FMCG distributors wanted to change their management methods and improve efficiency in the warehouse management process, so they re-planned the entire business process. First, they re-planned the shelf placement, then from printing orders to order allocation, and then to each pick

FMCG dealer wanted to change the management method and improve efficiency in the warehouse management process, so he re-planned the entire business process. First, he re-planned the shelf placement, and then from printing orders to order allocation, and then to each picking. The employees are responsible for their respective channels, and all of them have been re-optimized. Some use the warehouse management system, and some still rely on traditional management methods.

But many companies tend to ignore one aspect, which is the planning of picking paths. Picking path planning is very important, because the planned route can ensure that pickers do not go back when working, saving the picking time of each order and improving Overall picking efficiency.

If the dealer does not use the warehouse management system , the manual picking path planning is based on the cargo location information. The geometric order of the goods can be distinguished according to the location of the goods, so the path can also be sorted based on the cargo location number. Planning rules (i.e., rules for sorting cargo locations) are used to obtain the picking path.

When the same product is in stock in multiple locations, when assigning picking tasks, all possible picking paths are often compared (provided that there is sufficient inventory in all locations), and then the optimal path is selected. .

And when the inventory quantity on some storage locations is insufficient, the calculation logic will be more complicated. Regarding path optimization, we have mentioned it many times. Here is a brief summary of the relevant directions that need to be optimized:

Reasonable wave plan

When getting many orders, how to quickly disperse all the things on the orders? Comprehensive summarization of items belonging to the same category is a time-consuming and labor-intensive task. In addition, consumers now have more personalized needs, and the correlation between orders has great fluctuations, especially in the retail industry, which will cause a lot of workload for batch picking of goods.

Advanced WMS systems, such as Guanyunchang The establishment of wave rules in WMS systems can solve this problem. When the order is output, the order goods are comprehensively processed in the system. According to certain rules, multiple orders are treated as one batch and the goods are comprehensively sorted and sorted in batches. The establishment of wave rules can optimize picking paths and improve picking efficiency.

gives an example: batch orders with the same category and the same quantity are selected first; batch orders with the same category but inconsistent quantities are selected first, etc.

Appropriate picking methods

Choose appropriate picking methods according to different product categories, such as picking while sorting, picking first and then sorting, batch picking, etc.

Moderate picking tools

In addition, there is another easily overlooked but very important factor, which is the picking tool. The warehouse needs to allocate appropriate picking containers according to the picking order. If the container is too large, it will cause inconvenience in implementation, and if the picking Insufficient container capacity will result in extra work, so a moderate picking container is essential.

Laikenqiqihui dealer's exclusive warehouse management system provides enterprises with specialized warehouse planning and generates cargo location codes for each commodity location. After receiving the order, the system will automatically upload the order in the order of the location numbers. The goods are sorted to generate the picking list of the optimal path. The pickers sort according to the order of the picking list. They take an "S"-shaped route in the warehouse without going back, which greatly improves the picking efficiency.