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.     

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.     

印制电路板组装工艺规划与调度集成建模及优化方法

针对印制电路板(Printed circuit board,PCB)组装工艺与调度集成优化问题,建立集成的优化数学模型,提出将多色集合(Polychromatic set,PS)与遗传算法(Genetic algorithm,GA)相结合的新的优化方法。利用多色集合的逻辑围道矩阵和数值围道矩阵建立集成优化问题的约束模型。将约束模型与GA的遗传编码、遗传操作和适应度值计算等结合,保证GA始终在有效的解空间中进行搜索。不仅能提高遗传搜索的效率,还可以通过约束模型的修改,动态描述设备故障和PCB组装任务变化等不确定因素的影响,使得算法具有良好的适应性。实例计算结果表明,该方法能高效地实现PCB组装工艺规划与调度的集成优化,缩短PCB组装完工时间,减少交货期延迟,平衡设备的工作负荷。     

INTEGRATED APPROACH TO ASSEMBLY SEQUENCE PLANNING OF C0MPLEX PRODUCTS

Assembly sequence planning will be more difficult due to the increasing complexity ofproducts. An integrated approach to assembly sequence planning of complex products applying de-composition-planning-combination strategy is presented. First, an assembly is decomposed into a hier-archical structure using an assembly structure representation based on connectors. Then, an assemblyplanning system is used to generate the sequences that are locally optimal for each leaf partition in thestructure hierarchy. By combining the local sequences systematically in a bottom-up manner andchoosing suitable ones from the merged sequences, the assembly sequence of each parent structureincluding the whole assembly is generated. An integrated system has been completed. A complexproduct is given to illustrate the feasibility and the practicality of the approach.     

Efficient method of assembly sequence planning based on GAAA and optimizing by assembly path feedback for complex product

In the process of complex product assembly, assembly resources (fixtures, tools, operations, and so on) must enter assembly environment with parts together to rapidly finish product assembly. Assembly planning must take assembly resources into account fully. But, designer cannot plan every assembly procedure because of the lack of assembly resources during assembly design. Then, it will cause assembly failures and redesign for assembly easily. This paper investigates an efficient method of assembly sequence planning based on genetic algorithm and ants algorithm (GAAA) and optimizing by assembly path feedback to assembly process planning including assembly resources for complex products. Firstly, a new GAAA is investigated to rapidly plan assembly sequence in order to solve the nondeterministic polynomial-bounded problem in high searching and solving efficiency. Secondly, on the basis of the assembly sequence, a B-Rep filling algorithm which can form a swept volume between the part and its kinetic orientation is developed to plan assembly path interactively. Thirdly, the performance of the assembly path according to the assembly sequence is analyzed and sent back to avoid the most of assembly collisions and interventions during product assembly design. Lastly, we develop a simulating system to simulate assembly sequence and path based on component application architecture for CATIA V5. The simulating result proved that the proposed method of assembly sequence planning based on GAAA and optimizing by assembly path feedback for complex products is efficient. Assembly optimal design including assembly resources can work well.     

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.     

Assembly planning using a novel immune approach

Inspired by the vertebrate immune system, artificial immune system (AIS) has emerged as a new branch of computational intelligence. This paper explores the application of AIS in the problem of assembly planning and proposes a novel approach, called the immune optimization approach (IOA), to generate the optimal assembly plan. Based on the bionic principles of AIS, IOA introduces manifold immune operations including immune selection, clonal selection, inoculation and immune metabolism to derive the optimal assembly sequence. Maintenance of population diversity, attention to the local as well as the global search, and employment of heuristic knowledge to direct the search of optimized assembly sequences are the major concerns of IOA. The details of IOA are presented and the immune operations are discussed. Two practical products are taken as examples to illustrate the validity of IOA in assembly planning, and encouraging solutions in quality and efficiency are achieved. Comparisons with genetic algorithm demonstrate that IOA finds the optimal assembly solution or near-optimal ones more reliably and more efficiently, indicating that IOA has potential and advantages in dealing with assembly planning.     

基于JIT的加工和装配计划集成方法及其应用

针对订单生产型企业JIT准时供货的要求,建立了加工和装配计划集成模型,该模型的目标函数是为了保证产品交货期的要求;为保证计划的可行性,约束函数包括加工能力约束、装配能力约束、加工和装配顺序约束;模型为两层混合规划模型,运用了遗传算法和启发式规则,提出了混合启发式算法。最后,针对某按订单制造型企业进行了实例应用,对产品制造过程进行了分解,采用先由装配计划得出各工件的交货期,然后根据工件的交货期确定工件的加工和装配计划。     

基于遗传算法的飞机装配序列规划优化方法

在基于割集的装配顺序规划方法中，随着零件的增加，装配序列数呈指数增加，由此导致算法的组合爆炸问题。为此，提出了基于．遗传算法的装配序列规划优化方法，研究了零件装配信息的基因组表示方法，将参与装配的零件的基因组排列成序，实现装配顺序的染色体表示。采用模糊集理论建立了适应度函数，并对装配序列进行评价和优化。以某型飞机机翼产品为例，验证了技术的有效性。     

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。     

基于遗传算法的工步优化排序方法

针对数控加工中心上零件加工工步的排序问题,以辅助加工时间最短为优化目标,使用遗传算法对零件在一次装夹情况下的加工工步进行优化排序。提出了使用特征关系图和特征高度描述待加工特征之间加工的优先顺序、采用工步优先关系矩阵校验工步序列合理性的方法。论述了初始群体的生成、遗传算子以及工步优化排序的过程和算法。实际应用表明,该方法可有效提高工艺规划系统中工步的优化排序能力。     

Concurrent process/inspection planning for a customized manufacturing system based on genetic algorithm

Producing products with multiple quality characteristics is always one of the concerns for an advanced manufacturing system. To assure product quality, finite manufacturing resources (i.e., process workstations and inspection stations) could be available and employed. The manufacturing resource allocation problem then occurs, therefore, process planning and inspection planning should be performed. Both of these are traditionally regarded as individual tasks and conducted separately. Actually, these two tasks are related. Greater performance of an advanced manufacturing system can be achieved if process planning and inspection planning can be performed concurrently to manage the limited manufacturing resources. Since the product variety in batch production or job-shop production will be increased for satisfying the changing requirements of various customers, the specified tolerance of each quality characteristic will vary from time to time. Except for finite manufacturing resource constraints, the manufacturing capability, inspection capability, and tolerance specified by customer requirement are also considered for a customized manufacturing system in this research. Then, the unit cost model is constructed to represent the overall performance of an advanced manufacturing system by considering both internal and external costs. Process planning and inspection planning can then be concurrently solved by practically reflecting the customer requirements. Since determining the optimal manufacturing resource allocation plan seems to be impractical as the problem size becomes quite large, in this research, genetic algorithm is successfully applied with the realistic unit cost embedded. The performance of genetic algorithm is measured in comparison with the enumeration method that generates the optimal solution. The result shows that a near-optimal manufacturing resource allocation plan can be determined efficiently for meeting the changing requirement of customers as the problem size becomes quite large.     

基于改进蚁群算法的装配序列规划研究

装配序列规划能解决装配过程中所出现的速度和质量问题,降低生产成本。通过考虑装配影响因素,对装配体零件之间关系进行数学建模,提出一种解决该问题的改进蚁群算法。算法提出用加强装配关系矩阵来表示零件之间存在的强约束关系;用加强随机状态转移规则,使蚂蚁能更快地寻找到最优或者近优解;完善信息素更新规则,使算法能更好的利用正反馈机制。通过实例证明,该改进型算法能实际有效地解决装配序列规划问题。     

INTEGRATED APPROACH TO ASSEMBLY SEQUENCE PLANNING OF COMPLEX PRODUCTS

Assembly sequence planning will be more difficult due to the increasing complexity of products. An integrated approach to assembly sequence planning of complex products applying decomposition-planning-combination strategy is presented. First, an assembly is decomposed into a hierarchical structure using an assembly structure representation based on connectors. Then, an assembly planning system is used to generate the sequences that are locally optimal for each leaf partition in the structure hierarchy. By combining the local sequences systematically in a bottom-up manner and choosing suitable ones from the merged sequences, the assembly sequence of each parent structure including the whole assembly is generated. An integrated system has been completed. A complex product is given to illustrate the feasibility and the practicality of the approach.     

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。     

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     

基于产品结构赋权有向图模型的工艺设计

通过增加点的工艺路线属性和弧的物料属性 ,扩展了产品结构赋权有向图模型。研究了基于扩展产品结构赋权有向图模型进行工艺设计的方法与技术 ,包括工艺路线分配、加工工艺设计、装配工艺设计等。最后给出应用实例     

虚拟装配工艺规划实现技术研究

对虚拟环境下的产品装配工艺规划进行了研究,分析虚拟环境下面向集成的装配工艺规划系统结构。对虚拟装配工艺规划的三个核心问题(装配模型、装配序列规划和装配路径规划)进行描述,提出虚拟环境下面向工艺设计的产品装配模型总体结构。给出虚拟环境下装配约束关系的识别方法,实现了零部件基于约束的三维空间导航运动。建立原型系统,能够为虚拟环境下的装配工艺规划奠定基础。     

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.