计算机辅助几何可行装配顺序推理及基优化分析

针对装配优先关系分析,几何可行装配顺序推理以及最优几何可行装配顺序选择3个层次的问题,提出了一种系统化的分析方法-几何约束分析方法,该方法从装配体中各个零件之间的约束方向分析出发,可以自动求解出正确和完备的装配优先关系;在装配优先关系的约束政下,可以计算出所有的几何可行装配顺序规划;并从操作空间大、装配方便角度出发,设计出几何可行装配顺序优选算法;可以从大量的几何可行装配顺序中求解出几何性能最佳的装配顺序规划,应用具体实例分析演示了几何约束方法在计算机中的实现过程,并证实了该方法的实用性有效性。     

几何可行装配顺序推理方法及实现技术

在系统分析相关文献的基础上，重点针对装配优先关系推理和几何可行装配顺序计算，提出了一种系统化的分析方法－“几何约束分析”方法。该方法从装配体中各个零件之间的约束方向计算出发，可以自动求解出装配结构本身所固有的、隐含的装配优先关系，而且能够保证推理结果的正确性和完备性。在此基础上，设计出几何可行装配顺序的反向推理算法，并结合实例分析了基于几何约束分析方法的装配优先关系推理，及几何可行装配顺序推理的计     

计算机辅助三维装配顺序规划

针对三维空间装配顺序推理问题,应用方向包围盒和分离轴定理,对装配几何约束分析方法进行了扩展完善,提出三维几何约束分析方法,并开发出相应的计算机辅助分析系统.通过实例表明,该方法可以在三维装配环境中自动推理出正确完备的装配优先关系和几何可行的装配顺序.     

装配顺序规划中的几何约束分析方法

针对目前计算机辅助装配顺序规划中存在的问题，提出了一种几何约束分析方法。该方法根据装配结构设计ＣＡＤ信息，利用ＧＣＡ最小约束装配状态算法，能够计算出正确、完备的装配优先关系，为进一步提高装配顺序规划的自动化水平和分析效率提供了一种有效途径。     

集成环境下基于割集的装配顺序生成算法研究

在分析总结以往学者对装配顺序规划研究的基础上，综合拆卸法和优先约束法的特点，探讨了一种新的装配顺序分析方法，该方法利用产品的装配域信息，根据图论的割集法对产品进行拆分，建立几何优先约束关系，然后通过人机交互的方式建立工艺优先约束关系，最终得到可行的产品装配顺序。实现了集成环境下基于割集的装配顺序规划。给出了割集的生成算法框图以及装配顺序规划的算法框图，最后通过实例验证。     

集成环境下基于CAD产品装配顺序规划

在分析总结以往学者对装配顺序规划的研究基础上，综合拆卸法和优先约束法的特点，探讨了一种新的装配顺序分析方法，该方法利用产品的装配域信息，根据图论的割集法对产品进行拆分，建立几何优先约束关系，然后通过人机交互的方式建立工艺优先约束关系，最终得到可行的产品装配顺序。实现了集成环境下基于CAD产品装配顺序规划。本文给出了割集的生成算法框图以及装配顺序规划的算法框图，最后通过实例验证。     

产品装配顺序规划方法的研究

计算机辅助装配顺序规划是有关产品装配研究的重要内容。在提高装配顺序规划质量的条件下，综合拆分法与优先约束法的优点，提出了一种装配顺序规划的新方法。在子装配、组件预识别的基础上，采用割集法将产品进行拆分。基于装配城信息建立零件几何优先关系，基于产品共性特征及个性特征建立工艺优先关系，最终生成合理可行的装配顺序，并对实例进行分析。     

产品装配顺序的层次化推理方法研究

提出一种装配优先关系分类模型，将装配顺序规划过程中的各种装配优先关系分为几种优先关系，确定性工艺优先关系和模糊性工艺优先关系3类。并在此基础上，提出层次化装配顺序推理方法，分别从装配顺序的几何可行性、工艺可行性和工艺优良性3个层次，对装配顺序进行递进推理，最终得到性能优良的装配顺序。开发的产品装配分析软件原型系统－－PAAS可以对复杂产品的装配顺序规划进行有效的分析和优化。     

装配规划中基于割集的装配顺序生成方法

针对装配规划提出一种新的装配零件关系的描述方法，该方法应用改进的关联图－优先约束关联图，描述装配零件间的连接关系、优先关系及约束关系。在生成产品装配顺序时，充分地把装配优先关系与割集法副合到装配顺序搜索中，有效地生成产品所有满足装配条件的装配顺序，为装配规划提供参考的装配工艺路径。     

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.     

Computer aided geometric feasible assembly sequence planning and optimizing

Assembly sequence planning (ASP) is the foundation of the assembly process planning and design for assembly (DFA). In ASP, geometric feasibility is the prerequisite in the valid assembly sequences searching. The assembly precedence relations’ (APRs) deriving and fulfilling are the essential tasks in the geometric feasible assembly sequence planning. In this paper, a systematical approach called geometric constraint analysis (GCA) is proposed and the corresponding software system is developed and integrated with CAD system. Using this system, only with a few mouse clicks on CAD draft, assembly precedence relations (APRs) can be derived correctly and completely. Then, all the geometric feasible assembly sequences can be inferred out automatically. Moreover, an optimal algorithm is designed and realized in the GCA method, by which, the most optimal assembly sequence in terms of the operation convenience can be found out from the immense geometric feasible sequences. An erratum to this article can be found at     

考虑工具操作空间的装配序列生成方法

介绍了基于有向图的装配模型,该模型记录了零件间的优先关系,并对普通零件、紧固件进行不同的描述。在UG环境中对装配工具进行建模,在完整装配体中对工具的安装动作进行仿真和干涉检查,记录下工具同周围零件的潜在干涉信息,利用该信息快速检查装配序列是否满足工具的操作空间要求。然后应用改进的蚁群算法,在优先关系的指导下求解装配序列。针对妨碍工具操作等不可行的序列,提出信息素的惩罚蒸发策略,帮助蚁群避开不可行解。最后通过实例验证了算法的实用性。     

An integrated method for block assembly sequence planning in shipbuilding

Many efforts in the past have been made to find more efficient methods for assembly sequence planning in machining area. While few researches reported in other area such as block assembly in shipbuilding industry. In general, a ship hull is built with hundreds of different blocks, most of which are complicated in structure and different from each other in assembly planning. Additionally, there may be a large number of feasible assembly sequences for any block. A better sequence can help to reduce the cost and time of the manufacture. Therefore, it is necessary to seek out the optimal sequence from all feasible ones. Currently, the assembly sequences are determined manually by some process engineers. Consequently, it is becoming a time-consuming task and cannot make the assembly plan consistent to improve productivity. In this paper, a methodology-integrated case-based reasoning and constraints-based reasoning is proposed to improve the assembly planning for complicated products. Besides, genetic algorithm is designed to evaluate and select the optimal sequence automatically from the reference ones. The validity of the method is tested using real blocks, and the results show that it can facilitate the optimal assembly sequences generation.     

Optimization of operation sequencing in CAPP using simulated annealing technique (SAT)

Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environment. A problem in traditional CAPP system is that the multiple planning tasks are treated in a linear approach. This leads to an over constrained overall solution space and the final solution is normally far from optimal or even non-feasible. The operation-sequencing problem in process planning is considered to produce a part with the objective of minimizing the sum of machine, setup and tool change costs. In general, the problem has combinatorial characteristics and complex precedence relations, which makes the problem more difficult to solve. In this paper, the feasible sequences of operations are generated based on the precedence cost matrix and reward–penalty matrix using simulated annealing technique (SAT), a meta-heuristic. A number of benchmark case studies are carried out to demonstrate the feasibility and robustness of the proposed algorithm. This algorithm performs well on all the test problems, exceeding or matching the solution quality of the results reported in the literature for most problems. The main contribution of this work focuses on reducing the optimal cost with a lesser computational time along with generation of more alternate optimal feasible sequences. The proposed SAT integrates robustness, convergence and trapping out of local minima.     

An approach to multi-criteria assembly sequence planning using genetic algorithms

This paper focuses on multi-criteria assembly sequence planning (ASP) known as a large-scale, time-consuming combinatorial problem. Although the ASP problem has been tackled via a variety of optimization techniques, these techniques are often inefficient when applied to larger-scale problems. Genetic algorithm (GA) is the most widely known type of evolutionary computation method, incorporating biological concepts into analytical studies of systems. In this research, an approach is proposed to optimize multi-criteria ASP based on GA. A precedence matrix is proposed to determine feasible assembly sequences that satisfy precedence constraints. A numerical example is presented to demonstrate the performance of the proposed algorithm. The results of comparison in the provided experiment show that the developed algorithm is an efficient approach to solve the ASP problem and can be suitably applied to any kind of ASP with large numbers of components and multi-objective functions.     

INTEGRATED APPROACH TO GENERATION OF PRECEDENCE RELATIONS AND PRECEDENCE GRAPHS FOR ASSEMBLY SEQUENCE PLANNING

An integrated approach to generation of precedence relations and precedence graphs for assembly sequence planning is presented, which contains more assembly flexibility. The approach involves two stages. Based on the assembly model, the components in the assembly can be divided into partially constrained components and completely constrained components in the first stage, and then geometric precedence relation for every component is generated automatically. According to the result of the first stage, the second stage determines and constructs all precedence graphs. The algorithms of these two stages proposed are verified by two assembly examples.     

基于优先约束关系的装配序列规划研究

利用联结图方法建立设备的装配关系模型,生成联结矩阵,并利用子装配体的概念对模型进行简化.利用联结图模型分析零件间的优先约束关系生成优先关系矩阵,利用优先约束矩阵生成设备的可行装配序列,为设备装配序列选优提供基础.