基于Pareto解集蚁群算法的拆卸序列规划

为提高产品拆卸序列规划的效率,分析拆卸序列规划问题中的多个优化目标平衡问题,提出一种基于Pareto解集的多目标蚁群优化算法求解此类拆卸规划问题,并给出拆卸序列的构建过程。通过利用拆卸矩阵推导拆卸可行条件,获得可以执行拆卸操作的零件及其可行的拆卸方向。通过利用零件的轴向包围盒(Axis aligned bounding boxes,AABB)计算零件的拆卸行程。考虑拆卸方向改变次数、拆卸总行程、拆卸零件数量为优化目标,通过利用蚁群算法搜索可行解并计算各个解之间的支配关系,得到Pareto解集,实现求解优化的拆卸序列,给出算法的具体步骤。最后以单杠发动机为拆卸实例,利用所提方法进行拆卸序列规划求解,通过分析试验结果,并对比典型的单目标蚁群规划算法,证明了该方法的高效性和可行性。     

基于蚁群算法的产品拆卸序列规划研究

为了能以较高的效率求解出产品拆卸序列的方案,首先阐述了拆卸可行性信息图的概念,将产品的拆卸序列规划问题转述成对该加权有向图中具备最优值的路径搜索和寻优问题。提出了一种蚁群优化算法,并结合对产品元件的拆卸路径求解工具,以实现对产品拆卸可行性信息图的构建和对拆卸方案的搜索和寻优。蚂蚁的一条遍历路径代表了一个描述产品元件拆卸的方案;蚂蚁已经遍历过的路径上代表可行操作的节点数决定了其留下的信息素。启发式信息的求解分为两个部分,包括了确定启发式向量和求出启发式信息值,它们分别表征了方案的可行性及其优异程度。最后,通过一个实例,验证了这一方法的可行性及其计算效率。     

A novel approach to the geometric feasibility analysis for fast assembly tool reasoning

A product assembly or disassembly is completed by means of proper tools. The selection of feasible tools is an important process in planning a complete assembly or disassembly sequence. A key tooling consideration in assembly or disassembly planning is to reason the available space for a tool application during the assembly or disassembly of a product. Currently, assembly tool reasoning about space mainly depends on simulation-based or user-interactive approaches because of its computational complexity. These approaches are inappropriate in dealing with various what-if scenarios regarding assembly or disassembly planning in a rapid product development. They also depend on users’ expertise or experience in assembly or disassembly. This paper presents a novel approach to the geometric feasibility analysis for fast assembly tool reasoning. Techniques described in this paper are advantageous not only in the aid of generating a complete assembly or disassembly plan but also in the efficient support of such systems as computer-aided assembly planning (CAAP), design for manufacturing (DFM), design for assembly (DFA), design for disassembly (DFD), and computer-aided tool selection (CATS).     

An intelligent interactive approach for assembly process planning based on hierarchical classification of parts

Assembly process planning is a difficult problem in the product design and development process. In order to reduce the difficulty of assembly process planning (APP), this paper presents an approach to finding a practical plan for assembly process through the intelligent interactive method based on hierarchical classification of parts. First, two hierarchical classification principles towards interactive disassembly are presented based on the key assembly constraint (KAC). Then, the initial assembly relationship of the product is readjusted to a new hierarchical structure which is more suitable for assembly planning according to a novel hierarchical classification algorithm. On the basis of the new hierarchy of product, an intelligent disassembly-based approach is presented, which not only takes full advantage of the ant colony algorithm for searching and constructing an initial assembly sequence with three available assembly principles, but also makes full use of the experience and knowledge of the human being for achieving a better assembly process. The intelligent disassembly approach can achieve an optimized assembly sequence, paths and scheme necessary information regarding the required assembly fixtures and tools. Finally, a case study shows that the proposed approach is feasible and practical.     

面向绿色制造的产品选择拆卸技术研究

针对机电产品的绿色制造,分析了产品生命周期中设计、服役使用和退役处理三个阶段的产品零部件选择拆卸问题;提出了基于蚁群算法的产品选择拆卸规划方法,给出了面向选择拆卸的产品图建模和选择拆卸序列的动态构建过程,并考虑拆卸方向改变次数和拆卸零件总数原则,以求解优化的选择拆卸序列;讨论了面向全生命周期的产品选择拆卸平台构成,并初步实现了平台的功能.最后,用实例说明了选择拆卸平台的工作过程.     

基于改进人工蜂群算法的产品拆卸序列规划

为了提高复杂产品拆卸序列规划效率,提出了一种改进的人工蜂群算法用于此类问题求解。通过拆卸混合图表达产品零部件之间的连接关系和优先约束关系,并推导出可行拆卸序列的约束表达式,建立拆卸序列规划数学模型和适应度计算公式。对初始种群进行了优先约束规划,提出一种可行度算法用于蜂群对蜜源的搜寻与选择。定义了自适应选择参数、动态平衡可行度与适应度算法的优先配比,以实现复杂产品拆卸序列规划的快速求解。最后以内啮合齿轮泵为实例,利用所提方法进行了拆卸序列规划求解,通过分析实验结果,并对比传统人工蜂群算法,证明了该方法的可行性和高效性。     

复杂产品并行拆解建模及规划方法研究

为提高复杂产品并行拆解的效率,提出了一种针对复杂产品的并行拆解建模及规划方法。通过构建拆解约束图确定零件之间的连接关系,利用传递闭包算法进行聚类分析,将产品分解为若干个组件的集合。提取组件与组件之间的连接零件集合,利用人工蜂群算法对连接零件集合以及每个组件分别进行拆解规划,从而得到复杂产品的并行拆解模型及规划序列。以摩托车发动机的并行拆解为例,对该方法进行了验证,结果表明该方法能有效地实现复杂产品的并行拆解,提高复杂产品的拆解并行度和拆解效率。     

A converse method-based approach for assembly sequence planning with assembly tool

In order to improve the quality and efficiency of assembly sequence planning for complex mechanical product, a converse method-based approach for assembly sequence planning is proposed. Firstly, the disassembly interference matrix of product and the disassembly constraint degree of part are defined. Product disassembly sequence is obtained through geometry reasoning algorithm and the searching work of disassembly sequence is simplified by the contact constraint set. Secondly, the maneuverability of tool is inspected through the using matrix and interference matrix of assembly tool. The infeasible disassembly sequence is excluded and product assembly sequence is obtained by reversing the order of disassembly sequence. Thirdly, the evaluation mechanism for assembly sequence is established to get the optimal assembly sequence and the optimal assembly sequence is selected by calculating the value of evaluation function. Finally, a vibration generator is illustrated to verify the validity and feasibility of the proposed approach.     

Parallel disassembly sequence planning for complex products based on fuzzy-rough sets

The goal of the parallel disassembly sequence planning (PDSP) is to find an optimal feasible disassembly task sequence with many constraints. Due to the PDSP of complex product is restricted by various factors, the DPSP problem is not easily solved in a general form. In order to reduce the time complexity, this paper presents a PDSP method based on fuzzy-rough sets. Five disassembly factors including assembly constraints factor, disassembly precedence factor, disassembly time factor, disassembly tool factor, and combination type factor are defined and formulated. In light of the characteristics of PDSP, the fuzzy-rough set mapping model of parallel disassembly is constructed. The components to be disassembled are taken as knowledge universe, and disassembly membership function as objection function is defined as the indiscernibility relation. Then, the fuzzy-rough set mapping model of parallel disassembly is adopted to generate the optimum parallel disassembly sequence. Finally, two examples validate the proposed method.     

Mechanical Product Disassembly Sequence and Path Planning Based on Knowledge and Geometric Reasoning

A feature-based assembly model is proposed for disassembly sequence planning, and establishing a correct and practical disassembly path for the part in the product, based on geometric reasoning and knowledge. The fundamental assembly modelling strategy for a product is based on the mating features of its parts. An algorithm is introduced which uses the information provided by the mating features of parts in the product to find the candidate parts for disassembly and to carry out disassembly path planning. A complete and accurate interference checking approach is used to ensure no global collision while disassembling a part. In some cases, it cannot be implemented by geometric reasoning alone, so a set of criteria and heuristic rules based on knowledge, constraints, relationships among parts, and quantitative disassemblability assessment are used. It can also be carried out interactively by the user when necessary. The proposed method is integrated with the CAD model of the product. The user can visually disassemble the product while planning, so it is easier to carry out the disassembly planning and generate an optimal sequence.     

A particle swarm optimization algorithm with neighborhood-based mutation for sequence-dependent disassembly line balancing problem

For environmentally conscious and sustainable manufacturing, manufacturers need to incorporate product recovery by designing manufacturing systems to include reverse manufacturing by considering both assembly and disassembly systems. Just as the assembly line is considered the most efficient way to assemble a product, the disassembly line is seen to be the most efficient way to disassemble a product. While having some similarities to assembly, disassembly is not the reverse of the assembly process. The challenge lies in the fact that it possesses unique characteristics. In this paper, we consider a sequence-dependent disassembly line balancing problem (SDDLBP) that is concerned with the assignment of disassembly tasks to a set of ordered disassembly workstations while satisfying the disassembly precedence constraints and optimizing the effectiveness of several measures considering sequence-dependent part removal time increments. SDDLBP is not a trivial problem since it is proven to be NP-complete. Further complications occur by considering multiple objectives including environmental and economic goals that are often contradictory. Therefore, it is essential that an efficient methodology be developed. A new approach based on the particle swarm optimization algorithm with a neighborhood-based mutation operator is proposed to solve the SDDLBP. Case scenarios are considered, and comparisons with ant colony optimization, river formation dynamics, and tabu search approaches are provided to demonstrate the superior functionality of the proposed algorithm.     

A novel ant colony algorithm for assembly sequence planning

An ant colony algorithm-based approach to assembly sequence generation and optimization of mechanical products is presented in this article. For diverse assemblies, the approach generates different amount of ants cooperating to find optimal solutions with the least reorientations during assembly processes. Based on assembly by disassembly philosophy, a candidate list composed by feasible and reasonable disassembly operations that are derived from disassembly matrix guides sequences construction in the solution space expressed implicitly, and so guarantees the geometric feasibility of sequences. The state-transition rule and local- and global-updating rules are defined to ensure acquiring of the optimal solutions. Cases are given to show the effectiveness of the proposed approach, and the characteristics of the algorithm are discussed.     

Disassembly sequence planning approach for product virtual maintenance based on improved max–min ant system

In order to realize automation and intelligence of product disassembly process in a virtual maintenance environment, an improved max–min ant system based methodology for product disassembly sequence planning was proposed. The feasibility graph for product disassembly process was defined and the mathematic model of product disassembly sequence planning problem was set up. Thus, the problem of product disassembly sequence planning was transformed into the problem of searching optimal path on a feasibility graph. Moreover, an improved max–min ant system based on the strategy of sorting elite ants was presented and the flowchart of the improved algorithm was designed. Finally, by simulation examples, the robustness and outperforming others of the improved algorithm were verified.     

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.     

Ant colony optimization for disassembly sequencing with multiple objectives

Product disassembly takes place in remanufacturing, recycling, and disposal. The disassembly line is the best choice for automated disassembly, so it is essential that it be designed and balanced to work efficiently. The multi-objective disassembly line balancing problem seeks to find a disassembly sequence which provides a feasible disassembly sequence, minimizes the number of workstations, minimizes idle time, balances the line (ensures similar idle times at each workstation), as well as addressing other disassembly-specific concerns. However, finding the optimal balance is computationally intensive due to exponential growth, with exhaustive search quickly becoming prohibitively large. In this paper, an ant colony optimization metaheuristic is presented for obtaining optimal or near-optimal solutions to the disassembly line balancing problem. Examples are considered to illustrate implementation of the methodology. Conclusions drawn include the consistent generation of near-optimal solutions, the ability to preserve precedence, the superior speed of the metaheuristic, and its practicality due to its ease of implementation.     

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.     

Sequencing mixed-model assembly lines by considering feeding lines

A mixed-model assembly line is a type of production line where different models of a product are assembled on. Mixed-model assembly lines can respond to unanticipated changes in product demands quickly without keeping so many inventories. Designing mixed-model assembly line involves solving the traditional problems of the assembly line design (consists of balancing problem, determining cycle time, and the number and sequence of stations) in addition of determining the sequence of products in assembly line. The main goal of this paper is presenting a method in order to determine the sequence of products in mixed-model assembly line by considering Just-in-Time systems. Moreover, supplying some required components from feeding lines is considered. A mathematical model is presented which is capable of specifying the sequence of products in the mixed-model assembly line by considering main criteria and keeping feeding lines balanced. Mathematical model can be used for solving small-size problems. Because the combinatorial nature of sequencing problems typically provides an intractable search space for problems of “real world” size, the search heuristics of simulated annealing and ant colony algorithms are presented and used to find solutions for several problem sets. Experimentations show that the simulated annealing approach outperforms the ant colony approach in objective function performance.     

Optimisation of operations sequence in CAPP using an ant colony algorithm

Computer-aided process planning (CAPP) forms an important interface between Computer-aided design (CAD) and Computer-aided manufacturing (CAM). It is concerned with determining the sequence of individual manufacturing operations required to produce a product as per technical specifications given in the part drawing. Any sequence of manufacturing operations that is generated in a process plan cannot be the best possible sequence every time in a changing production environment. As the complexity of the product increases, the number of feasible sequences increases exponentially, and there is a need to choose the best among them. This paper presents an application of a newly developed metaheuristic called the ant colony algorithm as a global search technique for the quick identification of the optimal operations sequence by considering various feasibility constrains. A couple of case studies are taken from the literature to comparing the results obtained by the proposed method.     

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。     

装配/拆卸干涉矩阵的自动生成技术

讨论了基于ProEngineer三维设计模型的干涉矩阵自动生成方法。通过定义集成干涉矩阵来表达零件间装配/拆卸时的干涉关系,详细给出了产生干涉矩阵所需的零件/装配体信息提取和基于零部件运动扫掠体的干涉检查过程,采用干涉矩阵元素的二进制和十进制转换来降低计算复杂性,给出了干涉矩阵生成的算法流程并初步开发了原型系统。通过示例说明了系统的应用过程。