The paper "Research on Logistics Distribution Mode in Supply Chain Management Environment"

The new goal of modern logistics, especially under the mode of supply chain management.

The new goal of modern logistics, especially under the supply chain management mode, is to do more work with the same labor or cost; Using value-added services to transform warehouses from capital-intensive industries to labor-intensive industries; Reduce order fulfillment time and provide faster and more thoughtful service. However, the traditional warehousing operation management usually puts the goods in the nearest available space when they arrive or ignores the dynamic demand and changing customer demand mode of the goods, and places the goods according to years of habits and experience. The traditional layout of goods leads to slow flow, low efficiency and insufficient space utilization. Obviously, the traditional warehousing operation management can no longer meet the requirements of modern logistics.

First, a new warehouse operation and management mode-cargo space optimization management

This paper puts forward an optimal management method of warehouse space, which is closely related to "key performance indicators of warehouse", namely productivity, delivery accuracy, inventory turnover rate, storage time, order fulfillment time and storage density.

The optimal management of cargo space is used to determine the appropriate storage mode of each product specification and the space storage allocation under the appropriate storage mode. The optimal management of cargo space pursues the characteristics of different equipment and shelf types, cargo grouping, cargo space planning, built-in labor costs and other factors to achieve the best cargo space layout, which can effectively grasp the changes of goods and save costs to the maximum extent. The optimal management of cargo space can help to excavate the efficiency and cost of warehouse operation, and make key management preparations for a distribution center or warehouse under construction before operation.

Because few warehouse management systems (WMS) and computer systems can support location optimization management, about 80% of distribution centers or warehouses can't carry out correct location optimization at present. The main reason is that the basic data is insufficient, MIS resources can not be supported, and there is no correct software and method for cargo location optimization. In view of the actual needs of warehouse modernization, several powerful professional software companies have successfully developed warehouse location optimization management software. Software analysis and calculation of batch, quantity, quality control, unsalable degree, daily picking volume, daily import and export volume, etc. In the analysis, a variety of strategies are combined, such as association rules, complementary rules, compatibility rules and so on. To optimize the location of goods, thus greatly reducing the cost of goods layout.

Second, the necessary functions and implementation strategies of cargo location optimization

Whether it is commercial software or self-developed application software, location optimization must have the following basic functions: grouping goods according to built-in commodity attributes or user-defined attributes; Evaluate and suggest the best and available location for each project; Adjust the state of facilities when the classification and attributes of goods change; Mobile execution configuration required to change the warehouse from inefficient state to functional optimization state; Three-dimensional graphics or digital analysis results output.

Optimizing site selection requires a lot of original data and materials. For each product, you need to know the product code, product description, material type, storage environment, shelf life, size, weight, number of boxes per box, number of boxes per tray, etc. , even including customer order information. Once the complete original data is collected, it is particularly important to choose what kind of optimization strategy. The survey shows that applying some intuitive and taken-for-granted methods will be misleading and even lead to the opposite result. Efficient cargo location optimization strategy can increase throughput, improve labor utilization, reduce work-related injuries, make better use of space and reduce product breakage. Specifically, the following strategies can be adopted to optimize the cargo location:

1. Location optimization of periodic liquidity. According to the liquidity and the volume of goods in a certain period of time, such as year, season and month, the storage mode and storage location under the storage mode are determined.

2. Location optimization of sales volume. According to the shipments in each time period, the storage mode and space allocation are determined.

3. Optimization of unit volume position. According to the unit volume of a commodity, such as the volume of containers, pallets, boxes or turnover boxes, it is divided and integrated.

4. Location optimization of sorting density. Commodities with high sorting density should be placed in the golden area and the picking surface that is the easiest to pick.

Generally, location optimization is an optimization and simulation tool, which can run independently of WMS. Therefore, before the physical realization, it is a good practical method to use multiple strategies or alternate strategies in the virtual warehouse space to achieve satisfactory results.

Three, the eight rules of cargo location optimization calculation

It is difficult to describe the calculation of cargo location optimization with digital formula and digital model. Usually, some rules or standards are used for non-procedural operations. These rules play a role in limiting the convergence of data to the target in calculation. Most of the rules are universal. Even in an ordinary warehouse, goods are not allowed to be placed randomly or unplanned. Different distribution centers or warehouses will also formulate several special rules according to their own characteristics and the special attributes of goods. For example, distribution centers that support drug retail will store similar drugs separately to reduce the chance of wrong selection, but when storing non-drugs, they will be classified together according to the same product family. Specifically, there are eight rules for the optimal calculation of cargo location:

1. Rules based on turnover rate. That is, the goods are sorted according to the turnover rate from big to small, and then the order is divided into several segments (usually three to five segments), and the goods belonging to the same segment are classified as the same level. According to the principle of location or classified storage, the storage area is designated for each level of goods. The higher the turnover rate, the closer it should be to the entrance and exit.

2. Product association rules. This can shorten the extraction distance, reduce the fatigue of staff and simplify the inventory work. Historical order data can be used to analyze the relevance of products.

3. Law of product identity. The so-called identity principle refers to the principle that the same item is stored in the same storage position. In this way, the operator can simply be familiar with the storage location of the goods, and it is one of the basic principles to improve the productivity of the logistics center when the storage and retrieval of the same goods take the least handling time. Otherwise, when the same goods are scattered in multiple locations in the warehouse, it is not convenient to store and take out the goods, which may cause inventory difficulties and workers' mastery of the goods on the shelves.

4. Product complementarity principle. Goods with strong complementarity should also be stored nearby so that they can be quickly replaced by another commodity when they are out of stock.

5. Law of product compatibility. Products with low compatibility should not be put together to avoid damaging the quality.

6. Product size rules. In the layout of the warehouse, we also consider the unit size of the goods and the whole batch shape caused by the same group of goods, so as to supply appropriate space to meet specific requirements. Therefore, when storing articles, there must be changes in different sizes and positions to adapt to articles of different sizes and volumes. This rule can make the storage quantity and location of goods appropriate, make delivery fast, and reduce handling work and time. Once the unit size of the storage items is not considered, it may cause the storage space to be too large and waste space, or the storage space to be too small to store; Failure to consider the whole batch shape of stored items may also lead to the whole batch shape being too large to be stored in the same place.

7. Law of weight characteristics. The so-called weight characteristic principle refers to determining the high and low positions of goods stored in the cargo hold according to the different weights of goods. Generally speaking, heavier items should be placed on the ground or at a lower position on the shelf, while lighter items should be placed at a higher position on the shelf; When carrying by hand, the height below the waist is used to place heavier or larger items, and the height above the waist is used to place lighter or smaller items.

8. Law of product characteristics. The characteristics of goods not only involve the danger and corrosiveness of the goods themselves, but also may affect other goods, so they should be considered in the layout of logistics centers.

Rules can be made according to personality and characteristics of personality. For example, a drug warehouse must meet the requirements specified by GSP. When making rules, the priority between rules must also be clear.

By optimizing the position, more sorting surfaces can be realized in a small amount of space. For goods with large circulation, it is necessary to meet the needs of ergonomics and smooth and convenient channels to improve operational efficiency; For those goods with poor turnover, it is hoped that the space occupied after optimization will be small, so as to sort more kinds of goods in a small area, thus reducing the picking distance. In short, improving work efficiency and space utilization will eventually reduce costs.