I attended the 2014 International Material Handling Research Colloquium in Mason, Ohio in June. We had great hosts, Intelligated , which is a company that provides intelligent automated material handling solutions. This colloquium occurs every 2 years and is one of my favorite venues to present and learn about new research. The mechanisms used to disseminate research are a Book Chapter and a poster session. I enjoy the two-way dialog that occurs in a poster session format.
The research I presented was on piece-level order-fulfillment technology selection and conducted with my Ph.D. adviser, Russ Meller, and collaborators at SSI Schaefer and the Technical University of Graz. The work was sponsored by the National Science Foundation through a Doctoral Dissertation Enhancement Project, which enabled me to live 4 months in Graz, Austria. Not only did I get to work with engineers who design distribution centers for a living, I got to experience living in another country that has amazing public transportation, fresh bread on every corner, and is the place of musicians like Mozart and Beethoven.
Our research focused on the selection of piece-level order-fulfillment technologies. To design an effective piece-level order-fulfillment strategy that meets customer requirements while minimizing costs, high-demanded SKUs may be fulfilled differently than low-demanded SKUs. Consequently, more than one order-fulfillment technology may be required due to the variability in SKU profile. For example, the Figure below provides an example solution to the Piece-Level Order-Fulfillment Technology Problem.
For this distribution center and technology characteristics, the top 1800 SKUs are fulfilled using an automated technology (like an A-Frame system) and the bottom 6200 SKUs are fulfilled using a Goods-to-Man technology. The remaining in-between SKUs are fulfilled using manual man-to-goods system.
The goals of our research were two-fold.
- First, we were interested in developing a tool that can aid in decision making associated with which technologies to select and the assignment of SKUs to these technologies.
- Second, we wanted to understand what key factors resulted in implementing manual versus automated order-fulfillment technologies and to provide insights into the use of different order-fulfillment technology strategies.
To accomplish these two goals, we developed an Integer Linear Program formulation, validated the methodology with data from industry implementations, and conducted a set of numerical experiments and statistical analysis.
The insight that I found most interesting was that if automation was used for piece-level order-fulfillment it was used for:
- The few, very fast-moving SKUs
- The many, slow-moving SKUs.
Implementing automation for your fast-moving SKUs makes sense as the investment cost in automated technologies is justified by the high velocity of these products. Not so obvious is the reason for automation to pick slow moving SKUS. The reason occurs due to the large number of slow-moving SKUs and the need for quick order-fulfillment times.
Given that slow moving SKUs make up a large number of the total SKUs (e.g., in e-commerce over 90% of a retailer’s catalog can be comprised of slow-moving SKUs ), a large amount of space is consumed by slow-moving SKUs and if they are picked in a manual system, the order picker will have to travel large distances to retrieve these items. When customers put demands on delivery times, the order-fulfillment process must be completed quickly. This means that ALL items must be fulfilled within the allotted time (not just fast-moving items). Therefore, goods-to-man systems provide cost efficiency and reduced order-fulfillment lead times for slow-moving SKUs by eliminating the significant travel costs in manual systems.
Just to be clear, our analysis found that there are many cases when a manual process is best. For example, when labor rates or the number of order lines are low, a manual piece-level fulfillment process is often recommended. If you are interested in details, a pdf version of our book chapter can be downloaded here:
Pazour, Jennifer A. and Meller, Russell D., 2014, “A Framework and Analysis to Inform the Selection of Piece-Level Order-Fulfillment Technologies,” Progress in Material Handling Research: 2014, Material Handling Institute, Charlotte, NC. (Download the PDF )