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Adaptive Slicing in Additive Manufacturing using Strip Tree Data Structures

Beltur, Bharat Ramachandra
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479815018228663

Abstract Details

2016, MS, University of Cincinnati, Engineering and Applied Science: Mechanical Engineering.
Additive Manufacturing (AM) is a manufacturing process where material is laid down successively in layers based on a predetermined design to build the desired part. This inadvertently leads to a phenomenon called the staircase effect that affects the finish of the part. Reduction in staircase error and increase in build speed are two important factors that are being developed to improve AM processes, which have led to the introduction of the concept of adaptive slicing. Existing slicing methodologies compromise on either build speed or part finish quality. This thesis seeks to improve the AM process by introducing a new adaptive slicing algorithm using Strip tree data structures. An innovative method for adaptive slicing has been developed using a binary space partitioning approach. The algorithm developed is used to convert the 3D computer aided design (CAD) model of the part which is represented by an STL dataset to a strip tree data structure by taking into account its geometry, user defined tolerance values and the AM machine parameters. Using the strip trees generated, adaptive layer thicknesses are subsequently calculated to confirm to final part quality. This ensures improvement in the finish of the part while minimizing build time. The methodology is validated by virtually manufacturing example parts using the computed layer thicknesses and verifying part profile errors.
Sundararaman Anand, Ph.D. (Committee Chair)
Thomas Richard Huston, Ph.D. (Committee Member)
David Thompson, Ph.D. (Committee Member)
77 p.
Mechanics

Recommended Citations

Citations

  • Beltur, B. R. (2016). Adaptive Slicing in Additive Manufacturing using Strip Tree Data Structures [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479815018228663

    APA Style (7th edition)

  • Beltur, Bharat Ramachandra. Adaptive Slicing in Additive Manufacturing using Strip Tree Data Structures. 2016. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479815018228663.

    MLA Style (8th edition)

  • Beltur, Bharat Ramachandra. "Adaptive Slicing in Additive Manufacturing using Strip Tree Data Structures." Master's thesis, University of Cincinnati, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479815018228663

    Chicago Manual of Style (17th edition)

ucin1479815018228663
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© 2016, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.