  Due to the flexibility and adaptability of human, manual handling work is
still very important in industry, especially for 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-up and are time consuming. Digital mockup (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 work. The
motion data is transferred to a simulation computer for real time digital human
simulation. The data is 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.
