IISE transactions on occupational ergonomics and human factors最新文献

OCCUPATIONAL APPLICATIONSWorker well-being and overall system performance are important elements in the design of production lines. However, studies of industry practice show that current design tools are unable to consider concurrently both productivity aspects (e.g., line balancing and cycle time) and worker well-being related aspects (e.g., the risk of musculoskeletal disorders). Current practice also fails to account for anthropometric diversity in the workforce and does not use the potential of multi-objective simulation-based optimization techniques. Accordingly, a framework consisting of a workflow and a digital tool was designed to assist in the proactive design of workstations to accommodate worker well-being and productivity. This framework uses state-of-the-art optimization techniques to make it easier and quicker for designers to find successful workplace design solutions. A case study to demonstrate the framework is provided.

Occupational ApplicationDigital human models have been widely used for occupational assessments to reduce potential injury risk, such as automotive assembly lines, box lifting, and in the mining industry. Human motion prediction is one of the important capabilities in digital human models, and collision avoidance is involved in human motion prediction. An algorithm proposed earlier was implemented for human motion prediction, and simulated results were found to have a good correlation with the experimental studies. Use of this algorithm can help ensure that human motion is predicted realistically, and thus can impact the accuracy of injury risk assessments.

OCCUPATIONAL APPLICATIONSBiomechanical risk factors associated with spacesuit manual material handling tasks were evaluated using the singular value decomposition (SVD) technique. SVD analysis decomposed each lifting tasks into primitive motion patterns called eigenposture progression (EP) that contributed to the overall task. Biomechanical metrics, such as total joint displacement, were calculated for each EP. The first EP (a simultaneous knee, hip, and waist movement) had greater biomechanical demands than other EPs. Thus, tasks such as lifting from the floor were identified as "riskier" by having a greater composition of the first EP. The results of this work can be used to improve a task as well as spacesuit design by minimizing riskier movement patterns as shown in this case study. This methodology can be applied in civilian occupational settings to analyze open-ended tasks (e.g., complex product assembly and construction) for ergonomics assessments. Using this method, worker task strategies can be evaluated quantitatively, compared, and redesigned when necessary.

Occupational ApplicationsFounded in an empirical case study and theoretical work, this paper reviews the scientific literature to define the role of Digital Human Modeling (DHM), Digital Twin (DT), and Cyber-Physical Systems (CPS) to inform the emerging concept of Ergonomics 4.0. We find that DHM evolved into DT is a core element in Ergonomics 4.0. A solid understanding and agreement on the nature of Ergonomics 4.0 is essential for the inclusion of ergonomic values and considerations in the larger conceptual framework of Industry 4.0. In this context, we invite Ergonomists from various disciplines to broaden their understanding and application of DHM and DT.

OCCUPATIONAL APPLICATIONSMilitary helicopter pilots around the globe are at high risk of neck pain related to their use of helmet-mounted night vision goggles. Unfortunately, it is difficult to design alternative helmet configurations that reduce the biomechanical exposures on the cervical spine during flight because the time and resource costs associated with assessing these exposures in vivo are prohibitive. Instead, we developed artificial neural networks (ANNs) to predict cervical spine compression and shear given head-trunk kinematics and joint moments in the lower neck, data readily available from digital human models. The ANNs detected differences in cervical spine compression and anteroposterior shear between helmet configuration conditions during flight-relevant head movement, consistent with results from a detailed model based on in vivo electromyographic data. These ANNs may be useful in helping to prevent neck pain related to military helicopter flight by facilitating virtual biomechanical assessment of helmet configurations upstream in the design process.

OCCUPATIONAL APPLICATIONSThis contribution provides a framework for modeling user-product interactions (in CAD) for in-depth ergonomic analysis of product design, using digital human models. The framework aims to be applicable to a wide range of different products while being suitable for designers - especially those who do not have specialized ergonomic expertise or training in human behavior - by providing an intuitive, standardized, and time-efficient modeling procedure. The framework contains 31 elementary affordances, which describe mechanical dependencies between product geometries and human end effectors. These elementary affordances serve as a tool for interaction modeling. Additionally, the paper provides a taxonomy of elementary affordances, which can be used to formalize / abstract the nature of user-product interactions and to describe them as elementary affordances. Furthermore, an implementation of the interaction-modeling framework is presented in a CAD environment and provides an example of how the framework could be used in terms of a computer aided ergonomics tool.