Optimization of workcell layouts in a mixed-model assembly line environment

Mixed-model assembly lines enable automotive manufacturers to build different vehicles using the same equipment and facility. They allow a more rapid response to changes in customer demand. However, the increased production flexibility creates new challenges regarding assembly line planning and balancing. Part of this problem is how to allocate stock within the workcells so that non-value added operations, such as walking and waiting, are minimized. This paper addresses the issue of workstation layout optimization. Different formulations can be used to minimize non-value added time depending on the level of sophistication desired. We present three different optimization formulations and give an example of an optimized workstation layout.     

电子液压制动控制单元的混流装配线平衡优化研究

针对国内某汽车电子液压制动控制单元的混流装配线存在工作站数目过多、生产节拍不合理、作业负荷不均衡的问题,对该混流装配线进行了数学建模、自适应遗传算法求解和分析研究.首先,介绍了混流装配线平衡的基本概念,以及汽车电子液压制动控制单元的混流装配线;然后,在传统混流装配线平衡的基础上,综合考虑了工作站的数目最少、生产节拍最小...     

以成本优化为平台的混流装配线排序

随着客户需求的日益多样化,混流装配线在工业生产中得到越来越多的应用.为了降低混流装配线的闲置和超载现象带来的成本浪费,在分析混流装配线的闲置和超载成本的基础上,提出一种最小化闲置和超载成本的排序模型,并应用粒子群算法来进行优化.优化综合考虑了粒子群算法中惯性权值的关键作用,给出了一种模糊自适应的惯性权值调整方法.最后将优化模型及算法应用到具体的混流装配线,验证了该方法的有效性.这种排序方法可以降低企业的生产成本,从而提高企业的效益,在企业内具有实际的应用价值.     

Real options approach for a mixed-model assembly line sequencing problem

Mixed-model assembly lines are widely used in manufacturing. This can be attributed to increased product variety and potential just-in-time (JIT) benefits obtained by applying mixed-model assembly lines. Because of market demand volatility, the flexibility of such a line is increasingly becoming more important and, consequently, determining an accurate sequence is becoming more complex. In this paper, first, we use the real options approach to evaluate one specific type of flexibility, i.e., product-mix flexibility. This methodology is applied to determine the products’ quantity that must be satisfied by the mixed-model assembly line. Then, in order to determine a desired sequence, we consider three objectives simultaneously: (1) total utility work cost, (2) total production rate variation cost, and (3) total set-up cost. A nonlinear zero–one model is developed for the problem whose objective function is a weighted sum of the above-mentioned objectives. Moreover, two efficient metaheuristics, i.e., a genetic algorithm (GA) and a memetic algorithm (MA), are proposed. These solution methods are compared with the optimal solution method using Lingo 6 software over a set of randomly generated test problems. The computational results reveal that the proposed memetic algorithm performs better than the proposed genetic algorithm.     

混流汽车总装配线上的零部件优化配送方案研究

配送车每次配送的利用率大小是提高配送效率的主要因素,因此设计一种启发式算法使配送车一次装载的标准塑料周转箱尽可能多,提高配送车空间利用率.最后的仿真实验验证了上述配送方法的实用性,提出的零部件配送管理方法,只需使用较少的配送工人,同时降低了线旁库存,能为企业节省人力,降低生产成本.     

基于数字孪生的混流装配线资源配置优化

针对混流装配线资源配置优化效率低、时效性差、动态响应能力不足等问题,提出基于数字孪生的混流装配线资源配置优化方法.构建了物理装配车间、虚拟装配车间和生产计划系统协同工作的资源配置优化数字孪生模型,阐述了基于分段式解耦和多目标优化相结合的资源配置优化实现过程.将该方法应用于某企业混流装配线,结果表明优化后的装配线平衡率由...     

A hybrid genetic algorithm approach to mixed-model assembly line balancing

Assembly line balancing has been a focus of interest to academics in operation management for the last four decades. Mass production has saved huge costs for manufacturers in various industries for some time. With the growing trend of greater product variability and shorter life cycles, traditional mass production is being replaced in assembly lines. The current market is intensely competitive and consumer-centric. Mixed-model assembly lines are increasing in many industrial environments. This study deals with mixed-model assembly line balancing for n models, and uses a classical genetic algorithm approach to minimize the number of workstations. We also incorporated a hybrid genetic algorithm approach that used the solution from the modified ranked positional method for the initial solution to reduce the search space within the global space, thereby reducing search time. Several examples illustrate the approach. The software used for programming is C++ language .     

Solving a multi-objective mixed-model assembly line sequencing problem by a fuzzy goal programming approach

This paper presents a fuzzy goal programming approach to solve a multi-objective mixed-model assembly line sequencing problem in a just-in-time production system. A mixed-model assembly line is a type of production line capable of diversified small-lot production and is able to promptly respond to sudden demand changes for a variety of models. Determining the sequence of introducing models to such an assembly line is of particular importance for the efficient implementation of just-in-time (JIT) systems. In this paper, we consider three objectives, simultaneously: minimizing total utility work, total production rate variation, and total setup cost. Because of conflicting objectives, we propose a fuzzy goal programming-based approach to solve the model. This approach is constructed based on the desirability of decision maker (DM) and tolerances considered on goal values. To illustrate the behavior of the proposed model, some of instances are solved optimally and computational results reported.     

采用遗传算法的混流装配线平衡多目标优化

针对混流装配线操作人数已知、生产节拍待定情况下的平衡问题,研究了混流装配线第二类平衡问题的优化方法,以均衡各工作站的加权平均负荷、最小化生产节拍为优化目标,建立了求解加权平均负荷与生产节拍加权和的数学模型,并运用遗传算法对其进行求解.各优化目标数量级的统一,简化了算法求解过程,在保证解的有效性的同时提高了算法求解效率.算例分析验证了算法的有效性.     

A new approach to solve a mixed-model assembly line with a bypass subline sequencing problem

To meet the diversification of customer??s preferences, mixed-model assembly lines are installed in many manufacturing plants. In some of them, a large variation exists in assembly times among different product types. The large variation reduces production efficiency and may cause a line stoppage. These variations can be reduced by installing a bypass subline which processes a portion of assembly operations of products with relatively longer assembly times. In spite of its significance, sequencing problem on bypass subline rarely has been discussed in the literature. This paper addresses a sequencing problem with a bypass subline with the goals of leveling the part usage rates and reducing line stoppages. A novel hybrid algorithm incorporating genetic algorithm and event-based procedure is developed to solve the problem. Efficiency of the proposed algorithm is demonstrated through solving several test problems and comparing the resulted solutions with optimal solutions obtained from an exhaustive enumeration method.     

面向需求不确定的混装线物流车辆配送区域划分方法

静态的物流车辆调度方案难以适应需求不确定引起的混流装配线物料需求动态变化,导致配送效率低下,甚至生产流程紊乱等问题。针对此问题,提出了一种面向需求不确定的混流装配线物流车辆配送区域划分方法。首先,分析需求不确定对物流车辆配送量的影响,提出了基于信息熵的配送任务复杂性测度方法。其次,在复杂性测度的基础上,建立以物流配送车辆满载率最大、配送任务复杂度最小为目标的调度优化模型。最后,在实例中应用遗传算法对调度优化模型进行求解,得出物流车辆配送区域最优划分方案。结果表明,所提方法能够输出适应需求不确定的物流车辆配送区域划分方案,满足需求变化的同时,保证车辆满载率维持在最高水平,并降低配送任务复杂度,减少配送错误发生率。     

非同步混装线负荷平衡与投产排序集成优化方法

为了提高非同步混流装配线的生产效率,提出了一种负荷平衡和投产排序的集成优化方法.首先通过综合优先图,将多品种装配线平衡问题转变成单品种平衡问题;通过设计组合优先启发式方法,以最小化生产节拍为目标,生成平衡方案;在平衡方案基础上,按照生产需求,采用考虑有限缓冲区容量的NEH(Nawaz-Enscore-Ham)算法,获得...     

基于遗传算法和仿真分析的混合装配线平衡问题研究

为兼顾混合装配线平均负荷平衡和瞬时负荷平衡,提出了一种综合运用遗传算法和仿真分析的混合装配线平衡问题的求解方法.首先,基于综合作业顺序图和多品种产品在每个作业任务上的平均作业时间,采用遗传算法求解混合装配线平衡问题,其优化目标是均衡各工作站平均作业时间;然后,对遗传算法求解的一组较优解,从瞬时负荷平衡方面进行仿真分析,其优化目标是最大化各工作站利用率;最后,综合两个优化目标确定混合装配线平衡问题的最优解.通过算例分析,验证了求解方法的有效性.     

A two-phase linear programming methodology for fuzzy multi-objective mixed-model assembly line problem

We develop a fuzzy multi-objective linear programming (FMOLP) model for solving multi-objective mixed-model assembly line problem. In practice, vagueness and imprecision of the goals in this problem make the fuzzy decision-making complicated. The proposed model considers minimizing total utility work, total production rate variation, and total setup cost, using a two-phase linear programming approach. In the first phase, the problem is solved using a max–min approach. The max–min solution not being efficient, in general, we propose a new model in the second phase to maximize a composite satisfaction degree at least as good as the degrees obtained by phase one. To show the effectiveness of the proposed approach, a numerical example is solved and the results are compared with the ones obtained by the fuzzy mixed integer goal programming and weighted additive methods. The computational results show that the proposed FMOLP model achieves lower objective functions as well as higher satisfaction degrees.     

基于遗传算法的直线型和U型混流装配线平衡问题研究

针对混流装配线上不同产品作业时间差异导致的工作站瞬时负荷不均衡问题,提出了一种改进的直线型和U型混流装配线多目标平衡方法,并以装配线平衡率、平滑指数作为平衡效果的评价指标.综合考虑工序分配约束、工作站约束、优先关系约束和节拍约束等约束条件,同时兼顾工作站数最小和各工作站内不同品种产品负荷均衡2个目标函数,分别建立直线型...     

基于改进遗传算法的混装线多目标优化

在考虑产品需求速率的前提下,提出了调整加工成本的新方法,建立了混流装配线平衡问题的多目标优化模型。设计了基于自然数序列和拓扑排序的改进遗传算法对模型进行求解,改进交叉、变异操作来保护优秀基因,提出了种群扩张机制。对经典问题的计算试验结果表明,改进遗传算法在降低生产节拍的同时能优化产品加工成本,在求解效率和求解质量方面有显著的成效。     

Multi-criteria sequencing problem in mixed-model synchronous assembly lines

Mixed-model synchronous assembly line (MMSAL) is a type of assembly line that can be found in the production of large household appliances (e.g., washing machines, dryers, etc.). In this assembly line, products that are simultaneously processed on the line are transferred to the next station at the same time. In this paper, the sequencing problem of MMSAL with three objectives: (1) total idle cost, (2) total production rate variation cost, and (3) total setup cost is simultaneously studied. These three objectives are first weighted by their relative importance weights and a mathematical model is proposed for the problem. Since this problem is well known as non-deterministic polynomial-time hard class, a meta-heuristic algorithm based on simulated annealing is proposed to solve it. Performance of the proposed algorithm is compared against the Lingo 9 software. The computational results validate the efficiency and effectiveness of the proposed algorithm.     

Design configuration for a mixed-model assembly system in case of low product demand

In order to accompany the increasing variety of costumers’ demands, manufacturers tend to produce different models of the same product on an assembly line by introducing group assembly (GA) design concepts that improve the flexibility of assembly systems. Generally, when the demand for a set of similar products is relatively low and the set-up time is significant, the beneficial effects of the task repeatability of the straight line configuration are difficult to achieve. As a consequence, the fixed-point assembly philosophy is often preferred. This paper addresses the application of a mixed-model assembly balancing problem to an assembly-to-order environment in the case of low production rates and large number of tasks. The aim of this work is to propose an alternative design procedure for the balancing of semi-automated and mixed-model assembly systems under low product demand effects by the application of multi-turn circular transfers, such as a multi-stations rotating table. This layout configuration permits a job enlargement for human operators and, at the same time, provides an increment in task repeatability through the work-pieces assembling by increasing the number of the turns of the transfer. Finally, the developed heuristic procedure is tested on a simple rotating table assembly cell, a partial representation of a complete assembly system of domestic air compressors.     

模拟退火算法在混流装配投产中的应用

对混流装配投产顺序的不同调度目标进行分析,建立混流装配投产的目标函数,着重讨论了模拟退火算法的原理及在混流装配投产中的应用流程,最后通过实例对算法进行验证.验证结果表明,模拟退火算法比常规的目标追迹法更有效,可以在生产中推广应用.