This team partnered with Shaw Industries to revamp their reverse logistics process for returns. They redistributed the work from one central facility to 29 regional distribution facilities around the country and equipped them with an extensive desktop application that iterates through possible return decisions and returns both the top five feasible options and the costs associated with them. Through rerouting returns to be more cost-effective, as well as standardizing processes and reducing holding time, this team saved the company over $740,000/year.
Cycle-Ops partnered with Relay Bike Share to reduce the number of understock events. Understock events occur when a user attempts to rent a bike but finds a station is empty. To minimize understock events, we solved an optimization model using Python Code, which was given to Relay as a decision tool. When our solution is implemented, Relay will see an 84 percent reduction in understock events. As a result, Relay can make, on average, $27,300 in additional yearly revenue.
The goal of this project was to increase the throughput of Textron’s TUG tractor manufacturing line. The team used an optimization model to rebalance the manufacturing line, verified this output in a simulation model, and synchronized the workers on the line through Lean tools. If Textron implements this design, the daily tractor throughput will increase by 50 percent, enabling them to meet demand and capitalize on their backlog to increase yearly sales by $20 million.
This Senior Design team worked with FLEETCOR to modernize the company’s antiquated sales process of cold-calling customers. They applied data-driven IE techniques and developed an expected revenue-based lead-prioritization decision support tool employing machine learning models. The team projected the impact of their work would lead to an increase of 71 percent in new customer revenue
The Bacon ‘n’ Eggs team partnered with client Waffle House to identify areas in which their maintenance handling system could be improved. The goal of the project was to help Waffle House uphold their commitment to serving customers 24/7/365 by reducing the frequency, duration, and impact of breakdowns inside units.
The Mercedes-Benz Stadium team focused on the ways the food and beverage process affects the fan experience at the Mercedes-Benz Stadium. Their work resulted in a 50 percent reduction in fan wait time throughout the stadium.
The Emory Quality Metrics team created a trusted performance benchmarking system. This solution will allow Emory Healthcare to assess its surgeons’ performances and more easily identify parts of their system where they can add value either by improving quality of care or decreasing excess costs.
The Georgia Pacific Manufacturing team reduced the board manufacturing defect rate by 27% by optimizing SKU sequences and lowered inventory age for a total cost savings of over $1 million.
The Home Depot team provided in-store associates the resources to recommend products to customers more effectively. The recommendations will be derived from real transactional data by leveraging machine learning algorithms in conjunction with consumer behavior.
The UPS Crowd Source team implemented an "uber" like solution, optimized delivery routes to help UPS save $14 million over the busy holiday season.