Starting Semester: Spring 2022 Assigned: Yes Location: Atlanta
Papa John's International
Client Profile
Papa John's International, Inc. (NASDAQ: PZZA) opened its doors in 1984 with one goal in mind: BETTER INGREDIENTS. BETTER PIZZA. Papa John's believes that using high quality ingredients leads to superior quality pizzas. Its original dough is made of only six ingredients and is fresh, never frozen. It was the first national pizza delivery chain to announce the removal of artificial flavors and synthetic colors from its entire food menu. Papa John's also has a history of digital leadership and technology firsts in our industry - e.g. we were first to offer online ordering at all U.S. delivery restaurants, first to offer a systemwide mobile phone ordering experience, first to offer an animated, customizable pizza builder, first to launch a nationwide digital rewards loyalty program, and more. We were first in the pizza industry to reach 50% of sales via digital and e-commerce channels, and the first to achieve $1 billion in digital sales. Papa John's is the world's third-largest pizza delivery company with more than 5,500 restaurants in 49 countries and territories as of June 28, 2021.
Project Description
Project Summary: * Design improvements to the existing make line * Design and implement hands-free interface that improves on-the-job learning and/or guides the pizza maker through ingredient sequence and amounts (e.g. as the first topping is added and meets the target weight, the next topping instruction is shown) Possible implementations or extensions: Use pressure / weight sensors to detect when toppings are added, timing, and weight vs. spec Utilize analytics to provide reports showing statistical breakdown of timing and accuracy Optimizations to the Makeline to improve: Reduction in food waste Accuracy of made order Reduction of make time Employee satisfaction / onboarding speed Expected outcomes: Understand the complexity and costs of building such a system More precisely understand potential achievable benefits (reduced food waste / costs, improved order accuracy, makeline timing optimization) Potential technologies involved: Mechanical engineering for weight / pressure sensor(s) and inclusion in Make line Data storage Imaging Content Management Machine Learning Analytics Potential Materials needed: Pressure / weight sensors Back-end systems to support data storage and applications Access to a real make-line for experimentation Pizza ingredients Haptic or Motion sensors Audio Visual processing Displays Possible long-term extensions: Automation of topping placement Step-by-step instructions using non-tactile gestures (or possibly no gestures, such as audible commands)
Skills
Cross-disciplinary skills are encouraged, per the project description
