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A comprehensive framework for stiffness modeling of industrial robot for machining applications

journal contribution
posted on 2025-11-20, 12:24 authored by Selvaganesan J., Eldho Paul, Alexandr KlimchikAlexandr Klimchik, Arunachalam N
<p dir="ltr">Industrial robots offer several advantages, including a larger workspace, software flexibility, and the ability to enable multi-purpose, reconfigurable systems. However, their low stiffness during machining leads to both translational and rotational deformations at the end-effector, affecting machining accuracy. This study proposes a novel frame-invariant comprehensive compliance performance index that considers both translational and rotational deformations at the robot end-effector. A posture optimization problem is formulated using the proposed index to minimize end-effector deformation. Existing stiffness performance indices often neglect the impact of rotational deformation caused by compliance and spindle configuration. This study evaluates the significance of considering these effects by comparing the proposed index with conventional indices. Analytical results show that, for a given drilling position, the maximum percentage increase in the calculated deflection norm between the proposed index and indices that neglect rotational deformation such as the deformation evaluation index and compliance evaluation index are 77.45% and 30.77%, respectively. The proposed methodology is validated through robotic drilling experiments, demonstrating H9 tolerance accuracy and improved hole quality including better circularity and cylindricity in the optimal configuration compared to non-optimal configuration. The proposed methodology is validated by robotic drilling experiments, achieving H9 tolerance accuracy and improved hole quality, including enhanced circularity and cylindricity, in the optimized configuration compared to non-optimal configurations. The findings highlight the effectiveness of the proposed methodology in addressing stiffness-related challenges and improving machining accuracy.</p>

History

School affiliated with

  • School of Engineering and Physical Sciences (Research Outputs)

Publication Title

Journal of Manufacturing Processes

Volume

152

Pages/Article Number

1111-1122

Publisher

Elsevier

ISSN

1526-6125

eISSN

2212-4616

Date Submitted

2025-04-16

Date Accepted

2025-07-28

Date of First Publication

2025-08-31

Date of Final Publication

2025-10-30

Open Access Status

  • Not Open Access

Date Document First Uploaded

2025-11-17

Will your conference paper be published in proceedings?

  • N/A

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