支持变约束的装配顺序随需式规划方法

针对复杂产品装配约束变更,引起装配顺序被迫变化的问题,以产品装配现场零件、工装、资源失效等情况为例,通过对装配顺序非常规规划的特征分析,提出基于灰色理论结合遗传算法的方式解决装配顺序非常规规划问题.建立基于复合基因组的基因7元组编码机制,考虑装配约束关系,提出综合装配并行度、子装配稳定性、装配聚合性、装配重定向性的适应度函数表示方法,通过遗传操作,有效生成由变动环节开始的装配顺序各择集.将遗传算法生成的装配顺序备择集作为灰色决策集,建立灰色关联模型,结合原始装配顺序,建立装配顺序参考序列,进行灰色关联分析,求解理想最优或次优装配顺序,实现复杂产品装配顺序非常规规划.将所提算法应用于某机型组件装配中,验证算法的有效性.     

面向装配序列优化的一种改进基因算法

针对产品装配序列规划问题的特点和要求，提出了基因组编码表示方法，用以描述产品装配的相关信息，将装配序列表示了基因组排列组成的染色体，改进了传统的基本算法，通过交叉和多层次变异来实现基于基因组编码表示的多信息装配序列的并行优化，最后，通过实例说明了该算法的有效性。     

机械产品非线性装配顺序规划研究

提出了用于机械产品非线性装配顺序规划的关系码矩阵模型，通过编码将所有的装配关系信息集成于一个简单矩阵中，用连接模式，即二进制数模板技术来识别装配时零件的几何约束。基于关系码矩阵模型给出了规划可行的装配顺序，检测装配过程中零件的稳定性及识别子装配的计算方法，使用遗传算法搜索并优化装配顺序，用复合表表示遗传算法中个体的装配顺序。最后，通过一个实例验证了该方法的有效性。     

基于模糊粗糙集的并行装配序列规划方法

复杂产品的并行装配受到各种因素的制约,增加了并行装配序列规划的难度.提出了基于模糊粗糙集的并行装配序列规划方法.定义了并行度作为整个装配体的全局并行装配约束参数,给出了零件装配指标表来描述装配体中各零件的装配特征参数、结构特征参数和约束特征参数.根据这些参数,将待安装零件作为知识论域,提出了适切隶属度函数作为评价指标的不可辨识关系,在基于知识论域和不可辨识关系表示的知识库中采用模糊粗糙集模型,生成装配并行序列.机用台虎钳和等离子体增强化学气相沉积装配实例验证结果表明了该方法的有效性.     

基于零件约束的装配规划技术研究

装配规划是虚拟装配中的关键技术。这里将装配序列的分层规划方法和拆卸法求解装配序列的方法相结合，在研究产品装配层次结构的基础上，以子装配体为研究对象，利用零件之间的装配约束信息求解零件的拆卸方向和顺序，进而实现产品的装配顺序和路径规划。     

基于特征语义的装配序列规划预处理方法

针对复杂产品装配序列规划复杂度高、求解效率低下的问题，提出了基于典型零件装配语义规则的装配序列规划预处理方法。构建基于特征的装配语义模型，表达零件的类型与几何特征信息，在此基础上构建典型零件装配特征库；通过基于属性邻接图的匹配方法，进行零件类型识别及子特征分割；基于典型零件的装配规则，建立装配序列规划矩阵的降维方法，提出基于装配序列规划矩阵的装配可行序列生成方法；以主动锥齿轮子装配为例验证了方法的有效性。     

基于子装配体的并行装配序列规划方法研究

针对复杂产品的装配规划过程较为繁琐的难题,提出了一种基于子装配体的并行装配序列规划方法。将子装配体运用到序列生成的过程当中,通过对子装配体的识别,然后将识别后的零件进行并行序列规划,实现了优化装配序列的目的。通过实例验证,结果表明此方法比纯粹的并行化规划产生的序列少,简化了整个装配序列产生时所参与的零件数,简化了复杂产品的规划过程,提高了装配效率。     

基于基础件和连接关系的装配序列自动快速规划研究

对计算机装配序列快速规划进行了研究,为提高装配序列规划的效率,提出建立集成装配模型。该模型把零件基本属性信息、产品层次信息和关系信息作为基础信息,把连接信息作为衍生信息。为避免装配序列误判,提出把基础件作为装配序列的产生载体,来避免壳体类零件、轴类零件在连接关系中的误判,并结合减速器给出了具体的算法,进而说明基于基础件和连接关系的装配序列规划的优点。因此,该模型可支持自动实现复杂产品装配序列的计算机自动规划,可广泛应用于汽车、机器人等多零件产品的装配顺序规划。     

定位关系在装配序列规划中的应用研究

为提高产品仿真装配效率和满足装配工艺要求,提出一种基于定位关系分析的分类装配序列规划方法.首先对零件的装配特征属性进行预定义和分类,然后根据装配零件的联接关系,在可行拆装方向上建立所有邻接零件的定位关系链有向图;按照定位链顺序依次对零件进行干涉检测并更新其定位关系,最终获得可行装配序列.实例表明,该方法简化了模型的装配关系并有效缩小其装配序列解空间,在一定程度上提高了装配规划效率,并通过虚拟拆装仿真过程验证其生成序列的正确性和可行性.     

基于虚拟现实和仿生算法的装配序列优化

针对自动装配规划和交互式规划都存在不足,将虚拟现实和仿生算法结合起来,提出一种生成优化装配序列的新方法.建立基于几何约束的虚拟装配环境,在该环境中根据经验和知识进行交互式拆卸,定义优先约束表来表达零件间的优先约束关系.应用蚁群算法规划出初始优化的装配顺序,再在虚拟环境下进行仿真、评价和优化,考虑装配位置可达性和工具操作等因素,识别新的优先约束和评价准则,重新规划出更优的装配顺序,不断反复和完善,直到得到满意的最佳装配顺序为止.通过实例验证该方法有效性.     

求解分布式混合流水线调度问题的改进双层嵌套式遗传算法

针对分布式混合流水线生产的生产调度问题,模拟实际排产中的排产到线和排产到时的排产策略,提出了基于改进双层嵌套式遗传算法的两层优化模型。外层依据流水线分配平衡和准时交货等基本原则总体上解决生产订单在流水线之间的分配问题,内层以最小生产时间为主要目的求解流水线的生产订单生产次序问题。考虑到双层嵌套式遗传算法的时间复杂性,基于模糊逻辑理论设计了一种模糊控制器来动态调整遗传算子,并采用主动检测停止方法,提高算法效率。使用某空调工厂的实际生产数据验证了算法的可行性、计算结果的准确性及排产策略的有效性,为高级计划与排程(Advanced Planning and Scheduling,APS)中大规模复杂供应链调度问题提供了可借鉴的方法。     

基于实例的装配顺序规划技术研究

研究装配实例表示与重用技术，提出一种基于实例的装配顺序规划方法。通过对装配知识的组织来构造装配实例模型，采用基于相似度的实例检索算法，通过实例的检索获得符合设计要求的最佳匹配实例。以某机型机翼为例进行验证。     

基于SPEA2+的产品族模块单元多目标规划方法

在分析零件功能和物理特性的基础上,应用模糊数学理论给出产品族模块单元规划准则的量化计算方法,建立产品族模块单元多目标规划优化模型。针对传统的目标加权法在模型求解中的不足,采用改进的强度Pareto进化算法(SPEA2+)对模块单元多目标规划问题进行优化求解,从而得到一系列基于Pareto解集的产品模块规划方案,并利用模糊集合理论的Pareto综合选优方法得到了产品模块多目标规划的最优方案。结合项目实施以缝纫机为应用实例,验证提出方法的有效性和适应性。     

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.     

Unification of the a priori inconsistencies checking among assembly constraints in assembly sequence planning

Sequence planning generation is an important problem in assembly line design. A good assembly sequence can help to reduce the cost and time of the manufacturing process. This paper focuses on assembly sequence planning (ASP) known as a hard combinatorial optimization problem. Although the ASP problem has been tackled via even more sophisticated optimization techniques, these techniques are often inefficient for proposing feasible assembly sequences that satisfy the assembly planners’ preferences. This paper presents an approach that makes easier to check the validity of operations in assembly process. It is based on a model of the assembly planners’ preferences by means of strategic constraints. It helps to check a priori the consistency of the assembly constraints (strategic and operative constraints) given by the assembly system designers before and while running an assembly plan generation algorithm. This approach reduces the solution space significantly. A case study is presented to demonstrate the relevance of the proposed approach.     

洗衣机装配序列遗传优化建模及算法研究

为了研究装配序列遗传优化问题,以某洗衣机装配序列规划为例,讨论了面向装配序列遗传优化的建模方法。结合装配生产线布局、工位装配能力和工件连接关系的实际,给出了可装配性性能指标相关权重的一般性确定原则,建立了面向遗传优化的装配模型,并设计了遗传优化的编码方式和进化算子。为保证个体的有效性,提出了工位约束检验和以连接关系为依据的工件约束检验;为保持种群多样性、避免遗传算法早熟,提出了采用局部搜索策略进行扩展操作的方法。对洗衣机装配序列优化的结果验证了所建模型及所提算法的有效性。     

基于正态模糊时间窗约束的飞机装配物料配送路径规划

针对飞机装配过程中装配工位物料需求时间模糊化现象,提出基于正态模糊时间窗约束的工位物料需求时间参数表征方法,用正态模糊数的隶属度表示工位的满意度。建立了基于正态模糊时间窗约束的飞机装配物料配送路径规划数学模型,并采用遗传算法进行了求解。遗传算法的选择算子利用轮盘赌和最优保留策略,交叉算子采取小生境选择机制的双选择交叉策略,变异算子确保每代个体得到进化。MATLAB仿真结果表明,该规划方法拥有较好的经济效益。     

An effective integration approach toward assembly sequence planning and evaluation

An integration strategy for assembly sequence planning and sequence scheme evaluation is proposed. This strategy can be used to plan a reasonable assembly sequence, to optimize a sequence scheme, and to predict whether a collision will occur between the assembly tool and assembled components by considering factors like target components and assembly resources. A hybrid method is presented for assembly sequence modeling that combines human-computer interactive operations to manually build a hierarchical assembly sequence main model and a hybrid graph method to automatically generate sub-assembly sequence schemes of the main model. An optimization algorithm based on time-cost is introduced to handle a best candidate components selection. This relieves the problem of limited capability found when handling large size assembly models with traditional methods. The essential issues involved in system implementation are discussed as well; these include a representation method for the assembly consequence model, an optimization model of assembly sequence planning, and an object-oriented system architecture model employed with multi-agent technology for visually evaluating the assembling process. This system, KM computer-aided assembly process planning, KMCAAPP, has been developed on the basis of our previous work, KMCAD3; KMCAAPP uses the presented approach. KMCAAPP can be integrated with CAD model from KMCAD3D. A case study shows that the presented approach can use large CAD assembly models and delivers a feasible and effective way to integrate the assembly sequence planning process with scheme evaluation by visually evaluating the assembling process. This allows the identification of design errors in a timely manner and mitigates economic loss.     

基于混合优化算法的装配线平衡问题

为求解给定装配线生产节拍、最大化装配效率的装配线平衡问题,根据装配线的特点和平衡优化需求,分析了装配作业顺序、站位数量等因素对装配线站位内作业分配的影响,综合考虑装配线平衡率和平滑系数,建立了装配线平衡问题数学模型,并设计了 一种结合遗传算法(Genetic Algorithm,GA)、蚁群算法(Ant Colony ...     

Sequencing the mixed-model assembly line to minimize the total utility and idle costs with variable launching interval

A mixed-model assembly line (MMAL) is a type of a production line where a variety of products is assembled on it. A mixed-model assembly line problem involves not only solving the traditional problems of the assembly line design (i.e., determining the cycle time, the number and sequence of stations, and the balancing problem) but also determining the sequence of products in assembly line. The product sequencing has a high effect on the mixed-model assembly line efficiency. In this paper, we consider sequencing problem with a variable launching interval between products on the assembly line. A mathematical model is presented, which is capable to solve the small-sized ones of these problems. The considered problem involves two optimization problems (the sequencing problem and launching interval problem). Since this problem is strongly NP-hard, a hybrid metaheuristic algorithm based on the simulated annealing approach and a heuristic approach is developed. The heuristic approach (launching interval between products algorithm) is presented to solve the launching interval problem for each sequence. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. Variable launching interval consideration in MMAL problem causes the higher complexity of this problem. However, this assumption improves the considered goals for this problem. Not only a power algorithm for MMAL is presented in this paper but also the effect of this assumption is discussed. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm.