A framework for interactive work design based on motion tracking, simulation, and analysis

• Published in: Human factors and ergonomics in manufacturing & service industries Vol. 20; no. 4; pp. 339 - 352
• Main Authors: Ma, Liang, Zhang, Wei, Fu, Huanzhang, Guo, Yang, Chablat, Damien, Bennis, Fouad, Sawanoi, Akihiro, Fugiwara, Naoyuki
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01-07-2010; Wiley Subscription Services, Inc
• Subjects: Digital human modeling; Digital mock-up; Ergonomics; Maynard Operation Sequence Technique; Methods-time measurement; Motion control; Motion tracking; Motion-time study; Position tracking; Simulation; Target recognition; Time & motion studies; Work simulation; Work study
• ISSN: 1090-8471; 1520-6564
• DOI: 10.1002/hfm.20178

Because of the flexibility and adaptability of humans, manual handling work is still important in industry, especially in assembly and maintenance work. Well‐designed work operation can improve work efficiency and quality; enhance safety, and lower cost. Most traditional methods for work system analysis need physical mock‐ups and are time‐consuming. Digital mock‐up (DMU) and digital human modeling (DHM) techniques have been developed to assist ergonomic design and evaluation for a specific worker population (e.g., 95 percentile); however, the operation adaptability and adjustability for a specific individual are not considered enough. In this study, a new framework based on motion‐tracking technique and digital human simulation technique is proposed for motion–time analysis of manual operations. A motion‐tracking system is used to track a worker's operation while he/she is conducting a manual handling task. The motion data are transferred to a simulation computer for real‐time digital human simulation. The data are also used for motion type recognition and analysis either online or offline for objective work efficiency evaluation and subjective work task evaluation. Methods for automatic motion recognition and analysis are presented. Constraints and limitations of the proposed method are discussed. © 2010 Wiley Periodicals, Inc.