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Probabilistic Modeling and Analysis of Fused Deposition Modeling Process Using Surrogate Models

[+] Author Affiliations
Yi Liu, Pingfeng Wang

Wichita State University, Wichita, KS

Paper No. DETC2016-59603, pp. V02BT03A051; 9 pages
  • ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2B: 42nd Design Automation Conference
  • Charlotte, North Carolina, USA, August 21–24, 2016
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5011-4
  • Copyright © 2016 by ASME


Various sources of uncertain parameters at multiple levels, from design steps to manufacturing processes, are often involved in composite structures. Probabilistic modeling and analysis of the composite structure and its manufacturing processes can provide underlying information to assess uncertainties and improve the quality of the developed composite structures. This paper presents a stochastic multi-level modeling framework considering material, structural, modeling parameters as well as the manufacturing process based on a surrogate model. An enhanced laminate theory is employed to determine the elastic constants of the composite materials considering imperfect bonding among filaments in the manufacturing process. To improve the computational efficiency in simulation-based reliability approach, the evaluation of the structure properties is approximated by employing surrogate models based upon the physics model. To apply the present framework, a case study with a composite laminate beam under three-point bending, which is made through fused deposition modeling, is conducted, and the case study results demonstrate the efficacy of the presented modeling scheme and analysis methodology.

Copyright © 2016 by ASME
Topics: Modeling



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