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A colour-batching problem using selectivity banks in automobile paint shops

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.