的特点,对传统应用于连续空间的粒子群算法中的粒子位置、速度及其更新规则重新进行了定义,综合考虑产品装配过程中的重定向性、稳定性和聚合性,建立了多目标适应度函数。以汽车座舱模块总成的装配序列规划验证了算法的合理性和有效性。     

基于关联函数的复杂产品装配序列规划方法

针对复杂产品装配序列规划时出现组合爆炸的问题,将粒子群算法应用于求解复杂产品装配序列规划.基于可拓集合理论中关联函数的概念,提出了一种装配关联函数,由此结合各种联接关系的装配难易度构建装配联接函数.以发光二极管分拣机电极模块为例,说明了装配联接函数的计算方法.将装配联接函数、产品装配可行性和装配稳定性作为评价标准,构造装配序列规划的多目标模型.应用该方法,采用整数编码方式,对发光二极管分拣机进行了装配序列规划,并将粒子群算法与遗传算法进行对比分析,结果显示了粒子群算法的优越性.     

基于改进粒子群算法的锂电池模块装配序列规划

根据电动汽车中用到的锂电池模块装配特点,提出了模块内部零件的编码规则,并综合几何可行性、装配方向改变次数、装配连续性、装配工具改变次数和装配优先性五个指标设计了目标函数,结合改进的粒子群算法迭代更新得出最优装配序列组.通过电池模块实例对该算法进行了验证,结果表明本文提出的改进粒子群算法可以有效地求解该锂电池模块的装配序列规划问题.     

多工位装配序列粒子群优化算法

针对传统单工位装配序列求解上的不足,将粒子群算法应用于多工位多目标装配序列优化的求解,提出一种面向复杂多工位产品的装配序列优化方法。采用优先序列图(Assembly precedence graph,APG)来描述零件间的优先约束关系,构建优先关系矩阵、装配干涉矩阵、工位能力表和装配信息表,描述装配部件干涉及工位之间的关系;给出粒子群算法编码体系和装配关系算法模型表达方法;综合考虑装配操作成本、装配工具更换成本和装配夹装变更成本和运输成本的影响,提出有工程意义的适应度函数的表达式;根据APG生成随机的可行初始装配序列,并利用粒子群算法(Particle swarm algorithm,PSO)对装配序列和装配工位进行优化。以飞机起落架装配序列规划实例验证多工位粒子群装配序列优化算法有效性。     

基于改进粒子群算法的多工位装配序列规划

针对现有单工位装配序列规划结果难以满足工位需求的问题,提出一种基于改进粒子群算法的多工位装配序列规划方法。建立多工位装配模型来描述零部件的几何信息及其与工位的关系;用装配序列可行性、装配方向一致性、装配聚合性及工位间平衡性4个评价指标构建适应度函数。为解决一般粒子群算法易陷入局部最优解的问题,对惯性权重进行了改进,提出粒子相似度和相似度阈值的概念,并通过相似度阈值控制粒子的变异,提高了算法的全局搜索能力。以某型发动机为装配实例,验证了改进粒子群算法应用于多工位装配序列规划的可行性;同时将该算法和遗传算法、一般粒子群算法进行比较,证明了该算法的优越性。     

柔性薄板装配不等间距定形焊点布置优化

针对点焊中的定形焊点布置方案影响柔性薄板装配偏差,以及等间距焊点布置不适合所有薄板焊接情况的问题,提出一种基于支持向量回归机与粒子群优化算法的不等间距定形焊点布置优化方法。对薄板装配过程进行分析,建立了反映装配偏差与偏差源关系的装配偏差模型。以两种焊点的间距为设计参数,通过优化拉丁超立方实验设计在焊点布置设计空间获取样本方案,利用偏差模型获得样本响应。构建支持向量回归机—粒子群算法代理模型,预测得到使装配偏差最小的焊点布置最优方案。柔性薄板装配实例表明,在小样本学习情况下,与遗传算法—反向传播神经网络和响应面两种代理模型相比,该方法在模型预测准确度方面具有有效性和优越性,同时通过车身薄板实例表明了该方法的实用性。     

装配工艺规划中装配序列生成与评价方法研究

装配序列生成是计算机辅助装配工艺规划（ＣＡＡＰＰ，ＣｏｍｐｕｔｅｒＡｉｄｅｄＡｓｓｅｍｂｌｙＰｒｏｃｅｓｓＰｌａａｎｉｎｇ）的关键环节。本文首先给出了基于特征产品装配模型，然后提出基于割集理论的装配序列自动生成算法。该算法根据评价准则采用ＡＯ搜索算法寻找最优的装配序列，既节省了装配成本和时间，又减少了算法的时间和空间复杂性。     

Design automation and optimization of assembly sequences for complex mechanical systems

Assembly sequence design for a mechanical system can have significant impact on manufacturing cost and product quality. Traditionally, such a design process is largely based on experience and best practices, often ineffective and non-optimal as the system becomes complex. This paper proposes a new, systematic method for automatic assembly sequence design and optimization. Key elements include assembly modeling, sequence planning, locating scheme optimization, dimensional quality evaluation, and optimization. First, a directed graph and an assembly matrix are employed to describe the assembly relation of a system. Then, the feasible assembly sequences are generated through layered subassembly detection of adjacency matrices, filtered by engineering constraints. To evaluate quickly the assembly quality and compare the influences of different locating point schemes, a linear 3D variation propagation analysis model with deterministic locating principle is introduced. The optimal locating scheme is then selected using a genetic algorithm with the least variation propagation. Finally, the assembly dimensional quality for different sequences is evaluated and the optimal assembly sequences are achieved through genetic algorithms. A case of automotive body side assembly is presented to illustrate the whole methodology.     

A systematic method of adaptive joint design considering different assembly sequence in sheet metal product

In sheet metal assembly, not only the component variations and tool errors, but also the component structure (joint type) and assembly process (assembly sequence) affect the final dimensional quality. In this paper, a systematic method for adaptive joint design considering different assembly sequence is proposed to meet the in-process dimensional adjustability of KCs (key characteristics). First, the adaptive characteristic of the sheet metal joint is depicted. Then, the mathematical model in order for concurrently optimizing both joint type and different assembly sequence is presented. How to evaluate the combination of joint type and assembly sequence is carried out according to two conditions: (1) for single KC, and (2) for multiple KCs. The KC confliction is considered to ensure the important KCs. Genetic algorithm is used to resolve the optimization of joint design. An example is chosen to demonstrate our method finally, and various joint designs are acquired according to different assembly sequences by this means. The proposed methods make it possible for us to improve the dimensional quality of product in the design stage.     

基于Pro/E的三维辅助装配工艺规划系统研究

分析了现有计算机辅助装配工艺规划系统的不足,提出了三维辅助装配工艺规划系统的体系结构,并对其中装配模型信息表达、装配序列规划、路径规划、装配过程动画等关键技术进行了研究。基于Pro/E平台,建立修正的装配层次模型,并交互生成装配序列;通过确定装配路径上的关键点及关键点之间的位姿,进行装配路径规划和装配干涉检测。此提出的系统可以通过三维工艺简图和装配过程动画,形象、直观地指导现场装配。     

基于相对熵排序的装配序列质量模糊评价方法

在界定装配序列质量内涵的基础上,利用解释结构模型建立了可全面反映装配序列总体质量的评价指标体系,并利用各影响因素间的层次结构关系来定量计算各指标属性值。然后采用基于Vague集的模糊评判获得指标权重,同时引入基于相对熵的多属性排序方法对各装配序列质量进行综合评价,从而选出最优装配序列。最后用实例验证该方法的正确性与有效性。     

Assembly sequences merging based on assembly unit partitioning

Assembly sequence planning is a typical of combinatorial optimization problem which is difficult to be tackled when the number of parts of assembly becomes large. To reduce the searching space of assembly sequence planning of complex products, assembly sequences merging based on assembly unit partitioning is suggested. Assembly unit partitioning is presented to decompose the complex products into a group of assembly units containing a reduced number of parts or components, and the assembly design constraints and the assembly process constraints are comprehensively taken into account. The global optimal assembly sequences can be acquired through three steps. Firstly, the assembly units and decision graph of assembly unit are generated utilizing fuzzy analytical hierarchy process approach. Secondly, the optimal or near-optimal subsequences of assembly units can be obtained with current efficient methods of assembly sequence planning. Thirdly, under the assembly interference of assembly relations (geometrical constraints) of the whole products and the assembly precedence concluded by subsequences of assembly units, the assembly sequence merging is implemented to generate the global assembly sequences, and the optimal sequence is obtained through assembly sequences evaluation. The assembly constraints considered at the two previous steps is represented by the evaluation function. The effectiveness of the method is verified by an illustrative example and the results show that the searching space of assembly sequence merging of complex products is reduced remarkably and the optimal assembly sequence of the whole produces is obtained.     

A green assembly sequence planning model with a closed-loop assembly and disassembly sequence planning using a particle swarm optimization method

In a green product life cycle, it is necessary to determine how to disassemble a product before the product is planned to be assembled. In this research, a green assembly sequence planning model is developed. A closed-loop assembly sequence planning model is presented by integrating assembly and disassembly sequence planning models. For an assembled product, an assembly sequence planning model is required for assembling the product at the start, while a disassembly sequence planning model is performed for disassembling the product at the end. In typical assembly and disassembly sequence planning approaches, the two sequences are independently planned and evaluated. In this paper, a closed-loop model is presented to concurrently generate and evaluate the assembly and disassembly sequences. First, a graph-based model is presented for representing the feasible assembly sequences and disassembly sequences. Next, a particle swarm optimization (PSO) method with a new encoding scheme is presented. In the PSO method, the assembly and disassembly sequences can be simultaneously represented and evaluated with an objective of minimizing the total of assembly costs and disassembly costs. The test results show that the presented method is feasible and efficient for solving the integrated assembly and disassembly sequence planning problem. An example product is illustrated and discussed.     

基于模拟退火算法的装配序列生成与优化

分析了一个优良装配序列应满足的装配约束条件,从几何可行和工艺优良两方面对装配序列进行评价;介绍了影响装配序列工艺性能的四大因素及其量化方法。在此基础上,建立了基于模拟退火算法的装配序列优化规划模型,并对算法的性能和速度进行了分析、处理。最后通过齿轮泵的应用实例说明了该优化算法的有效性。     

Imperialist competitive algorithm for assembly sequence planning

Automated generation of all feasible assembly sequences for a given product is highly desirable in manufacturing industry. Many research studies in the past decades described efforts to find more efficient algorithms for assembly sequence planning. Imperialist competitive algorithm for assembly sequence planning is presented in this paper. Population individuals called countries are in two types: colonies and imperialists that all together form some empires. Each assembly sequence is encoded into the country. The proposed algorithm is tested and compared with genetic algorithm and particle swarm optimization. Results show that imperialist competitive algorithm can improve the quality in solution searching and upgrade the opportunity to find optimal or near-optimal solution for assembly sequence planning.     

虚拟现实环境下交互式船舶装配序列规划研究

针对传统装配序列规划方法解空间大、模型简单的问题,提出了应用虚拟现实技术解决船舶装配序列规划问题的方法。该方法分为虚拟拆卸和方案评价两个阶段,分析了虚拟装配平台上进行虚拟拆卸的基本流程和关键技术——虚拟环境下的实体模型表达和基于装配约束的运动导航。建立了船舶装配序列评价模型,确定了零件重量、装配时间、装配稳定性和装配过程难度等面向手工装配的评价指标。最后,用某船舶机舱区域的规划实例进行了验证,结果表明该方法生成的装配序列对实际船舶装配生产具有指导作用。