Multibody Simulation Framework for Human-Machine Interaction in Impact Wrench Fastening: Enabling Reliability and Work-Related Health Risk Assessment

Abstract: Ensuring both work-related health protection and reliability in impact wrench operations requires an in-depth understanding of human-machine systems, specifically the interactions between the human operator, impact wrench, and bolt connection with the environment. However, existing studies typically focus on isolated aspects, neglecting the complex dynamics between these systems. The lack of a simulation framework hinders assessments of human load, hand-arm vibration syndrome (HAVS) risk, and the reliability of the fastening process. Without a holistic approach, it remains challenging to optimize tool design, refine tightening strategies, and mitigate risks associated with high-frequency impulsive forces.To address this gap, we present a multibody simulation framework for analyzing human-machine systems, integrating three models: a digital human model (DHM) based on a musculoskeletal human model for biomechanical and health risk assessment, a multibody impact wrench model with drivetrain dynamics to capture impulsive force transmission, and a multibody bolt connection model with fastening dynamics to assess reliability. The three models run as a co-simulation between OpenSim and MATLAB Simulink described by Molz et al. The multibody impact wrench model based on the presented workload model (ApOL) of Sänger et al. is extended by modelling the internal drivetrain dynamics of the impact wrench and the forces acting onto the human during the bolt tightening process. The bolt model integrates finite element (FE) simulations on the micro level with a multibody system (MBS) model on the macro level to capture tribological effects in tangential impact-driven bolt tightening. The micro-scale FE model incorporates real thread topographies to compute friction coefficients, which are then applied in the macro-scale MBS model that includes bolt inertia and the impact wrench’s drive system. This enables a more accurate prediction of fastening dynamics, thread deformation, and torque losses, improving the assessment of the final preload force while ensuring scalability across different bolt sizes. By leveraging these models, we establish a multibody simulation framework that links human biomechanics, tool dynamics, and the mechanics of the bolt connection. Our framework provides a structured way to assess how impulsive forces propagate through the different systems. Additionally, by integrating fastening mechanics, we can examine how variations in bolt preload, friction coefficients, and tightening sequences impact the reliability of the bolt connection. The framework can also be used to compare different impact wrench tool designs and configurations, offering insights into how to mitigate undesired tool-induced physical stresses on the human operator. It sets the stage for future developments in enabling reliability and work-related health risk assessment. The modular nature of the framework allows for extensions, such as incorporating sensor-based validation data, and adapting the approach to other fastening tools. Additionally, this framework can be applied to different industrial settings, where fastening precision and human stress are critical factors, such as construction industry. The DHM in OpenSim estimates muscle activity in response to external forces and motion; however, it is not validated for assessing vibration exposure. This remains an active research topic within the musculoskeletal modeling community. Future work will focus on validating the simulation results against experimental measurements and refining the dynamic models to capture interactions more accurately. Ultimately, this framework establishes a foundation for systematically analyzing and enhancing human-machine interaction in impact wrench fastening, effectively linking reliability with work-related health risk assessment.

Keywords: human-machine system, drivetrain, bolt connection, tribological modelling, hand-arm vibration syndrome (HAVS)

DOI: 10.54941/ahfe1006699

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