Supply Chain Digest and Distribution Digest recently completed a large survey of order fulfillment operations and found (among many other things that we will publish soon) that 72% of respondents are discrete order picking using a combination of pallet jacks and order picker trucks. This confirms survey results done by other industry sources that show non-conveyorized manual order picking methods are commonly used in both large and small DCs throughout the supply chain.

During phone interviews with several of these companies, we found that simple rules for routing order pickers, like “traverse every aisle with pick locations entirely” were being used with volume-based storage assignment methods. For many of these operations, better routing and storage strategies are available.

Because travel time can account for 50% or more of total order picking time, choosing the right routing strategy becomes even more important, especially if some type of storage assignment criteria is involved. Routing and storage strategies can each individually reduce travel distances of order pickers, but a good combination of both is even more effective.

Still, the efficiency of the order picking process partly depends on factors that are difficult to change, such as building configuration, existing storage and picking systems (racks), and order picking equipment (pallet jacks, order picking trucks, pick carts, etc.). Therefore, the objective is to reduce the time needed for picking an order through improved efficiency of the order picking strategy without changing layout or material handling equipment – not an easy task given the huge number of possibilities.

So, this got us thinking about how companies can optimize their manual order picking route and storage strategy.

Common Methods for Routing Order Pickers

Total picking time can be roughly divided into time for driving or walking to locations (travel time), time for picking the products, and time for remaining activities such as obtaining a picklist and an empty pick carrier. By reducing the travel distances, and therefore travel times, a significant reduction in the total order picking time can be achieved.

There are several ways to reduce travel distances in the order picking process. One way is to optimize order picking routes. Given that the order picker has to collect a number of products in specified quantities at known locations, the question is then in what sequence should the order picker visit these locations in order to minimize the distance traveled?

The following describes six logical order picking route strategies (for example layouts of each, see the diagrams that follow the list):

1. The Transversal strategy

The simplest way to route order pickers is by using the transversal (also called S-shape strategy). Any aisle containing at least one item is traversed through the entire length. Aisles with no picks are skipped. After picking the last item, the order picker returns to the front aisle.

This method is likely to be the most frequently used routing strategy. It is especially useful if order picking equipment is used that cannot easily change directions within an aisle. Also it is one of the better strategies if equipment is used that requires much time for changing aisles.

2. Return strategy

With the return strategy, the aisles are always entered from the front and left on the same side after picking the items in this aisle.

This method is only to be preferred if there is only one possibility for changing aisles in the warehouse. If the warehouse has two (front and back) or more possibilities for changing aisles, then this method will be outperformed by nearly all other methods listed.

3. Midpoint strategy

For this method, the warehouse is essentially divided into two halves. Picks in the front half are accessed from the front aisle, and picks in the back half are accessed from the back aisle. Only the first and the last aisle are traversed entirely.

This method could be a good alternative to transversal as long as there is, on average, only one pick per aisle. However, the Largest Gap strategy (see #4 below) always has a better performance than Midpoint and is therefore to be preferred. The Midpoint does offer a simple approach that is easy to implement.

4. Largest Gap strategy

The picker enters the first aisle and traverses this aisle to the back of the warehouse. Each subsequent aisle is entered as far as the ‘largest gap’ and left from the same side that it was entered. A gap represents the distance between any two adjacent items, or between a cross aisle and the nearest item.

The last aisle is traversed entirely and the picker returns to the depot along the front, entering again each aisle up to the largest gap. Thus, the largest gap is the part of the aisle that is not traversed.

5. Composite/Combined strategy

This routing strategy combines features of the Transversal and Return strategies.

This method decides for each aisle individually whether it is shorter to traverse it entirely or to make a return route. With this method, there is a kind of dynamic programming component which, in a way, makes it possible to look one aisle ahead. This method may be a good candidate to use for routing with volume-based storage policies.

6. Optimal routing

All of the strategies listed above restrict the possibilities to create an optimum route. For example, the Transversal strategy forces order pickers to traverse each aisle entirely.

To obtain the shortest route possible, you need a strategy that is capable of considering all possibilities for travelling in and between aisles. The Rotterdam School of Management developed just such a simulation program, which is available on the Internet free of charge. The program appears to be relatively user-friendly and is capable of comparing numerous combinations of rectangular warehouse layouts, routing strategies, and storage policies. It can be found at http://www.fbk.eur.nl/OZ/LOGISTICA/. Most settings can be altered, often with a single mouse click.

ORDER PICKING ROUTE DIAGRAMS

Storage Assignment Methods

The most common methods of storage assignment are random, volume-based, and class-based. Random storage is the easiest to use as items are just assigned to any open storage location. Volume-based storage involves ranking all of the items by demand and then assigning storage locations based on this ranking.

Since warehouse assortment changes in variety and demand levels, volume-based storage may be difficult to implement, making class-based storage a more practical alternative. Class-based storage is essentially a combination of random and volume-based storage. Items are divided into storage classes based on demand, but the items are assigned random storage locations within their class storage area.

Much more detailed information on order picking efficiency with routing and storage policies can be found in a 17-page comprehensive report available through the Material Handling Industry of America (MHIA) at: www.mhia.org - click on Learning Center and enter keywords – Order Picking 401 – then click search.

All of the non-automated warehousing and distribution companies that SCDigest recently interviewed, who depend exclusively on manual picking methods, rely on WMS and auto ID technologies to drive down cost while trying to maximize throughput. Still, most admit that they are searching for, and experimenting with, better ways to fine tune their picking/storage strategies. They know all too well that reducing order pickers walk or drive time, along with utilizing effective strategies for assigning products to storage locations, is crucial to improving their productivity and throughput numbers.

Agree or disgree with Holste's perspective? What would you add? Let us know your thoughts for publication in the SCDigest newsletter Feedback section, and on the website. Upon request, comments will be posted with the respondent's name or company withheld.

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