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A dynamic mechanical model for hand force in right angle nutrunner operation

S A Oh1, R G Radwin, F J Fronczak

  • 1Samsung Data Systems Co., Ltd., Seoul, Korea.

Human Factors
|December 12, 1997
PubMed
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This study developed a mechanical model to estimate hand forces during tool use. Tool inertia significantly impacts hand forces, with dynamic models offering more accurate predictions than static ones, especially for harder joints.

Area of Science:

  • Ergonomics and Biomechanics
  • Occupational Safety and Health
  • Mechanical Engineering

Background:

  • Estimating hand forces in tool use is crucial for preventing musculoskeletal disorders.
  • Existing models often lack accuracy due to complexities of tool-user interaction.
  • Understanding the influence of tool parameters on hand forces is essential for safer tool design.

Purpose of the Study:

  • To develop and validate a deterministic mechanical model for estimating static and dynamic hand forces.
  • To investigate the impact of target torque and joint hardness on hand forces during tool operation.
  • To compare the accuracy of static and dynamic models in predicting hand forces.

Main Methods:

  • Utilized kinematic measurements and a deterministic mechanical model based on physical tool parameters.

Related Experiment Videos

  • Experimentally varied target torque (25, 40, 55 Nm) and joint hardness (35-900 ms torque buildup time).
  • Validated model estimations against direct hand force measurements using a strain gauge dynamometer.

    • Main Results:

    • Estimated hand force was significantly affected by target torque and joint hardness.
    • Peak and average dynamic hand force varied, being lowest for hard joints (35 ms) and highest for medium-hard joints (150 ms).
    • Tool inertia was identified as a major factor reducing hand reaction force; increased inertial force correlated with decreased estimated hand force.

    Conclusions:

    • The developed dynamic model provides a more accurate estimation of hand forces compared to static models, particularly for harder joints.
    • Tool inertia plays a critical role in modulating hand forces, necessitating its inclusion in predictive models.
    • The findings can inform the design of tools and work procedures to minimize operator hand forces and reduce injury risk.