A Petri net-based heuristic for mixed-model assembly line balancing problem of Type-E

To effectively respond to the changing market demands, a manufacturer should produce variety of products with small lots. Thus, multiple products (models) are assembled simultaneously on a same line. However, it is very challenging to balance such an assembly line. This paper conducts a study on balancing a mixed-model assembly line of Type E. To solve this problem, a coloured-timed Petri net model is developed to describe the task precedence relationship. Also, the optimisation problem is formulated as a mathematical programming model. Then, with the models, a two-stage heuristic algorithm is proposed to solve the problem. At the first stage, based on the Petri net model, a P-invariant algorithm (PA) is presented to minimise the number of workstations. At the second stage, a heuristic is proposed to further minimise the cycle time by combining the PA with a binary search algorithm (BSA). Performance of the proposed method is evaluated by an illustrative example and numerical experiments. It is shown that it works well in terms of both solution accuracy and computational efficiency for large size problems.     

Workload balancing and manufacturing complexity levelling in mixed-model assembly lines

To effectively react and meet the current ever growing demand for individualised motor vehicles, built to customer specific requirements, automotive industry has accelerated its transition towards mass-customisation. As a result, the number of new model introductions has drastically increased over the past three decades. To cope with this intensified customisation, the current automotive assembly platforms are designed to assemble a wide range of relatively different models, and are turned into mixed-model assembly lines (MMALs). This implies that the set of tasks to be performed on each workstation is no longer stable but varies highly with the model-mix. As a consequence, the manufacturing complexity increases at the workstations and throughout the whole assembly system. This paper proposes a method to monitor manufacturing complexity at each workstation while the MMAL is being balanced. An entropy-based quantitative measure of complexity, which incorporates the variability of each task duration, is developed. This measure is used to monitor the manufacturing complexity level at each workstation. An integrated mixed-line balancing and complexity monitoring heuristic is proposed, to determine workload balance solutions, in which manufacturing complexity is levelled throughout the workstations composing the line. This procedure is tested on a real data-set provided by an automotive manufacturer. The results are reported and thoroughly discussed.     

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。     

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。     

Measuring complexity in mixed-model assembly workstations

In an effort to maintain or increase their market share and at the same time prevent costs from escalating, manufacturing organisations are increasingly using their current manufacturing system to produce custom output. As a consequence, the large number of product variants increases significantly the complexity of manufacturing systems, both for the operators as for the support services. This is especially true in automotive industry, where customisation is increasing at a rapid pace. To counter the ensuing loss of productivity, a more fundamental approach to dealing with this complexity in manufacturing processes is required. In order to investigate the impact of complexity on production performance, one must first delineate the concept and then identify as unambiguously as possible highly complex workstations. This article defines complexity at the workstation level and proposes a complexity measure for mixed-model assembly workstations. Based on data from several leading automotive companies from Belgium and Sweden, some statistical models are proposed to characterise workstations complexity. The models are described and their validity and accuracy are discussed.     

An adaptive genetic algorithm approach for the mixed-model assembly line sequencing problem

A mixed-model assembly line (MMAL) is a type of production line that is capable of producing a variety of different product models simultaneously and continuously. The design and planning of such lines involve several long- and short-term problems. Among these problems, determining the sequence of products to be produced has received considerable attention from researchers. This problem is known as the Mixed-Model Assembly Line Sequencing Problem (MMALSP). This paper proposes an adaptive genetic algorithm approach to solve MMALSP where multiple objectives such as variation in part consumption rates, total utility work and setup costs are considered simultaneously. The proposed approach integrates an adaptive parameter control (APC) mechanism into a multi-objective genetic algorithm in order to improve the exploration and exploitation capabilities of the algorithm. The APC mechanism decides the probability of mutation and the elites that will be preserved for succeeding generations, all based on the feedback obtained during the run of the algorithm. Experimental results show that the proposed adaptive GA-based approach outperforms the non-adaptive algorithm in both solution quantity and quality.     

Planning of buffers within mixed-model lines

Summary This paper deals with the planning of buffers within a mixed-model line, which is typical of vehicle industries. The positioning of the buffers will be of special interest and will be discussed by an exact method and three heuristics. In addition the determining of buffer sizes will briefly be addressed. All aspects are considered concerning their influence on scheduling criteria. We will demonstrate that the placing of buffers leads to an improvement in job sequencing problems. In particular a balanced capacity usage will be achieved.     

Minimising utility work and utility worker transfers for a mixed-model assembly line

Mixed-model assembly lines (MMALs) are types of production lines that are able to respond to diversified costumers’ demand for a variety of models without holding large inventories. The effective utilisation of a mixed-model assembly line requires the determination of the assembly sequence for different models. In this paper, two objectives are considered in a sequential manner, namely minimising: (i) total utility work, which means work from an additional worker to assist an operator for completion of an assembly task; and (ii) utility worker transfer which states the move of a utility worker to a different segment of the assembly line. First, due to the NP-hard nature of the problem, three heuristic methods are proposed with the aim of minimising total utility work. Then, the solutions which are obtained from the heuristics are improved in terms of the total number of utility worker transfers via a local search based method. Furthermore, the solution approach was applied in a real life mixed model tractor assembly line. Results validated the effectiveness of sequencing approach in terms of solution quality.     

Balancing mixed-model assembly lines with adjacent task duplication

When a mixed-model assembly line (MAL) is balanced, it is generally assumed that the variants of a task over different models should be assigned to an identical station. In this study, this restriction is relaxed and the variants of a task over different models can be duplicated on two adjacent stations (referred to as adjacent task duplication) to improve the MAL’s efficiency. The adjacent task duplication incurs few additional training and tool duplication costs as each task is duplicated on at most two stations. Moreover, for each task, the assembly part storage is not duplicated as it can be shared by the two adjacent stations. The mathematical model of this problem is formulated and some important properties are characterised. A branch, bound and remember algorithm is then developed to solve the problem. The performance of the proposed algorithm is tested on 900 representative instances, of which 889 instances are optimally solved. The experimental results show that the use of the adjacent task duplication policy effectively reduces the number of stations, especially when the WEST ratios are small.     

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.     

基于车型相似度的装配线排序

通过总结混流装配线排序问题,提出了一种新的装配线排序模型.根据装配车型的关键件不同,引入车型相似度的概念,应用遗传算法解决以最大化相似度总和为目标的混流装配线优化排序问题.经实践中应用,关键件装配更换次数减少了70%.     

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...