Quantification of Exposure to Risk Postures in Truck Assembly Operators: Neck, Back, Arms and Wrists.

The study assessed the proportion of time in risky postures for the main joints of the upper limbs in a truck assembly plant and explored the association with musculoskeletal symptoms. Fourteen workstations (13 individuals) of a truck assembly plant were selected, and seven sensors were placed on the body segments of the participants. The sensors included tri-axial accelerometers for the arms and back, inclinometers for the neck and electro-goniometry for quantifying flexion/extension of the right and left hands. The proportions of time in moderate awkward postures were high at all workstations. Neck and wrist excessive awkward postures were observed for most workstations. The average values of the 91st percentile for back flexion and right/left arm elevation were 25°, 62°, and 57°, respectively. The 91st and 9th percentile averages for neck flexion/extension were 35.9° and -4.7°, respectively. An insignificant relationship was found between the percentage of time spent in awkward upper limb posture and musculoskeletal symptoms. The findings provide objective and quantitative data about time exposure, variability, and potential risk factors in the real workplace. Quantitative measurements in the field provide objective data of the body postures and movements of tasks that can be helpful in the musculoskeletal disorders (MSDs) prevention program.

Using Digital and Physical Simulation to Focus on Human Factors and Ergonomics in Aviation Maintainability.

OBJECTIVE: This research aimed to evaluate the differences in the assessments made by three simulation tools used in a maintainability design office to perform human factor/ergonomics (HFE) analysis: digital human modeling (DHM), virtual reality (VR), and physical mock-up (PMU). BACKGROUND: Maintainability engineers use digital/physical simulation tools in the early design phase to analyze whether the design is well adapted for maintenance operators. Knowing the potential of these simulation tools would encourage maintainability stakeholders to integrate HFE in the design process more efficiently. METHOD: Eleven maintenance tasks were analyzed from the participation of six maintenance operators. Various HFE indicators including physical, cognitive, and organizational indicators were assessed. Each operator repeated 11 maintenance tasks on VR and PMU. Based on the anthropometric parameters, six manikins were created to analyze 11 maintenance tasks on DHM. RESULTS: A significant difference was found for the organizational indicators between VR and PMU, whereas the physical and cognitive indicators are similar. DHM, VR, and PMU are compared with the common HFE indicators for the physical dimension and present a significant difference for individual tasks. CONCLUSION: To reduce the gap between simulation tools, a better physical representation is requested on the VR platform, improving the perception of work sequences in the virtual world. Concerning DHM, a new paradigm is proposed to study a few tasks per work area instead of studying each task independently. APPLICATION: This study will help develop a new methodology and tools specifically for non-HFE experts in the maintainability department.

Within and between Individual Variability of Exposure to Work-Related Musculoskeletal Disorder Risk Factors.

Industrial companies indicate a tendency to eliminate variations in operator strategies, particularly following implementation of the lean principle. Companies believe when the operators perform the same prescribed tasks, they have to execute them in the same manner (completing the same gestures and being exposed to the same risk factors). They attempt to achieve better product quality by standardizing and reducing operational leeway. However, operators adjust and modify ways of performing tasks to balance between their abilities and the requirements of the job. This study aims to investigate the variability of exposure to physical risk factors within and between operators when executing the same prescribed tasks. The Ergonomic Standard method was used to evaluate two workstations. Seven operators were observed thirty times between repeated cycle times at those workstations. The results revealed the variability of exposure to risk factors between and within operators in the repeated execution of the same tasks. Individual characteristics and operators' strategies might generate the variability of exposure to risk factors that may be an opportunity to reduce the risks of work-related musculoskeletal disorders (WR-MSDs). However, sometimes operators' strategies may cause overexposure to risk factors; operators most often adopt such strategies to undertake their tasks while reducing the workload.

Physical risk factors identification based on body sensor network combined to videotaping.

The aim of this study was to perform an ergonomic analysis of a material handling task by combining a subtask video analysis and a RULA computation, implemented continuously through a motion capture system combining inertial sensors and electrogoniometers. Five workers participated to the experiment. Seven inertial measurement units, placed on the worker's upper body (pelvis, thorax, head, arms, forearms), were implemented through a biomechanical model of the upper body to continuously provide trunk, neck, shoulder and elbow joint angles. Wrist joint angles were derived from electrogoniometers synchronized with the inertial measurement system. Worker's activity was simultaneously recorded using video. During post-processing, joint angles were used as inputs to a computationally implemented ergonomic evaluation based on the RULA method. Consequently a RULA score was calculated at each time step to characterize the risk of exposure of the upper body (right and left sides). Local risk scores were also computed to identify the anatomical origin of the exposure. Moreover, the video-recorded work activity was time-studied in order to classify and quantify all subtasks involved into the task. Results showed that mean RULA scores were at high risk for all participants (6 and 6.2 for right and left sides respectively). A temporal analysis demonstrated that workers spent most part of the work time at a RULA score of 7 (right: 49.19 ± 35.27%; left: 55.5 ± 29.69%). Mean local scores revealed that most exposed joints during the task were elbows, lower arms, wrists and hands. Elbows and lower arms were indeed at a high level of risk during the total time of a work cycle (100% for right and left sides). Wrist and hands were also exposed to a risky level for much of the period of work (right: 82.13 ± 7.46%; left: 77.85 ± 12.46%). Concerning the subtask analysis, subtasks called 'snow thrower', 'opening the vacuum sealer', 'cleaning' and 'storing' have been identified as the most awkward for right and left sides given mean RULA scores and percentages of time spent at risky levels. Results analysis permitted to suggest ergonomic recommendations for the redesign of the workstation. Contributions of the proposed innovative system dedicated to physical ergonomic assessment are further discussed.