Increasing efficiency is something most warehouse managers are striving to do. There are several ways one may increase efficiency in a warehouse, in this post we will present some inspirational ways of analyzing the order picking activity and how to apply it in the search for a fitting solution.

Breaking down the process

When seeking to increase efficiency one initially have to look at all processes that occur in the day to day warehouse work and what percentage of all time is spent on different activities. Order picking is often reported to be the most time-consuming and critical activity in a warehouse (Weaver, Baumann, Starner, Iben, & Lawo, 2010), but packing, restocking, and several other activities are also performed.

Looking closer at the order picking time and using it as an example of this post, it can be divided into four interleaved tasks, as done by Schwerdtfeger and colleagues (2009) in their paper. The order picking time includes base time, way time, picking time and dead time.

  • The base time includes all tasks at the beginning and the end of one order (e.g. login at the system, pick-up and delivery of the collecting unit or the paper list).

  • The way time is the time the user physically moves through the storage area.

  • The picking time consists of actually grabbing the item with the following delivery in the collecting unit or on a conveyor.

  • The dead time includes the search for information and the human information processing and all process steps that are not necessary for the real task (e.g. open the packages).

Pinpointing the area

Breaking down all the different activities performed in a warehouse like above can help in pinpointing where there may be time to save and potential changes have the biggest impact.

Calculations on performance, such as picked order lines per hour, can be done using the order picking time, as well as the occurrence of errors and other discrepancies in the order picking time.

If the amount of picked order lines per hour is low, it might be due to an issue in any of the above tasks, and it will be revealed when the process is broken down into the interleaved tasks. In case the error rate is high the problem most likely affects the base time. Identifying what area in the picking process that creates performance loss will help in the search for a fitting solution.

Superhuman

In the article by Schwerdtfeger and colleagues (2009) they make a discrepancy between coarse and fine navigation. They define fine navigation as locating an items shelf position, while coarse navigation is referred to as finding the actual shelf.

Coarse navigation falls in the category of way time, since it consists mostly of travelling to the right shelf, locating it during the movement. Fine navigation falls in the category of dead time since it includes cognitive processes such as search of information and information processing.

The authors of the paper state that the coarse navigation is manageable for all workers, while guidance in the fine navigation has the ability to increase the performance. This statement will be the ground for our example case in this post.

Choosing the right solution

As described in our previous post, motivation is utterly important in all work performed by humans. But enabling the work to be performed in a good manner is also important, and that means increasing the ability.

“To increase the ability to perform a task we can apply simplicity factors. These include training, tools and making the target behavior easier to perform. […] the best way to increase ability is by making the behavior easier to do […].”

In our example, adding simplicity factors to support fine navigation has a big potential in improving order picking time. To improve performance, we need to make it easier to perform the fine navigation.

Tools may assist in making the behavior easier to do, but not all tools have the same prerequisites to assist in our goal. The tool in itself is not enough, the simplicity in handling the tool is a big part of the tool’s success.

Below is a list containing some of the most available tools on the market today. Their effect is partly dependent on factors such as what kind of goods that are to be picked, warehouse layout, and others. They are also partly dependent on the design of the tool, and how it assists the user in their work. In relation to our example, we will mainly look at their potential in lowering the ability to perform fine navigation.

  • Automated storage system/vertical storage lift
  • Tablet
  • Handheld scanners/Mobile data terminals
  • Pick by Voice
  • Pick by Vision
  • Pick by Light

Paper picking lists, mobile data terminals, and tablets all give the picker information in the same way, written and visually, thereby leaving the picker to imprint the information in their short term memory to be able to identify the location to pick the item from. Pick by voice uses another sense, hearing, but put the same strain on the picker due to the load on their short term memory. These tools do not assist in lowering the ability to perform fine navigation and will thereby not improve the order picking time in our example.

Pick by light and automated storage systems does not put the same amount of load on the pickers memory, due to their ability to guide the picker to the correct location of the item to pick. The tools do not require the picker to remember the same amount of information during the time they search for the items shelf position. The tools will thereby not be as demanding for their mental capacity.

Pick by vision bridges the gap between picking tools where the picker needs to keep all information in their memory and picking tools where the picker is guided to the correct item placement. In the future, when the vision picking technology has matured and developed to be more advanced, there will be systems that reach the same level of guidance as pick by light, together with additional advantages that is not supported by pick by light. Those systems will both be more flexible and bring a broader range of support to their users.

Conclusion

Following the above process in analyzing the problem area of a warehouse, we have managed to narrow the possible solutions down to two or three options, based on the example problem. When choosing between the options other criteria such as economy, type of goods, picking speed and warehouse layout can be assessed to pin down the best option for the current warehouse. The available picking solutions on the market all bring different advantages and drawbacks, the choice thereby has to be done in relation to current circumstances and set goals.

References:

Schwerdtfeger, B., Reif, R., Gunthner, W. A., Klinker, G., Hamacher, D., Schega, L., Böckelmann, I., Doil, F., & Tumler, J. (2009). Pick-by-Vision: A first stress test. In 2009 8th IEEE International Symposium on Mixed and Augmented Reality (pp. 115-124). IEEE.

Weaver, K. A., Baumann, H., Starner, T., Iben, H., & Lawo, M. (2010). An empirical task analysis of warehouse order picking using head-mounted displays. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1695-1704). ACM.