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Thermal modeling and uncertainty quantification of tool for automated garment assembly


In this work, a thermal Finite Element model is developed to simulate the performance of a blade-like tool for robotic work cells performing automated garment production using a novel thermoplastic stiffening layer. Uncertainty quantification and sensitivity analysis are applied to determine the most important design properties and optimize key performance metrics for swift and reliable garment assembly. Attention is focused on the geometric and thermal design properties that minimize sensitivity to environmental conditions while maximizing expected productivity. An example design is shown for illustrative purposes. This work may inform future design innovation for similar heating tools and reduce the need for physical experiments and long calibration times on the factory floor.

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Data Availability

The data used in this work was generated by code written by the authors. It may be obtained from the contributing authors upon reasonable request.

Code Availability

The code used in this work may be obtained from the contributing authors upon reasonable request.


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This work was partially funded by the Siemens Corporation and the Advanced Robotics Manufacturing (ARM) Institute. Professor Zohdi’s work is supported by AFRI Competitive Grant no. 2020-67021-32855/project accession no. 1024262 from the USDA National Institute of Food and Agriculture. This grant is being administered through AIFS: the AI Institute for Next Generation Food Systems.

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Correspondence to Tarek I. Zohdi.

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Castrillon, N., Rock, A. & Zohdi, T.I. Thermal modeling and uncertainty quantification of tool for automated garment assembly. Comput Mech 70, 879–889 (2022).

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  • Uncertainty quantification
  • Finite element method
  • Thermal modeling
  • Automation
  • Garments