Optimizing Makespan and Ergonomics in Integrating Collaborative Robots Into Manufacturing Processes

Abstract

As collaborative robots begin to appear on factory floors, there is a need to consider how these robots can best help their human partners. In this paper, we propose an optimization framework that generates task assignments and schedules for a human–robot team with the goal of improving both time and ergonomics and demonstrate its use in six real-world manufacturing processes that are currently performed manually. Using the strain index method to quantify human physical stress, we create a set of solutions with assigned priorities on each goal. The resulting schedules provide engineers with insight into selecting the appropriate level of compromise and integrating the robot in a way that best fits the needs of an individual process. Note to Practitioners —Collaborative robots promise many advantages on the shop and factory floor, including low-cost automation and flexibility in small-batch production. Using this technology requires engineers to redesign tasks that are currently performed by human workers to effectively involve human and robot workers. However, existing quantitative methods for scheduling and allocating tasks to multiple workers do not consider factors, such as differences in skill between human and robot workers or the differential ergonomic impact of tasks on workers. We propose a method to analyze how the inclusion of a collaborative robot in an existing process might affect the makespan of the task and the physical strain the task places on the human worker. The method enables the engineer to prioritize and weigh makespan and worker ergonomics in creating schedules and inspect the resulting task schedules. Using this method, engineers can determine how the addition of a collaborative robot might improve makespan and/or reduce job risk and potential for occupational hazard for human workers, particularly in tasks that involve high physical strain. We apply our method to six real-world tasks from various industries to demonstrate its use and discuss its practical limitations. In our future work, we plan to develop a software tool that will assist engineers in the use of our method.