What are the factors influencing warehouse process optimization? (Part 1)

Published by Ngoc Tran on

Warehouse process optimization

Warehousing is one of the key supply chain nodes, with an important role in storing, consolidating, and distributing products. However, due to the dynamic market environment and organizational change, warehouse processes have several bottlenecks. As a result, warehouse process optimization is needed to streamline warehouse processes and improve utilization. The goal of this article is to provide you with an overview of fundamental aspects that affect the optimization of warehouse processes.

#1: Warehouse layout design

A common warehouse design consists of the following areas: warehouse office, receiving, storing, packing, and shipping. To organize the location of these areas, a few factors should be considered, such as the length and width of the warehouse, the number of blocks, the number of picking aisles, the number of rack levels, the level of warehouse automation, and the position of input and output gates. Besides, the size of different areas should be carefully calculated to avoid situations like a small shipping area or unnecessary travelling time. Warehouses used to be designed with receiving and shipping gates on the same side, which often caused congestion during peak periods. To optimize this process, warehouses nowadays have receiving and shipping doors opposite to each other. This also creates a more organized way to unpack and pack various types of shipments. According to Gue et al. (2012), a Flying-V, Fishbone and Inverted-V design of cross aisles (see Figure 2) can reduce 10-20% of traveling distance.

Warehouse layout design

Figure 2. Warehouse layout design (Gue et al., 2012)

Many warehouse layouts are narrow-aisle because this increases space utilization and minimizes costs. If you’re unsure which layout applies to your warehouse, you can test these layouts by using AutoCAD, a software to create warehouse design.

#2: Order-picking routes

The order-picking process is strongly correlated with warehouse layout. Multiple research agreed that order-picking had the longest duration in warehouse activities, among receiving, storage, packing, and shipping. Some common wastes during this process are (1) congestion due to waiting time of a picker queuing to enter the aisles, (2) shortage of pickers due to holidays or illness, (3) delays of orders including multiple items, etc. Petersen (1997) presented five routing strategies applicable to the mezzanine warehouse (see Figure 3), consisting of:

  • The S-Shape strategy: illustrates the route to completely travel across all aisles containing the order (required products).
  • The Return strategy: defines that a picker enters the aisles storing the required products but always returns to the entrance of this aisle.
  • The Mid-point strategy: determines a picker to pass through each aisle at most to the middle of the aisle and then returns to the entrance of the aisle he entered.
  • The Largest Gap strategy: is quite similar to the Mid-point strategy, but it sets a point that should not be traveled through based on the largest gap between two products in the aisle.
  • The Combined strategy: combines the S-Shape and Return strategies by selecting the pick aisle entry based on a picker’s current location. After all required products in one aisle are picked, the strategy decides to either complete this aisle or enter the other entrance of another aisle, or return to the initial entrance.
Order picking strategies

Figure 3. Order-picking strategies (Petersen, 1997)

Thanks to technological breakthroughs, the optimal route can be determined by applying dynamic programming called Picking Path Optimization Algorithms. Other effective solutions to streamline this process are augmented reality, robotics, Lean Six Sigma (especially the 8 Wastes of Lean), etc.

#3: Storage policies

Storing process includes the task of selecting storage locations to put a received product into storage. This process also depends on the warehouse layout in terms of several storage racks, blocks, and storage locations within the warehouse. There are a few distinct storage strategies that have been applied in practice, as follows.

  • The closest open location storage: selects the first empty storage location the employee enters. As a result, utilization is higher in the neighborhood of this rack compared with the farther ones.
  • The rank-based storage: classifies products based on several criteria such as popularity, fast-and-slow moving, volume, pick density, size, etc.
  • The class-based storage: defines groups of products into classes, location of classes within the warehouse. ABC classification is an example for this strategy. Dangerous goods like vehicle battery, chemical are strictly stored in a separated area and require special handling.
  • The family group storage: proposes to store products that often need to be picked in combination because of their relations or similarities (e.g., same country group).
  • The random storage: offers no reserve locations for incoming products but rather allocates them randomly to unoccupied racks. The advantage is flexibility while the difficulty to organize is the disadvantage.
  • The dedicated storage: is opposite to the random strategy, indicating that each product has been assigned to a specific storage area. Little changes can be made in the warehouse, so it is more vulnerable to dynamic circumstances, and thus utilization may be low.

As you can see, so many different techniques can be used, adapted, and combined to optimize distinct warehouse processes. Subtle changes in the warehouse design and workflows can lead to noticeable enhancement in company performance, for example, a reduction in operations costs and a rise in employee productivity and satisfaction.

What are other elements affecting warehouse process optimization? Think about it and we will discuss it together in the next post. Stay tuned!

Thank you for reading and please share if you find it useful!

Recommended reading:

Živičnjaka, M. et al. (2022) Case-study analysis of warehouse process optimization

Lesch, V. et al. (2021) A Case Study on Optimization of Warehouses

America, K., (2020) The effects if storage utilization on warehouse efficiency and operational costs

Karasek, J., (2013) An overview of warehouse optimization

Image source: https://www.westgateuk.co.uk/news/internet-shopping-causes-boom-in-the-warehouse-sector/

Series Warehouse process optimization


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