Optimization of Storage Categorization : A simulation based study of how categorization strategies affect the order fulfillment time in a multi-picker warehouse

The most costly and labor-intensive activity for almost every warehouse is the order picking process and a key challenge for manufacturing companies is to store parts in an efficient way. Therefore, to minimize the order retrieval time when picking from a storage, the need of a sufficient storage categorization strategy becomes vital. One of the logistics centers at Scania in Södertälje stores parts that will be transported to the chassis assembly and the assembly of gearboxes and axles when needed in the production. In one of the storage areas at the logistics center, namely the PS storage, the forklift drivers picking from the storage have experienced congestion in the storage aisles and that it might be possible to reduce the order fulfillment time when picking the orders. This master thesis aims to investigate the possibility of optimizing the picking process in the PS storage, with respect to the order fulfillment time for the forklift drivers, with categorization of the goods. This has been analyzed with a heuristic optimization approach and with the use of a discrete event simulation model, where different categorization strategies have been applied on the storage and compared to the current state. By categorizing the goods in the PS storage, a reduction of the order fulfillment time can be done of around 4% - 5% compared to the current state with all tested categorization strategies. The strategy which has been shown to give the largest improvement is by categorizing the parts in the storage according to their final delivery address at the production line, which would reduce the order fulfillment time by 5.03% compared to the current state. With this categorization method, parts that are picked on the same route are located close to each other