Simultaneous topology and build orientation optimization for minimization of additive manufacturing cost and time

Fritz, Kevin; Kim, Il Yong

doi:10.1002/nme.6366

Cited by 15 publications

(10 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the method of [71], a mathematical framework for minimisation of the structural compliance, build time, and build cost of an LPBF part in simultaneous part orientation and density-based topology optimisation. The surface area and support volume of an input 3D model were implemented as the physical factors affecting the build time and build cost.…”

Section: One-step Methods For the Lpbf Processmentioning

confidence: 99%

Status, issues, and future of computer-aided part orientation for additive manufacturing

Qin

Shi

et al. 2021

Int J Adv Manuf Technol

View full text Add to dashboard Cite

Part orientation is a critical task in the process of additive manufacturing product realisation. Recently, various computer-aided methods for this task have been presented in the literature. The coexistence of different methods generates a series of questions: What are the common characteristics of these methods? What are the specific characteristics of each method? What are the main issues in computer-aided part orientation for additive manufacturing currently? What are the potential research directions in this field in the future? To approach these questions, a review of the existing computer-aided part orientation methods for additive manufacturing is presented in this paper. This review starts with a clarification of a part orientation problem and a classification of the existing methods into two categories according to their process of solving the problem. An overview of the representative methods in each category is then carried out from the aspects of approaches for orientation search, generation, or selection, estimation of build orientation factors, determination of weights of factors, establishment of overall objective function, and demonstration of effectiveness. After that, a discussion about the main issues in computer-aided part orientation for additive manufacturing is documented based on the overview. Finally, a suggestion of some future research directions in this field is reported.

show abstract

Section: One-step Methods For the Lpbf Processmentioning

confidence: 99%

Status, issues, and future of computer-aided part orientation for additive manufacturing

Qin

Shi

et al. 2021

Int J Adv Manuf Technol

View full text Add to dashboard Cite

show abstract

“…They accomplish this by defining the density of any element as a function of the densities of other elements that can support it based on finite element meshes, spatial density gradients, or searching for elements in a defined support region . An advantage of these methods is they find the self-supporting geometry that minimizes production cost, time, and/or structural compliance or maximize eigenfrequency, rather than relying on posthoc modifications to the geometry. − …”

Section: Future Developments That Could Change the Equation For Ammentioning

confidence: 99%

“… 103 An advantage of these methods is they find the self-supporting geometry that minimizes production cost, time, and/or structural compliance or maximize eigenfrequency, rather than relying on posthoc modifications to the geometry. 102 − 105 …”

Section: Future Developments That Could Change the Equation For Ammentioning

confidence: 99%

Is Additive Manufacturing an Environmentally and Economically Preferred Alternative for Mass Production?

Jung

Kara

Nie

et al. 2023

Environ. Sci. Technol.

View full text Add to dashboard Cite

The manufacturing sector accounts for a large percentage of global energy use and greenhouse gas emissions, and there is growing interest in the potential of additive manufacturing (AM) to reduce the sector’s environmental impacts. Across multiple industries, AM has been used to reduce material use in final parts by 35–80%, and recent publications have predicted that AM will enable the fabrication of customized products locally and on-demand, reducing shipping and material waste. In many contexts, however, AM is not a viable alternative to traditional manufacturing methods due to its high production costs. And in high-volume mass production, AM can lead to increased energy use and material waste, worsening environmental impacts compared to traditional production methods. Whether AM is an environmentally and economically preferred alternative to traditional manufacturing depends on several hidden aspects of AM that are not readily apparent when comparing final products, including energy-intensive and expensive material feedstocks, excessive material waste during production, high machine costs, and slow rates of production. We systematically review comparative studies of the environmental impacts and costs of AM in contrast with traditional manufacturing methods and identify the conditions under which AM is the environmentally and economically preferred alternative. We find that AM has lower production costs and environmental impacts when production volumes are relatively low (below ∼1,000 per year for environmental impacts and below 42–87,000 per year for costs, depending on the AM process and part geometry) or the parts are small and would have high material waste if traditionally manufactured. In cases when the geometric freedom of AM enables performance improvements that reduce environmental impacts and costs during a product’s use phase, these can counteract the higher production impacts of AM, making it the preferred alternative at larger production volumes. AM’s ability to be environmentally and economically beneficial for mass manufacturing in a wider variety of contexts is dependent on reducing the cost and energy intensity of material feedstock production, eliminating the need for support structures, raising production speeds, and reducing per unit machine costs. These challenges are not primarily caused by economies of scale, and therefore, they are not likely to be addressed by the increasing expansion of the AM sector. Instead, they will require fundamental advances in material science, AM production technologies, and computer-aided design software.

show abstract

“…Rather than adopting a tessellated infill design approach to generating supports, advanced concepts are also emerging from the research community for the support structures to be generated via TO (Mezzadri et al 2018). Some of these methods enable TO concurrently with part orientation, accounting for both structural performance and manufacturing constraints (Fritz and Kim 2020). Supporting structures can also be optimised with respect to thermal compliance to minimise mean temperature (Giraldo-Londoño, et al 2020) or for maximising heat dissipation (Miki and Nishiwaki 2022).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous optimisation of support structure regions and part topology for additive manufacturing

Daynes

2022

Struct Multidisc Optim

View full text Add to dashboard Cite

Support structures are required to enable the build of additively manufactured parts. The supports reinforce overhanging regions on the part and/or counteract the thermally-induced residual stresses generated during printing. However, the optimal design of the part for its intended use case is decoupled from the design of the support structures in a conventional design for additive manufacturing (DfAM) workflow. In this work, a novel methodology is presented that simultaneously optimises the part topology and its support structure regions. A two-model topology optimisation approach is considered. One model describes the combined part and support structure regions subject to a pseudo-gravity load and a second model describes the part subject to its intended application load cases. A novel load-aligned trunk and branch support structure is generated from the topology optimisation results. Generating the fine support features in a post-processing step avoids the computational expense of topology optimising the intricate supports directly. Thermo-mechanical simulations of a selective laser melting process confirms that this new approach to optimising support structures can reduce manufacturing process-induced deformation when benchmarked against a conventional DfAM workflow.

show abstract

Simultaneous topology and build orientation optimization for minimization of additive manufacturing cost and time

Cited by 15 publications

References 35 publications

Status, issues, and future of computer-aided part orientation for additive manufacturing

Status, issues, and future of computer-aided part orientation for additive manufacturing

Is Additive Manufacturing an Environmentally and Economically Preferred Alternative for Mass Production?

Simultaneous optimisation of support structure regions and part topology for additive manufacturing

Contact Info

Product

Resources

About