AI-assisted Monitoring of Human-centered Assembly: A Comprehensive Review

Abstract

Detection and localization of activities in a human-centric manufacturing assembly operation will help improve manufacturing process optimization. Through the human-in-loop approach, the step time and cycle time of the manufacturing assemblies can be continuously monitored thereby identifying bottlenecks and updating lead times instantaneously. Autonomous and continuous monitoring can also enable the detection of any anomalies in the assembly operation as they occur. Several studies have been conducted that aim to detect and localize human actions, but they mostly exist in the domain of healthcare, video understanding, etc. The work on detection and localization of actions in a manufacturing assembly operation is limited. Hence, in this work, we aim to review the process of human action detection and localization in the context of manufacturing assemblies. We aim to provide a holistic review that covers the current state-of-the-art approaches in human activity detection across different problem domains and explore the prospective of applying them to manufacturing assemblies. Additionally, we also aim to provide a complete review of the current state of research in human-centric assembly operation monitoring and explore prospective future research directions.