Applying modern robotics technologies to demand prediction and production management in the quick-service restaurant sector

Breffni M. Noone, R. Craig Coulter

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

Given the twin objectives of ensuring consistent quality and controlling costs, quick-service restaurants have been in the forefront of automating their operations whenever possible. This article explores a novel approach to achieving these two objectives by using modern robotics technologies to improve operations. Instead of applying robotics technology for direct labor replacement, robotics can augment workers' cognitive capacity. This alternative application of robotics technologies encompasses two key components: (1) robotic sensing for demand prediction and (2) robotic planning for production management. Using the example of Zaxby's Franchising Inc., this article explains the improvements possible with modern robotics technologies and the challenges of implementing it. Unusual for quick-service, Zaxby's uses a fresh, cook-to-order concept, which resulted in backlogs during busy times. Zaxby's robotics application substantially reduced both service times and food waste. The system tracks customer arrivals, starts the cooking process as customers arrive, and then gives employees specific directions to expedite cooking and service, so that wait times have been reduced. Developing the algorithms needed for robotic systems gives corporate operators the opportunity to analyze their operating systems, resolve inconsistencies, and provide for clear performance assessment.

Original languageEnglish (US)
Pages (from-to)122-133
Number of pages12
JournalCornell Hospitality Quarterly
Volume53
Issue number2
DOIs
StatePublished - May 2012

All Science Journal Classification (ASJC) codes

  • Tourism, Leisure and Hospitality Management

Fingerprint

Dive into the research topics of 'Applying modern robotics technologies to demand prediction and production management in the quick-service restaurant sector'. Together they form a unique fingerprint.

Cite this