A new approach to the design and optimisation of support structures in additive manufacturing

By G. Strano, Liang Hao, Richard M. Everson, Kenneth E. Evans. 2013

387 citations recorded by the source corpus.

Subfields: Building and Construction, Industrial and Manufacturing Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/08b4e4361ab9c43748f1a7705b55526af560d732

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Martin Leary
2. Matthijs Langelaar
3. Charlie C. L. Wang
4. Filomeno Martina
5. Milan Brandt

In Industrial and Manufacturing Engineering

1. Matthijs Langelaar
2. Krishnan Suresh
3. Charlie C. L. Wang
4. Albert C. To
5. Lin Cheng
6. Xuan Liang
7. Zhan Kang
8. Lei Li

In Mechanical Engineering

1. S. Sun
2. Lin Cheng
3. Milan Brandt
4. M. Mehrpouya
5. Jiaxi Bai
6. Xun Xu
7. Krishnan Suresh
8. W. Wong

Citations in the corpus

• Topology optimization of 3D self-supporting structures for additive manufacturing (2016, methodology): “Efforts have been made to automate and/or optimize the addition of these support structures [15, 16, 17], or to find the most economical sacrificial lattice structures, e.g. [ 18].”
• An overview of powder granulometry on feedstock and part performance in the selective laser melting process (2017, background): “Most of these effects were related to the energy density used in the SLM process where researchers have developed various physical and numerical models to predict surface quality [160,165,166].”
• An additive manufacturing filter for topology optimization of print-ready designs (2016, background): “Various strategies to automate the addition of minimal support structures have been proposed, see e.g. Strano et al. (2013), Vanek et al. (2014), and Calignano (2014).”
• Metal additive manufacturing in the commercial aviation industry: A review (2019, methodology): “Some years ago, additive manufacturing processes were just used for prototyping and today there are more and more industries trying to exploit the benefits of AM in terms of design complexity and just-in-time production [39, 230, 231].”
• Deformation and failure behaviour of Ti-6Al-4V lattice structures manufactured by selective laser melting (SLM) (2015, background): “This is attributed to additional powder being captured by the melt pool during SLM layer manufacture of overhanging surfaces [30].”
• On utilizing topology optimization to design support structure to prevent residual stress induced build failure in laser powder bed metal additive manufacturing (2019, methodology): “[11] proposed a method to design support structure through the optimization of built orientation and cellular structure.”
• Support Structures for Additive Manufacturing: A Review (2018, methodology): “[43] proposed a new approach which applies a new optimization algorithm to use pure mathematical 3D implicit functions for the design and generation of the cellular support structures, including graded supports.”
• Current and future trends in topology optimization for additive manufacturing (2018, background): “structure [28], tree-like structure [29,30], bridge-like scaffold [31], and repetitive cellular structures [32,33], which form lightweight support subjected to the well-defined part geometry and build direction.”