Data-driven analysis and human-centric assignment for manual assembly production lines

Abstract

Flow production-oriented assembly production lines have become crucial in various industries with the development of Industry 4.0, leading to mass customization and personalized production. In addition, Industry 5.0 has emerged, which emphasizes human-centric design. Manual assembly production line balancing, considering worker ergonomics, has also gained substantial attention. This study aims to solve the line balancing problem through combination optimization considering ergonomic risks based on many studies on human-centric production lines. A framework of the data-driven analysis and assignment for manual assembly production lines is proposed herein. The proposed framework defines and analyzes the process difficulty and the worker’s process ability and assigns a skilled worker to a process through the presented heuristic algorithm. To demonstrate the applicability of the proposed framework, a case study was conducted on an experiment imitating a home appliance assembly line in the United States. This paper provides empirical evidence of a framework aimed at realizing human-centric business objectives through case study. Future studies on the data-driven analysis and assignment for manual assembly production lines are anticipated to exhibit a range of variations such as line balancing problems and evaluation methods.