Abstract
Upper limb and back injuries are common musculoskeletal disorders among automotive assembly operators which can reduce operators’ ability and increase industries costs. Characterizing and quantifying movements and postures of the upper limb and back can discriminate the workload between assembly tasks in the real settings. Characterizing and developing a pattern of movements help to understand the function of body parts and to investigate the reasons of injuries. The aim of this study was, therefore, to characterize upper arm and back movements in the automotive assembly tasks, using accelerometer data and Exposure Variation Analysis. One workstation of a truck assembly plant including various assembly tasks was selected for data collection. Two experienced operators who assembled Selective catalytic reduction (SCR) tank on trucks during the 11 min cycle time were included as participants of the study. Acceleration data were registered by the triaxial accelerometers placed simultaneously on the right/left upper arms and lower back of the participants. Video-recordings of operators’ activity were performed and synchronized with the acceleration data. The EVA method was used to plot movements of the upper arms and lower back. The pattern of movements for the arms and back was plotted for various assembly tasks such as tightening, material handling, and inserting (with force). The EVA showed the difference between assembly tasks in term of frequency and intensity which can be used to distinguish the tasks causing either upper limb disorders (such as rotator cuff syndrome) or low back pain. Furthermore, transition of accelerometer data in a way that provide meaningful and understandable information has been a challenge in the quantification of workload, and the EVA can illustrate and characterize a pattern of movements and postures during different tasks.
Published Version
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