A colour-batching problem using selectivity banks in automobile paint shops
A colour-batching problem using selectivity banks in automobile paint shops
复制标题
DOI：
10.1080/00207543.2014.948970
复制
发表时间：
2015-02-16
影响因子：
9.2
通讯作者：
Zhou, Jiangong
中科院分区：
文献类型：
--
作者：
Sun, Hui;Fan, Shujin;Zhou, Jiangong
本文研究了在汽车涂装车间中经常出现的颜色排序问题，其中选择性银行被用作存储和检索系统，以执行在涂装操作之前对车身进行重新排序的实践。重新排序的目的是获得面向颜色的批次汽车，以降低喷漆店的设置成本。在本文中，两个启发式程序，排列和洗牌算法，旨在快速，有效地实现良好的色彩效果。在汽车放置阶段可以应用排列启发式算法，而在汽车释放阶段可以利用洗牌启发式算法。计算实验进行了评估所提出的算法的性能。结果表明，洗牌启发式可以产生可比的汽车检索序列与一个确切的分支和界限的方法，和建议的排列和洗牌启发式可以联合应用，以实现良好的颜色检索在一个非常短的时间内，小于0.4秒的比较，与现有的两种颜色检索方法。这些研究成果对汽车制造业的色彩管理实践具有重要的指导意义。
This paper studies the colour-batching problem frequently raised in automobile paint shops, where selectivity banks are used as storage and retrieval systems to execute practices of resequencing car bodies before painting operations are performed. The purpose of resequencing is to obtain colour-oriented batches of cars in order to reduce setup costs incurred in paint shops. In this paper, two heuristic procedures, arraying and shuffling heuristics, are developed aimed at quickly and effectively achieving good colour-batching results. The arraying heuristic can be applied in the car placing stage, while the shuffling heuristic can be utilised in the car releasing stage. Computational experiments are carried out to evaluate the performance of the proposed heuristics. It is shown that the shuffling heuristic can generate comparable car retrieval sequences with an exact branch & bound approach, and the proposed arraying and shuffling heuristics can be jointly applied to achieve good colour batching in a very short time duration of less than 0.4 s in comparison with two existing batching methods. These research findings can provide good insights into the practice of colour batching in automobile manufacturing.