面向产品族的混流装配线平衡研究

基于产品族的模块化与通用性,研究了面向产品族装配的混流线平衡问题.基于对一族产品装配过程的聚类分析,提出了面向产品族的混流装配线的平衡设计方法和模型,可以为大规模定制企业实现面向产品族的混流装配提供参考,并用案例说明本文方法的应用.     

免疫粒子群算法在混流装配线排序中的应用

混流装配线上的产品投产排序是影响装配线生产效率的重要因素.建立以最小化装配线总闲置—超载成本为优化目标的装配线排序模型,采用粒子群算法来解决混流装配线的投产排序问题.考虑到基本粒子群算法易陷入局部最优解的问题,引入免疫算法思想对其进行改进,根据抗体亲和性与浓度值的计算,及时进行粒子的替换以维持种群的多样性,防止粒子过早...     

缓冲区容量约束下发动机混流装配线排序研究

为解决缓冲区容量约束下发动机混流装配排序问题,以关键部件消耗均匀化和最大完工时间最小化为目标,建立了优化数学模型,设计了一种多目标遗传算法,采用了混合交叉算子和启发式变异方法,并设计了基于帕累托分级和共享函数的适应度函数,将多目标遗传算法和多目标模拟退火算法的优化结果进行了比较。研究结果表明,多目标遗传算法在满意度和计算效率方面均优于多目标模拟退火算法,是一种有效的混流装配线排序问题求解算法。     

考虑效率差异和流动分配的混流装配线工人优化

本文研究了考虑工人装配水平差异、不同工位之间可以流动分配的装配线工人优化调度，在确定混流装配线的排序后，装配工人在其最擅长的工位工作，在完成本工位的工作后参与其他工位的装配工作，定义相关的优化因素变量和约束条件，建立了考虑工人工位效率差异且可流动分配的混流装配线工人优化数学模型。采用削峰填谷算法和多种群移民算法进行工人的调整和均衡优化，利用一个三层神经网络对削峰填谷的工位进行评估选择，得到工人的最优分配方案，最后通过Matlab对举例进行了验证。算例优化后，减少了2名装配工人，并提高了装配线的平衡率。     

SPS模式下零部件配送质量的混流装配线总装排序

针对零部件供应不能实现JIT的混流装配线排序问题,提出在SPS物料配送模式下,以提高零部件配送质量为目的,分析拣选环节筐车排列顺序对零件拣选错配和漏配的影响,从两方面探讨通过安排筐车排列顺序以最小化拣选错配和漏配率;同时在总装环节,追求零部件消耗速率均衡化.从而建立同时考虑总装和零部件配送两阶段优化的混流装配线排序模型.结合排序案例,证明该排序模型能在平准化零部件消耗的同时提高配送质量.     

遗传禁忌搜索算法在混流装配线排序中的应用

针对混流装配线排序问题，提出了一种混合遗传禁忌搜索算法，在每一代遗传演化之后，按一定比例随机选择部分解进行禁总搜索，以提高算法的全局搜索能力和收敛性。通过一个混流装配线排序实验，分别利用遗传算法和遗传禁忌搜索算法进行求解，结果表明遗传禁忌搜索算法具有更好的全局搜索能力和收敛性能。     

混合粒子群算法在混流装配线优化调度中的应用

应用粒子群算法求解混流装配线的优化调度问题,给出粒子的构造方法,并针对算法中存在过早收敛的问题,提出了一种与局部优化和粒子微变异方法相结合的混合粒子群算法.给出了一个实例,实例应用粒子群算法和混合粒子群算法分别进行求解,与其他一些方法比较表明,混合粒子群算法可以有效、快速地求得混流装配线优化调度问题的解.     

混流汽车液压电子制动控制单元装配线平衡问题设计与研究

为了有效解决混流汽车液压电子制动控制单元装配线平衡问题,提出了基于优化遗传算法的求解方法。首先对于复杂的液压电子制动控制单元装配线的工艺装配过程进行设计与计算,分析液压电子制动控制单元的生产工艺步序、工作站数、生产节拍、以最小化生产节拍、最小化工作站数以及均衡各工作站的加权平均负荷进行多目标优化。同时构建液压制动控制单元装配工艺平衡问题的测量模型,并进行案例分析,利用模型求解。最后,以某独资汽车零部件工厂的汽车液压电子制动控制单元装配线为例,对工艺过程进行数学建模,采用优化遗传算法进行求解。结果表明,所提方法与测量模型可为汽车液压电子制动控制单元装配线平衡问题提供可行的解决方案。     

考虑转换约束的汽车混流装配线投产排序研究

讨论了有生产线线边替补人员协助完成超载工作量的情况下,汽车混流装配线投产排序的问题,并且考虑工作人员行走占用的时间。通过对某整车厂进行实地调研,将汽车装配生产中的优化问题从以往文献中只考虑的总装车间向前延伸到涂装车间,给出连续喷涂某种颜色的车辆数的上界s。在此基础上,并考虑总装线线边物料消耗速率波动均衡和子装配工负荷均衡的约束条件,建立涂装切换成本和总装车间人工成本最小化的数学模型。最后,用CPLEX对模型进行优化求解,并分析得出生产节拍和工作站长度等参数与总成本之间的变化关系。     

变速箱多品种混流装配线信息管理系统设计

基于现代汽车制造企业信息化、网络化和柔性化的要求,设计并开发了一个变速箱多品种混流装配线信息管理系统,该系统以信息技术、计算机应用技术和质量管理方法为手段,对变速箱装配线上的信息进行采集、监控、分发与管理,并保存产品质量信息,提高了汽车零部件企业生产现场的信息化水平,具有良好的应用前景.     

Role of similarity measures in PCB grouping procedures

The problem of grouping printed circuit boards (PCBs) for simultaneous assembly on electronic assembly machines is an extension of the set-covering problem. A general approach based on cluster analysis and measure of similarity between PCBs is suggested as a basis of PCB grouping. The approach is independent of the specific similarity measure used. We show that, due to the analogy between this problem and the problem of machine cell formation in group technology, similarity measures developed for the second problem are useful as building blocks in a general framework that solves the PCB grouping problem.     

基于改进田口方法的轮毂装配过程质量控制研究

针对风力机轮毂装配工序的质量控制问题，结合多品种小批量生产模式的特点，提出了一种面向定位布置的轮毂装配关键工序识别与监控的方法。综合考虑轮毂装配生产中的成本因素及相对质量损失，制定装配工序的质量特性损失标准，采用改进的质量损失函数识别轮毂装配关键工序；为解决统计过程控制（SPC）方法应用于小批量生产模式的瓶颈，引入基于直觉模糊集的工序相似性分析与评定方法，通过分析工序相似性的影响因素，构建轮毂装配成组工序相似性评判指标体系及评定模型，完成工序相似性的测度。最终使用SPC方法监控管理轮毂装配关键工序，确保轮毂的装配质量。该研究为小批量生产模式中运用SPC方法管理过程质量提供了理论依据。     

基于装配相似性与灰色模型的汽车装配工时预测

汽车企业为适应市场需求的不断变化,加快了推出新车型产品的步伐。针对目前汽车总装混流工时预测速度缓慢的问题,提出基于装配相似性与灰色理论GM（0,N）模型的装配工时预测方法。将装配工时按特性分为取料时间、定位时间和连接时间,提取影响各部分工时的关键因素,通过计算样本与基准零件的装配相似系数,结合装配工时在MATLAB中构建拟合曲线,最后在函数关系式和GM（0,N）模型中分别预测定位时间和连接时间。通过与MTM法进行比较,证实该方法具有准确性和高效性。     

Assembly tolerance allocation using a coalitional game method

Assembly tolerance allocation in modern manufacturing industries is important because it directly affects product quality and manufacturing cost. Loose tolerances may cause quality deficiency while tight tolerances can increase the cost. It is significant to develop a reasonable tolerance allocation strategy for every assembly component combining the cost and quality demands. Traditionally, designers often adopt the single objective optimization with some kind of constraint or establish a comprehensive evaluation function combining several optimization objectives with different weights to solve the tolerance allocation problem. These approaches may not be desirable as it is difficult to adequately consider the interaction and conflict between the cost and quality demands. In this article, an assembly tolerance allocation method using coalitional game theory is proposed in an attempt to find a trade-off between the assembly cost and the assembly quality. First, the assembly tolerance allocation problem is formulated as a multi-objective optimization problem and the concept of the Pareto-optimal solution is introduced. Then, how the assembly tolerance allocation model is transformed into a coalitional game model is discussed, and a key technique of transforming the tolerance design variables into the game strategies is presented. Further, the Shapley value method of coalitional game based on each player's contribution evaluation to the profit of the whole coalition is given. Finally, the feasibility of the procedure is demonstrated through an example of vehicle front structure assembly.     

A cost estimation model to support automation decision in assembly systems design

Cost analysis is crucial in the design of assembly systems and the decision on their level of automation (LoA). This paper presents a cost estimation model of assembly system that is used to decide their LoA during the early phase of projects. Based on an extensive literature review, a complete cost model integrating multiple cost drivers is proposed. This model is then exploited to create the objective function of an integer linear programme model utilised to solve the LoA decision problem. The work provides a way to perform cost estimation of assembly systems alternatives and to decide the most appropriate LoA in assembly. The cost estimation model is built with a parametric approach allowing the definition of various optimisation objectives. The proposed integer programme, complement this approach by proposing the suitable constraints set, that describes the LoA decision problem.     

基于MAF实验的战斗部模型设计研究

为设计战斗部的实验模型,利用相似理论确定了实验模型的相似准则与相似参数.在战斗部模型设计中,校核了战斗部模型的载荷和堵塞度.该实验模型能够用于MAF(Model Aerodynamic Facility)风洞实验,对战斗部设计具有一定的指导意义.     

基于XGBoost的车身尺寸装配质量智能预测模型

针对汽车多级制造系统中传统机器学习方法处理多元数据样本时间久、精度低等问题,提出一种基于XGboost的车身尺寸装配质量智能预测模型,解决多级制造系统的车身装配精准预测控制问题。首先,通过对车身多级装配过程的分析,对数据样本进行预处理,建立基于Spearman系数的不同特征要素的绝对相关性矩阵;其次,对生产流程的相关数据实时采集、清洗及挖掘分析,提出数据分析流程与数据处理框架,建立基于XGBoost的车身尺寸装配质量智能预测模型,并通过对模型性能的有效评估实现对车身尺寸装配的精准控制;最后,仿真实例对比分析表明,基于XGboost的质量智能预测模型能精准地解决多级制造系统中的车身装配质量控制问题。     

基于启发式算法的电控板装配线线平衡优化

为了解决人员配置不稳定而导致的工位作业负荷不平衡问题,以某电控板装配企业为对象,构建其电控板装配线生产模型和线平衡优化模型。在该优化模型中,将约束条件转化为启发式规则,改进模型的参数设置和处理过程,将该模型转化为可求解的启发式算法。以该企业某电控装配线为例,通过线平衡优化实验证明该模型有效提高产量和线平衡率,说明该模型是有效和实用的。     

A dynamic programming approach to integrated assembly planning and supplier assignment with lead time constraints

As manufacturers face fierce competition in the global market, responsiveness has become an important competitiveness factor in addition to quality and cost. One essential responsiveness strategy is to reduce product development and lead times by integrating assembly planning with supplier assignment. This paper addresses the problem of integrated assembly and supply chain design under lead-time constraints by formulating and solving an optimisation problem with minimal total supply chain costs. This new time-constrained joint optimisation problem belongs to an NP-hard resource-constrained scheduling problem. To model this problem effectively, we develop a novel Hyper AND/OR graph and apply it for integrating assembly and supply chain decisions. We also develop a dynamic programming model and associated algorithm in order to solve the integrated optimisation problem with pseudo-polynomial time complexity in practice. Numerical case studies validate that the methods developed can solve the integrated decision-making problem optimally and efficiently. This paper overcomes the limitations of previous studies on concurrent assembly decomposition and supplier selection, which optimises cost without time constraints. The models and results of this research can be applied to a variety of areas including assembly design, maintenance module planning and supply chain restructuring.     

Mixed model assembly system with multiple secondary feeder lines: layout design and balancing procedure for ATO environment

The constant research for efficiency and flexibility has forced assembly systems to change from simple/single assembly lines to mixed model assembly lines, while the necessity to reduce inventory has led the transition from single to multi-line systems, where some components are assembled in secondary lines, called feeder lines, connected to the main one by a ‘pull philosophy’. A possible approach to configure such an assembly system is to balance the main line first and use the retrieved cycle time to balance each feeder line separately, which is a questionable solution, especially if operators can perform tasks on both the feeder and the main line. Moreover for its complexity the mixed model balancing problem is usually solved transforming it into a single model by creating a single ‘virtual average model’, representative of the whole production mix. The use of a virtual average model assumes that the processing times of some models are higher or lower than the cycle time, which creates overload/idle time at the stations. This approach, especially in complex multi line production systems, largely reduces the assembly line productivity and increases the buffers dimensions. This paper faces the mixed model assembly line balancing problem in the presence of multiple feeder lines, introducing an innovative integrated main-feeder lines balancing procedure in case of unpaced assembly systems. The proposed approach is compared with the classical one and validated through simulation and industrial applications.