Topology Optimization Software for Additive Manufacturing: A Review of Current Capabilities and a Real-World Example

2016 ◽  
Author(s):  
Sai Nithin Reddy K. ◽  
Ian Ferguson ◽  
Mary Frecker ◽  
Timothy W. Simpson ◽  
Corey J. Dickman
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
User Interfaces ◽  
Educational Software ◽  
Software Tools ◽  
Additive Manufacture ◽  
Optimization Software ◽  
Current State ◽  
Complex Organic

Topology optimization is finding renewed interest thanks to additive manufacturing — a technology that is well-suited to fabricate the complex organic shapes and structures that often arise from topology optimization. This paper reviews the current state of topology optimization software through the redesign of a real aerospace mounting plate, focusing on manufacturing considerations that are important for additive manufacturing (AM). Twenty different commercial and educational software tools are investigated and categorized based on their capabilities. Two representative software tools are then demonstrated with well-known examples to compare user interfaces and outputs, and one is chosen to perform the mounting plate case study. We find that all of the commercially available topology optimization software packages offer similar capabilities and considerably more functionality than educational software, but only a few niche products can be tailored to specific applications and manufacturing processes. Current commercial software does not provide adequate manufacturing constraints to remove the need for manual interpretation of results for additive manufacture. A case study involving optimization of an industry-relevant component for AM is used to provide in-depth understanding of both topology optimization and manufacturing considerations in AM. Shortcomings in the existing software tools are presented, and future requirements to take advantage of the increasing AM capabilities, particularly in metals, are discussed.

scholarly journals Optimization of Brake Calipers Using Topology Optimization for Additive Manufacturing

2021 ◽  
Vol 11 (4) ◽  
pp. 1437
Author(s):  
Evangelos Tyflopoulos ◽  
Mathias Lien ◽  
Martin Steinert
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Optimization Procedure ◽  
Optimization Approach ◽  
Design Flexibility ◽  
Current State ◽  
3D Printed ◽  
Removal Processes ◽  
Material Layout

The weight optimization of a structure can be conducted by using fewer and downsized components, applying lighter materials in production, and removing unwanted material. Topology optimization (TO) is one of the most implemented material removal processes. In addition, when it is oriented towards additive manufacturing (AM), it increases design flexibility. The traditional optimization approach is the compliance optimization, where the material layout of a structure is optimized by minimizing its overall compliance. However, TO, in its current state of the art, is mainly used for design inspiration and not for manufacturing due to design complexities and lack of accuracy of its design solutions. The authors, in this research paper, explore the benefits and the limitations of the TO using as a case study the housings of a front and a rear brake caliper. The calipers were optimized for weight reduction by implementing the aforementioned optimization procedure. Their housings were topologically optimized, partially redesigned, prepared for 3D printing, validated, and 3D printed in titanium using selective laser melting (SLM). The weight of the optimized calipers reduced by 41.6% compared to commercial calipers. Designers interested in either TO or in automotive engineering can exploit the findings in this paper.

Lattice Structure Design for Additive Manufacturing: Unit Cell Topology Optimization

2019 ◽  
Author(s):  
Bradley Hanks ◽  
Mary Frecker
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Lattice Structure ◽  
Optimization Method ◽  
Structure Design ◽  
Unit Cell ◽  
Lattice Structures ◽  
Design For Additive Manufacturing ◽  
Structure Topology

Abstract Additive manufacturing is a developing technology that enhances design freedom at multiple length scales, from the macroscale, or bulk geometry, to the mesoscale, such as lattice structures, and even down to tailored microstructure. At the mesoscale, lattice structures are often used to replace solid sections of material and are typically patterned after generic topologies. The mechanical properties and performance of generic unit cell topologies are being explored by many researchers but there is a lack of development of custom lattice structures, optimized for their application, with considerations for design for additive manufacturing. This work proposes a ground structure topology optimization method for systematic unit cell optimization. Two case studies are presented to demonstrate the approach. Case Study 1 results in a range of unit cell designs that transition from maximum thermal conductivity to minimization of compliance. Case Study 2 shows the opportunity for constitutive matching of the bulk lattice properties to a target constitutive matrix. Future work will include validation of unit cell modeling, testing of optimized solutions, and further development of the approach through expansion to 3D and refinement of objective, penalty, and constraint functions.

Utilizing Design for Metal Additive Manufacturing and Topology Optimization to Improve Product Designs

2019 ◽  
Author(s):  
Martin L. Tanaka ◽  
Jeremy J. Smith
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Yield Strength ◽  
Maximum Stress ◽  
Optimized Design ◽  
Original Design ◽  
Optimization Software ◽  
Metal Additive Manufacturing ◽  
Fea Model ◽  
Metal Additive

Abstract Metal additive manufacturing has transformed the product design process by enabling the fabrication of components with complex geometries that cannot be manufactured using conventional methods. Initial designs can be further enhanced by employing topology optimization software and Design for Metal Additive Manufacturing (DFMAM) guidelines. In this study, a commercially available bicycle spider-crank was optimized for three-dimensional (3D) metal manufacturing. The 3D surface geometry of the original spider-crank was acquired using a white light scanner and used to generate a 3D solid model of the part. Boundary conditions were obtained from cycling loads found in published literature and applied to an ANSYS Finite Element Analysis (FEA) model. The FEA model was analyzed to determine the von Mises stress throughout the part. ANSYS Topology Optimization software was applied to the model. The software uses an iterative process to remove low stress material and recalculate stress within the part until no more material can be removed without exceeding a target maximum stress value. Following topology optimization, DFMAM principles were applied to enable the part to be 3D printed. Results from the FEA showed the DFMAM optimized design to be 41.5% lighter than the original design. The maximum stress increased from 41.2% of the material yield strength to 61.5% in the DFMAM optimized design, which exceeded the target optimization value of 50% yield strength. Analysis results were verified experimentally. The original design and DFMAM optimized design were printed using an EOS M 290 metal additive manufacturing machine. Parts were separated from the support structure and tested on a universal testing machine. A custom testing apparatus was designed and built to conduct the testing. Testing was performed at 15 degrees intervals throughout the range of motion. Strain gages attached to the arm of the crank were used to obtain stress values at specific locations and dial indicators were used to measure the deflection of the crank arm under load. Experimental results closely matched results obtained from the FEA, validating the model. With the model validated at specific locations, it was assumed that the stress calculated by the FEA at the critical points were also accurate. The results showed the topology optimization software to be an effective and useful tool for optimizing the design of 3D metal printed parts. However, topology optimization alone was not enough to finalize a design prior to printing. The application of DFMAM principles were needed to ensure that the overhanging structures would not collapse during printing. Because the determination of what constitutes an overhang is determined by the part orientation when printed, some modification will generally be required prior to printing. In conclusion, using a bicycle spider-crank as an example, this research has shown that the use of topology optimization software and Design for Metal Additive Manufacturing principles is able to reduce the weight of a 3D metal printed part while simultaneously achieving a maximum stress near a target value.

Digital Solutions for Integrated and Collaborative Additive Manufacturing

2016 ◽  
Author(s):  
Yan Lu ◽  
Paul Witherell ◽  
Felipe Lopez ◽  
Ibrahim Assouroko
Keyword(s):  
Additive Manufacturing ◽  
Analytical Framework ◽  
Knowledge Bases ◽  
Software Tools ◽  
Data Models ◽  
Development Environment ◽  
Manufacturing Operations ◽  
Support Tools ◽  
Product Design Process

Software tools, knowledge of materials and processes, and data provide three pillars on which Additive Manufacturing (AM) lifecycles and value chains can be supported. These pillars leverage efforts dedicated to the development of AM databases, high-fidelity models, and design and planning support tools. However, as of today, it remains a challenge to integrate distributed AM data and heterogeneous predictive models in software tools to drive a more collaborative AM development environment. In this paper, we describe the development of an analytical framework for integrated and collaborative AM development. Information correlating material, product design, process planning and manufacturing operations are captured and managed in the analytical framework. A layered structure is adopted to support the composability of data, models and knowledge bases. The key technologies to enable composability are discussed along with a suite of tools that assist designers in the management of data, models and knowledge components. A proof-of-concept case study demonstrates the potential of the AM analytical framework.

scholarly journals REDESIGN AND TOPOLOGY OPTIMIZATION OF AN INDUSTRIAL ROBOT LINK FOR ADDITIVE MANUFACTURING

2019 ◽  
Vol 17 (3) ◽  
pp. 415 ◽  
Author(s):  
Evangelos Tsirogiannis ◽  
George-Christopher Vosniakos
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Strain Energy ◽  
Industrial Robot ◽  
Selective Laser Sintering ◽  
Maximum Strain ◽  
Trial And Error ◽  
Optimization Software ◽  
And Topology ◽  
Strength And Stiffness

Design optimization for Additive Manufacturing is demonstrated by the example of an industrial robot link. The part is first redesigned so that its shape details are compatible with the requirements of the Selective Laser Sintering technique. Subsequently, the SIMP method of topology optimization is utilized on commercially available software in order to obtain the optimum design of the part with restrictions applicable to Additive Manufacturing, namely member thickness, symmetry and avoidance of cavities and undercuts. Mass and strain energy are the design responses. The volume was constrained by a fraction of the initial mass. The desired minimization of maximum strain energy is expressed as an objective function. A 7% reduction in the mass of the part was achieved while its strength and stiffness remained unchanged. The process is supported by topology optimization software but it also involves some trial-and-error depending on the designer’s experience.

Designing for Additive Manufacturing: Lightweighting Through Topology Optimization Enables Lunar Spacecraft

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
Melissa E. Orme ◽  
Michael Gschweitl ◽  
Michael Ferrari ◽  
Ivan Madera ◽  
Franck Mouriaux
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Preliminary Design ◽  
Powder Bed ◽  
Lunar Landing ◽  
Rigorous Testing ◽  
Numerical Effort ◽  
Engine Mount ◽  
Development Approach

An end-to-end development approach for space flight qualified additive manufacturing (AM) components is presented and demonstrated with a case study consisting of a system of five large, light-weight, topologically optimized components that serve as an engine mount in SpaceIL's GLPX lunar landing craft that will participate in the Google Lunar XPrize challenge. The development approach includes a preliminary design exploration intended to save numerical effort in order to allow efficient adoption of topology optimization and additive manufacturing in industry. The approach also addresses additive manufacturing constraints, which are not included in the topology optimization algorithm, such as build orientation, overhangs, and the minimization of support structures in the design phase. Additive manufacturing is carried out on the topologically optimized designs with powder bed laser technology and rigorous testing, verification, and validation exercises complete the development process.

Promotion of Knowledge and Technology Transfer Towards Innovative Manufacturing Process: Case Study of New Hybrid Coating Process

2019 ◽  
Vol 13 (3) ◽  
pp. 419-431 ◽  
Author(s):  
Kentaro Shinoda ◽  
Hiroaki Noda ◽  
Koichi Ohtomi ◽  
Takayuki Yamada ◽  
Jun Akedo ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Manufacturing Process ◽  
New Technologies ◽  
Aerosol Deposition ◽  
Design Tool ◽  
Coating Process ◽  
Past Study ◽  
Fine Ceramics

A new, multi-dimensional, additive manufacturing process for fine ceramics was proposed and developed as part of a national project in Japan. The process consists of three-dimensional printing and two-dimensional coating of fine ceramics. A new coating process, hybrid aerosol deposition (HAD), was proposed as the ceramic coating process. The HAD process is a hybrid of aerosol deposition (AD) and plasma spray. Such new technologies, however, usually take a long time to move from first discovery to use in producing a commercial product. For example, a past study showed that it took nearly 15 years from the invention of the AD process to the time it became a technology used at an industrial company. Therefore, it is very important to consider how to accelerate the learning and technological transfer of a new process to industry in addition to how to develop new processes once they emerge. In this study, a new scheme, a coating hub, is proposed to promote the transfer of the HAD process to industrial adoption. In the coating hub, a collaboration scheme for companies to get interest of the technology, even in the early stages of technological development, is considered. Here, needs-seeds matching, reliable relationships, intellectual property, and the generalization of technology are considered. Another important scheme of the coating hub is to try to couple design with manufacturing. Here, product design tools for agile production are provided. In order to attract and evaluate consumers for targeted products, a Kansei delight design based on the Kano model is introduced. A delight map viewer is provided to visualize potential consumers’ delight factors. Detailed planning from the early trial stage is introduced with the viewer. A topology optimization tool is also provided in the coating hub as a design tool. In order to validate this coating hub concept, a ceramic frying pan is designed as a case study. The delight map viewer proves effective for those who are not design professionals to consider the attractiveness of products based on user evaluation. The coupling of the topology optimization tool is also useful for the multidimensional additive manufacturing of ceramics proposed in this study. This case study implies that even a small manufacturer could design a new product by utilizing the coating hub concept. It would give many new opportunities not only to big manufactures interested in high-end business-to-business components but also to supporting industries and even to individuals to utilize new emerging coating technologies.

Additive Manufacturing Constraints in Topology Optimization for Improved Manufacturability

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Kunal Mhapsekar ◽  
Matthew McConaha ◽  
Sam Anand
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Experimental Validation ◽  
Manufacturing Processes ◽  
Manufacturing Constraints ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
And Topology ◽  
Am Processes

Additive manufacturing (AM) provides tremendous advantage over conventional manufacturing processes in terms of creative freedom, and topology optimization (TO) can be deemed as a potential design approach to exploit this creative freedom. To integrate these technologies and to create topology optimized designs that can be easily manufactured using AM, manufacturing constraints need to be introduced within the TO process. In this research, two different approaches are proposed to integrate the constraints within the algorithm of density-based TO. Two AM constraints are developed to demonstrate these two approaches. These constraints address the minimization of number of thin features as well as minimization of volume of support structures in the optimized parts, which have been previously identified as potential concerns associated with AM processes such as powder bed fusion AM. Both the manufacturing constraints are validated with two case studies each, along with experimental validation. Another case study is presented, which shows the combined effect of the two constraints on the topology optimized part. Two metrics of manufacturability are also presented, which have been used to compare the design outputs of conventional and constrained TO.

Application of Topology Optimization and Design for Additive Manufacturing Guidelines on an Automotive Component

2016 ◽  
Author(s):  
Sai Nithin Reddy K. ◽  
Vincent Maranan ◽  
Timothy W. Simpson ◽  
Todd Palmer ◽  
Corey J. Dickman
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Low Cost ◽  
Engineering Practice ◽  
Optimized Design ◽  
Design For Additive Manufacturing ◽  
Manufacturing Costs ◽  
Cost Structures ◽  
And Performance

Topology optimization is a well-established engineering practice to optimize the design and layout of parts to create lightweight and low-cost structures, which have historically been difficult, or impossible, to make. Additive Manufacturing (AM) provides the freedom to fabricate the complex and organic shapes that topology optimization often generates. In this paper we use topology optimization to create lightweight designs while conforming to additive manufacturing constraints related to overhanging features and unsupported surfaces when using metallic materials. More specifically, we use design for additive manufacturing (DfAM) rules along with topology optimization to study the tradeoffs between the weight of the part, support requirements, manufacturing costs, and performance. The case study entails redesigning an upright on the SAE Formula student racecar to reduce support structures and manufacturing and material cost when using Direct Metal Laser Sintering (DMLS). Manufacturing the optimized design without applying DfAM rules required support material up to 202.4% of the volume of the model. Using DfAM, the upright is redesigned and manufactured with supports requiring less than 15% of the volume of the model. The results demonstrate the challenges in achieving a balance between weight reduction, manufacturing costs, and factor of safety of the design.

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