A multi-plant assembly sequence planning model with integrated assembly sequence planning and plant assignment using GA

In a multi-plant collaborative manufacturing system, the manufacturing operations and assembly operations for producing a product can be distributed at different plants at various locations. The components are assembled with assembly operations performed in a multi-plant assembly sequence. In this research, a multi-plant assembly sequence planning model is presented by integrating (1) assembly sequence planning, and (2) plant assignment. In assembly sequence planning, the components and assembly operations are sequenced according to the assembly constraints and assembly cost objectives. In plant assignment, the components and assembly operations are assigned to the suitable plants to achieve multi-plant cost objectives. The feasible assembly sequences are generated using the developed graph-based models of assembly precedence graphs and matrices. A genetic algorithm (GA) method is presented to evaluate the multi-plant assembly sequences with an objective of minimizing the total of assembly operational costs and multi-plant costs. The main contribution lies in the new model for multi-plant assembly sequence planning and the new GA encoding scheme for simultaneous assembly sequence planning and plant assignment. Example products are tested and discussed. The test results show that the presented method is feasible and efficient for solving the multi-plant assembly sequence planning problem.     

逐步求解的装配顺序规划方法

产品装配是一个为已装配体尚未完成装配的配合寻找可装配件的过程。针对该特点,提出逐步评判的装配顺序求解方法。建立装配规划约束的编码矩阵,采用混合编码的方式表示几何约束和语义约束。以混合编码矩阵为基础,通过装配约束推理和判断获得产品装配过程每一步的可行装配方案,作为装配顺序评价集。以装配方向改变、装配工具改变、装配体的稳定性和装配准确度要求作为规划因素集,运用多因素模糊综合评判方法为已装配体获取最优的装配方案,逐步缩小求解空间,直到规划完成所有零件的装配顺序。将该方法应用于某机型舱门骨架装配规划中,结果表明该方法合理、有效,能够满足工程实际需求。     

An efficient method of automatic assembly sequence planning for aerospace industry based on genetic algorithm

A method of generating assembly sequences is developed in this paper, which can be used in the satellites assembly. The method must take into account the assumptions specific for assembly processes of large number of connections, multi-stage and parallel assembly. Setting priority relations between connections is involved. The assembly sequence is presented as a directed acyclic graph, whose vertices are mutually uniquely assigned to the connections. The minimization of the number of violated priority precedence of performing connections has been proposed as a criterion of optimization. In this article, a new way of coding the acyclic serial-parallel sequence was designed. The proposed method allows analyzing the sequence using the graph theory. Original, two-part crossover and mutation operators for assembling sequence were proposed. Examples of calculations are performed on an actual structure of a local structure of a satellite.     

Subassembly identification for assembly sequence planning

Assembly sequence planning is a typical of NP-complete problem which will spend a large amount of computation time or disk memory once the assembly becomes complex. The complex product or assembly is composed of many parts and the number of assembly relationships between them is numerous. To decrease the difficulty of assembly sequence planning of complex products, the subassembly identification methods are focused on. It aims to decompose a complex assembly into a limitative number of subassemblies. Each subassembly contains a relatively smaller number of parts and the assembly sequence planning tasks of them can be handled efficiently. The subassembly identification methods for assembly sequence planning are summarized with respect to assembly constraints. The assembly constraints including the topological, geometrical, and process constraints are considered and merged into the assembly models for subassembly identification. The assembly models are generally represented as directed or undirected assembly diagrams including these considered constraints. It is generally taken as the input information to generate appropriate subassemblies complying with the requirements. The graph theories and graph search algorithms, integer programming methods and the emerging techniques, such as the knowledge-based methods, the intelligent algorithms and the virtual technology, etc. are advocated to resolve the subassembly identification problem with respect to the assembly models. The hierarchical assembly tree is widely used to represent the results of subassembly identification. These useful methods are not only used to subassembly identification for assembly sequence planning, but also successfully referred to by product disassembly.     

面向装配序列规划的装配建模方法研究

为实现自动化的装配序列规划,提出了一种应用面向对象和Petri网技术定义的产品装配模型.该模型由静态模型和动态模型构成.基于模型定义,提出了局部装配可行性的判定依据,并据此建立了一种基于静态模型的动态模型构造算法.该算法通过逐层分析可能状态的变迁,最终获得装配体所有几何可行的装配序列.通过实例验证了该建模方法的有效性.     

装配序列规划问题求解的一种混合算法

基于蚂蚁算法和的遗传算法特点,给出了一种解决装配序列规划问题的遗传和蚂蚁混合算法.混合算法中利用蚂蚁的每一次周游,快速生成问题的一组可行解,用遗传算法对得到的可行解进行快速优化,并根据优化解的质量,生成路径上的信息素分布,以加速蚂蚁最优路径上信息素的积累,从而引导蚂蚁更快地搜索到问题的最优解.实验结果表明,混合算法在装配序列规划问题求解上具有更好的性能.     

带时间窗约束的船体分段空间调度问题

研究了将空间资源作为关键资源的生产调度问题--空间调度问题,分析了空间调度问题和三维装箱问题的异同,以具有时间窗约束的空间调度三维模型为基础,提出改进的基于极点的启发式定位规则,给出结合禁忌搜索和基于极点的定位规则的优化算法,并通过仿真验证了算法的有效性.     

面向装配序列规划的装配成本评价研究

针对装配序列的特点提出了一个装配成本评价的模型,认为装配成本与产品装配过程中装配方向的变化次数,产品组成零件装配后的运动不确定度总和有关.提出了基于零件的装配方向矩阵确定装配方向变化次数的方法,并根据装配基础件确定零件装配后的运动不确定度.采用了基于优先关系矩阵的干涉推理方法检验装配序列的可行性,并计算装配序列中可能产生的装配干涉数目,最后用实例验证了所提模型的有效性.     

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.     

基于免疫算法的装配序列规划问题求解

针对装配序列规划问题提出了一种模拟生物免疫系统的免疫算法,并给出了亲和力计算、抗体生成、免疫选择、记忆细胞更新等的具体实现方法.实例仿真结果表明,免疫算法在装配序列规划问题的求解中充分体现了免疫系统的多样性、免疫自我调节、免疫记忆和分布式并行等特点.免疫算法较遗传算法具有更强的全局搜索能力和更快的收敛速度,有效地改善了全局收敛性能和收敛速度.     

求解装配序列规划的一种多智能体进化算法

针对求解装配序列规划的进化类算法中个体智能性不足的问题,设计了求解装配序列规划的一种多智能体进化算法。携有装配序列规划信息的智能体不仅是竞争、变异等进化操作的基本单元,同时又具有"学习"、"协作"等智能行为。实验表明,与其他各类进化算法相比,多智能体进化算法具有明显的优越性。     

基于模型检验集成规划系统的机械装配序列规划

为探索机械装配序列规划的新技术,剖析了模型检验集成规划系统和规划领域定义语言,根据一般智能规划问题的形式化定义对机械装配序列规划问题进行了形式化描述;基于装配和拆卸可逆的前提假设,利用谓词逻辑公式和时态逻辑公式对机械装配过程中的硬约束和软约束进行了描述;根据装配序列规划问题的形式化描述,对装配序列规划领域及领域的具体问题进行了定义,给出了基于模型检验集成规划系统的装配序列规划问题的求解过程.实验结果表明,该系统可以正确、有效地实施机械装配序列规划.     

Integrated knowledge-based assembly sequence planning

This paper presents a novel approach and system for the automatic generation, selection and evaluation, optimisation, and simulation of assembly plans. The information and knowledge about a product and its assembly (e.g. assembly constraints, solid model and CAD database, heuristic rules) are described using a hybrid approach and model with numeric and symbolic representation. A new methodology is presented to generate all feasible assembly sequences of the product by reasoning and decomposing the feasible subassemblies, and representing them by the assembly Petri net modelling. Qualitative strategic constraints are then used to evaluate the feasible assembly sequences. In order to obtain a good assembly sequence, some quantitative criteria such as assembly time and cost, workstation number, operator number, and part priority index are applied to select the optimal assembly sequence. Based on DFA analysis, MTM time analysis, and assemblability analysis, estimates are made of the assembly time and cost of the product when each of these sequences is used. A knowledge-based system KAPSS has been developed to achieve the integration of generation, selection evaluation, and visualisation of the assembly sequences.     

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.     

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.     

粒子群算法在装配顺序规划中的应用

装配顺序规划是计算机辅助工艺设计的一个重要环节,影响着轿车车身的装配质量和效率.针对当前装配顺序规划易产生组合爆炸等问题,提出了基于粒子群算法的装配顺序规划算法.装配偏差是影响装配质量的重要因素,因此应用装配体的装配偏差评价装配顺序.在装配顺序规划过程中,首先将装配顺序编码为粒子,根据所建立的判断规则进行识别粒子的可行性,并通过装配偏差评估可行粒子的适应度值,然后根据粒子群算法过程规划装配顺序,最后采用前翼子板案例阐述装配顺序的生成和优化过程.     

A knowledge-based engineering system for assembly sequence planning

In this study, we developed a knowledge-based engineering (KBE) system to assist engineers in promptly predicting a near-optimal assembly sequence. A three-stage assembly optimization approach with some heuristic working rules was employed to establish the proposed system. In the first stage, Above Graph and a transforming rule were used to create a correct explosion graph of the assembly models. In the second stage, a three-level relational model graph, with geometric constraints and assembly precedence diagrams, was generated to create a completely relational model graph, an incidence matrix, and a feasible assembly sequence. In the third stage, a robust back-propagation neural network engine was developed and embedded in the Siemens NX system. System users can easily access the volume, weight, and feature number through the Siemens NX system interface, input the related parameters such as contact relationship number and total penalty value, and predict a feasible assembly sequence via a robust engine. Three real-world examples were used to evaluate the feasibility of the KBE system. The results show that the proposed system can facilitate feasible assembly sequences and allow designers to recognize contact relationships, assembly difficulties, and assembly constraints of three-dimensional components in a virtual environment type.     

一种基于遗传算法的装配序列规划新方法

装配序列规划的实质是NP组合优化问题,应用遗传算法来解决装配序列规划问题可以得到较好的结果.但是使用传统的遗传算法则收敛速度较慢,通过应用Boltzman变比技术来调整遗传算法在不同时期的选择压力,则可以较好的改善遗传算法的收敛速度较慢的问题.因此提出了一种应用Boltzman变比技术的遗传算法来解决装配序列规划问题的方法.通过使用精英选择技术,保证上一代种群中的最优个体能够顺利的进入到下一代中,以防止种群中优良个体的丢失.并提出了一种基于简化关联图来生成遗传算法初始种群染色体的新方法,该方法结合人工输入的方法,可以保证了初始种群染色体的质量.根据装配序列规划问题的特点,设计了具有针对性的杂交算子和变异算子.在实际应用中,该方法取得了良好的效果.     

一种基于遗传算法的装配序列优化方法

基于遗传算法建立了装配序列生成模型,对装配序列进行优化生成。为提高优化效率,该算法将装配方向作为已知数据给出,并引入子装配体进行分层规划。最后,以蜗轮减速器装拆序列规划为实例验证该方法的有效性。     

面向虚拟装配的装配序列规划技术研究

目前产品装配序列完全通过自动推理获得的方法工程实用性不高,据此,提出将计算机的辅助知识导航与人的决策相结合的方法,通过虚拟环境下的人机协同方式来解决装配序列规划问题。首先给出了装配序列知识导航的框架结构,提出了根据当前装配状态,将几何层和语义层知识规则交替运用、递进分层的装配序列动态导航算法;给出了几何层推理所运用的优先级判断准则和假设,并对语义层规则的4层框架描述方法进行了说明;最后通过实例进行了验证。