Extracting Distinctive Motion Patterns in Nut-Tightening and Nut-Loosening Tasks Based on Joint Angle and Principal Component Analysis

To improve training for manual assembly and disassembly tasks, it is essential to characterize changes in workers’ movements with task repetition. This study analyzed repeated nut-tightening and nut-loosening tasks using optical motion capture data collected from five workers. Workload-related postures were assessed using rapid upper limb assessment (RULA), and movement coordination was examined through principal component analysis (PCA) of six joint angles. The results indicated that the RULA grand score varied little across trials and lacked sufficient sensitivity to detect subtle changes associated with task repetition. By contrast, joint-angle statistics and PCA revealed evidence of both shared and task-specific changes in movement patterns. In particular, PCA indicated a common pattern of adaptation across tasks, alongside distinct changes in coordination during nut-tightening and nut-loosening. These findings suggest that multivariate motion analysis may inform proficiency assessment and the design of task-specific training for manual assembly and disassembly work.