Optimize Cooler Restocking

Overview

Our group was tasked with discovering a way to optimize the cooler restocking process at all Sheetz locations by minimizing total labor time spent in the cooler. Presently, Sheetz invests an average of 30 hours a week per store restocking their coolers. The company estimates this costs $15,000,000 annually.

Objectives

The objective of this project was very clear: find a way to minimize labor in the coolers. We were given a broad scope, but clear instructions. The project needed to be cost effective, safe, adaptable across stores, and serviceable.

Approach

– The team gathered the customer needs by holding weekly status meetings, attending store visits, and watching the cooler restocking process.
– After meeting with the Sheetz team, we split into three groups: Automated solutions, Semi-Automated solutions, and Optimized solutions. This was Phase 1 and 2.
– We then Alpha Prototyped the best solutions from each phase using feasibility studies. These studies tested for time, cost, and safety.
– After the first phases were complete, the team came together and was able to combine the best solutions into one.
– This solution was also tested using feasibility studies, more specifically an in-depth financial analysis and a finite element analysis (FEA).
– Multiple CAD models were created, one for the C-Channels, the shelving, and the organization of the backroom.
– Other supporting documents included a full app-layout and multiple SOP (Standard Operating Procedure) documents.
– We did fabricate multiple prototypes (or iterations) of the C-Channels, the SOPs, and the APP Layout. Additionally, a prototype for the sensors was created.
– Testing was preformed by doing the feasibility studies mentioned above, as well as physically testing our manual prototype using the stocking channels given to us by our sponsor.
– Our model was validated through financial analysis, comments from our sponsor, and strength testing.

Outcomes

The team ran ROI calculations taking into account the cost of sensors, warehouse technology, channels, and other associated expenses. We estimated the cost of labor within a 15-year time period (the lifespan of a store) to be $225,000,000. Our solution would cost roughly $13,000,000. Even if our solution only produced a 10% reduction in labor, just three hours faster each week, the company would see the ROI within eight years, well within the 15-year time period.