The topic of robotic, or automatic, mixed pallet building has come up quite a bit recently, so I thought I'd share some of the benefits and challenges that go along with it. To give you some background, a few years ago companies started building rainbow packs, which are basically a box or bag of products that contain smaller quantities of different flavors or product lines. This allows consumers to sample a variety of items without buying large quantities of each.

As an example, you might go to the grocery store and pick up some snack bags of chips for your kids' lunches. Instead of picking up a big bag of BBQ chips, you can pick up a variety pack containing multiple, snack-size bags in different flavors-- a few BBQ, a few sour cream and onion, and a few salt and vinegar. Another example is flavored water. Instead of buying a tray with 12 bottles of cranberry flavored water, you can buy a tray that has 4 cranberry, 4 blackberry, and 4 cherry flavored bottles. This has advantages for both the manufacturer and the consumer.

The manufacturer can choose to package some high-selling items with some low-selling items to move more products. Consumers get to sample new flavors because they don't have to commit to buying full cases of them. It's a win-win, but the challenges come from getting those different products into the same packaging. Typically, one flavor of product is packaged in bulk, meaning that bulk quantity has to be unpackaged, mixed up with other product flavors in a rainbow-pack configuration, and repackaged before it's sent to the grocery store.

So what does all of that have to do with robotic mixed pallet building? Well, this concept of a rainbow pack actually stemmed from the advent of mixed pallet building first used by the material handling and logistics industries. These industries realized that if they could repackage bulk products into individually-packaged, single-serving variety packs, then they could also solve a warehousing issue. The issue is that products come packaged in large, bulk cases and need to get to store shelves in individual containers. For instance, the grocery store might only have room on its shelves for 30 bottles of detergent, but when detergent is shipped from the manufacturer to the distribution center, there are 40 cases on a pallet and 4 bottles in each case for a total of 160 bottles on each pallet.

Typically, this is way more than the store needs or has room for, so the warehouse has to break down the pallet and place just 8 of those cases on a new pallet to ship to the store. However, the challenge is that distributors don't want to ship a pallet with just 8 cases on it. They want to fill the pallet with other products the store needs, so the cost of shipping is reduced. This leads to a lot of labor being used to break down additional bulk pallets and build complete mixed pallets with what the store actually needs. It is this labor-intensive process of breaking down and re-building pallets that makes robotic mixed palletizing so appealing.

Benefits of a robotic mixed pallet building system:

• Reduce labor
• Reduce workers compensation claims
• Save shipping costs by building more complete pallets
• Reduce errors in shipping the wrong products
• Reduce damaged products

Challenges of a mixed pallet building system:

• More data to keep track of for the warehouse management system
• End of Arm Tool (EoAT) has to be able to pick up many different products
• Many pick locations requires a lot of real estate
• Must keep track of case sizes, pallet sizes, case weights, and figure out the best way to build a pallet with large heavy cases on the bottom and smaller lighter cases on top.

Taking both the benefits and challenges into account, most companies now believe it is well worth investing in this technology because the amount of savings typically far outweighs any challenges the system might present.

What do you think? Do you think this technology would benefit your company? Maybe, you've already invested in a system like this. If so, feel free to post your comments or questions.

Author: Jason Nowak