Human-Centered Task Allocation: A Simulation-Based Case Study

Abstract

This study investigates human-centered task allocation, focusing on factors such as cognitive load, physical demand, and ergonomics. A discrete event simulator was developed to validate the task allocation results of the Q-learning optimization. The simulation evaluates the process and resulting task allocation plan based on predefined human-centered objectives. Through a case study on remanufacturing, we demonstrate how to optimize the coordination of a robotic arm and two human operators to reduce overall workforce requirements. The simulation allows for the analysis of operators' cognitive and physical workloads over time, enabling exploration of not only typical time balances but also cognitive and physical burdens.