Functional Performance Tailoring of Additively Manufactured Components via Topology Optimization

2017 ◽  
Author(s):  
John C. Steuben ◽  
John G. Michopoulos ◽  
Athanasios P. Iliopoulos ◽  
Andrew J. Birnbaum
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
High Performance ◽  
Functional Performance ◽  
Underwater Vehicle ◽  
Length Scale ◽  
Hand Tool ◽  
Component Shape ◽  
Future Work ◽  
Am Processes

The freedom of design that is afforded by Additive Manufacturing (AM) processes opens exciting possibilities for the production of lightweight, high performance components and structures. Consequently, in recent years the development of software tools to enable engineering design methods that exploit the unique features of AM has become a subject of increased research interest. In this paper we explore the use of Topology Optimization (TO) algorithms to tailor component shape in order to achieve the intended functionality of additively manufactured components at the macro length scale. We present two case studies: the first concerns the hierarchical nesting of functions in a hand tool, while the second covers the development of a metamaterial component substructure for an Uninhabited Underwater Vehicle (UUV) hull. We offer conclusions regarding the usefulness of TO techniques for the design of AM components, and a summary of future work, which we feel is necessary to improve such methodologies.

Multiscale Topology Optimization for Additively Manufactured Objects

2018 ◽  
Vol 18 (3) ◽  
Author(s):  
John C. Steuben ◽  
Athanasios P. Iliopoulos ◽  
John G. Michopoulos
Keyword(s):  
Topology Optimization ◽  
Energy Deposition ◽  
Multiple Scales ◽  
Precise Control ◽  
Hand Tool ◽  
Macro Scale ◽  
Performance Specifications ◽  
Future Work ◽  
Am Processes ◽  
Meso Scale

The precise control of mass and energy deposition associated with additive manufacturing (AM) processes enables the topological specification and realization of how space can be filled by material in multiple scales. Consequently, AM can be pursued in a manner that is optimized such that fabricated objects can best realize performance specifications. In the present work, we propose a computational multiscale method that utilizes the unique meso-scale structuring capabilities of implicit slicers for AM, in conjunction with existing topology optimization (TO) tools for the macro-scale, in order to generate structurally optimized components. The use of this method is demonstrated on two example objects including a load bearing bracket and a hand tool. This paper also includes discussion concerning the applications of this methodology, its current limitations, a recasting of the AM digital thread, and the future work required to enable its widespread use.

Towards Multiscale Topology Optimization for Additively Manufactured Components Using Implicit Slicing

2017 ◽  
Author(s):  
John C. Steuben ◽  
Athanasios P. Iliopoulos ◽  
John G. Michopoulos
Keyword(s):  
Topology Optimization ◽  
Complex Geometries ◽  
Generate Functional ◽  
Hand Tool ◽  
Macro Scale ◽  
Functional Features ◽  
Future Work ◽  
Functional Components ◽  
Am Processes ◽  
Meso Scale

Additive Manufacturing (AM) encompasses a set of fabrication technologies that are being used with increasing frequency in a wide variety of scientific and industrial pursuits. These technologies, which operate by successive additions of material to a domain, enable the manufacture of highly complex geometries that would otherwise be unrealizable. However, the material micro and meso-structures generated by AM processes differ remarkably from those that arise from conventional techniques and occasionally introduce unwanted functional features; this has been an obstacle to the use of AM in some applications. In the present work, we propose a multiscale method that utilizes the unique meso-scale structuring capabilities of implicit slicers for AM, in conjunction with existing topology optimization tools for the macro-scale, in order to generate functional components. The use of this method is demonstrated on the example of a hand tool. We discuss the applications of this methodology, its current limitations, and the future work required to enable its widespread use.

Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Paul Witherell ◽  
Shaw Feng ◽  
Timothy W. Simpson ◽  
David B. Saint John ◽  
Pan Michaleris ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Metal Powder ◽  
Manufacturing Process ◽  
Process Model ◽  
Model Development ◽  
Process Models ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Future Work ◽  
Am Processes

In this paper, we advocate for a more harmonized approach to model development for additive manufacturing (AM) processes, through classification and metamodeling that will support AM process model composability, reusability, and integration. We review several types of AM process models and use the direct metal powder bed fusion AM process to provide illustrative examples of the proposed classification and metamodel approach. We describe how a coordinated approach can be used to extend modeling capabilities by promoting model composability. As part of future work, a framework is envisioned to realize a more coherent strategy for model development and deployment.

Differential Performance Signature Qualification for Additively Manufactured Parts

2018 ◽  
Author(s):  
John G. Michopoulos ◽  
John C. Steuben ◽  
Athanasios P. Iliopoulos
Keyword(s):  
Additive Manufacturing ◽  
Graphical Representation ◽  
Functional Performance ◽  
Complex Objects ◽  
Aircraft Landing ◽  
Differential Performance ◽  
Aircraft Landing Gear ◽  
Am Processes ◽  
Comparison Measures ◽  
Quantities Of Interest

Additive Manufacturing (AM) technologies and associated processes, enable successive accretion of material to a domain, and permit manufacturing of highly complex objects which would otherwise be unrealizable. However, the material micro- and meso-structures generated by AM processes can differ remarkably from those arising from conventional manufacturing (CM) methods. Often, a consequence of this fact is the sub-standard functional performance of the produced parts that can limit the use of AM in some applications. In the present work, we propose a rapid functional qualification methodology for AM-produced parts based on a concept defined as differential Performance Signature Qualification (dPSQ). The concept of Performance Signature (PerSig) is introduced both as a vector of featured quantities of interest (QoIs), and a graphical representation in the form of radar or spider graph, representing the QoIs associated with the performance of relevant parts. The PerSigs are defined for both the prequalified CM parts and the AM-produced ones. Comparison measures are defined and enable the construction of differential PerSigs (dPerSig) in a manner that captures the differential performance of the AM part vs. the prequalified CM one. The dPerSigs enable AM part qualification based on how their PerSigs are different from those of prequalified CM parts. After defining the steps of the proposed methodology, we describe its application on a part of an aircraft landing gear assembly and demonstrate its feasibility.

Complex Solutions for Complex Problems? Exploring the Role of Design Task Choice on Learning, Design for Additive Manufacturing Use, and Creativity

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Rohan Prabhu ◽  
Scarlett R. Miller ◽  
Timothy W. Simpson ◽  
Nicholas A. Meisel
Keyword(s):  
Additive Manufacturing ◽  
Self Efficacy ◽  
Engineering Students ◽  
Educational Interventions ◽  
Problem Statement ◽  
Design Task ◽  
Complex Solutions ◽  
Future Work ◽  
Am Processes

Abstract The integration of additive manufacturing (AM) processes in many industries has led to the need for AM education and training, particularly on design for AM (DfAM). To meet this growing need, several academic institutions have implemented educational interventions, especially project- and problem-based, for AM education; however, limited research has explored how the choice of the problem statement influences the design outcomes of a task-based AM/DfAM intervention. This research explores this gap in the literature through an experimental study with 175 undergraduate engineering students. Specifically, the study compared the effects of restrictive and dual (restrictive and opportunistic) DfAM education, when introduced through design tasks that differed in the explicit use of design objectives and functional and manufacturing constraints in defining them. The effects of the intervention were measured through (1) changes in participant DfAM self-efficacy, (2) participants' self-reported emphasis on DfAM, and (3) the creativity of participants' design outcomes. The results show that the choice of the design task has a significant effect on the participants' self-efficacy with, and their self-reported emphasis on, certain DfAM concepts. The results also show that the design task containing explicit constraints and objectives results in participants generating ideas with greater uniqueness compared with the design task with fewer explicit constraints and objectives. These findings highlight the importance of the chosen problem statement on the outcomes of a DfAM educational intervention, and future work is also discussed.

Design for additive manufacturing: a comprehensive review of the tendencies and limitations of methodologies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Luis Lisandro Lopez Taborda ◽  
Heriberto Maury ◽  
Jovanny Pacheco
Keyword(s):  
Additive Manufacturing ◽  
Design Methodology ◽  
Functional Performance ◽  
Cost Evaluation ◽  
Product Management ◽  
Design For Additive Manufacturing ◽  
Content Type ◽  
Starting Point ◽  
The Subject ◽  
Future Work

Purpose There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective. Design/methodology/approach This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers. Findings Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions Originality/value The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.

Efficient Multi-Material Topology Optimization

2021 ◽  
pp. 275-292
Author(s):  
Amir M. Mirzendehdel ◽  
Krishnan Suresh
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Consumer Products ◽  
Simultaneous Optimization ◽  
Multiple Materials ◽  
Am Processes

This chapter focuses on generating optimized topologies using multiple materials. The interest in multi-material topology optimization (MMTO) stems from the well-recognized synergy between topology optimization (TO) and additive manufacturing (AM), where organic structures created through TO can be directly fabricated by a variety of AM processes. Given the rapidly increasing capabilities of AM, there is an opportunity to improve the performance of consumer products, biomedical, and aerospace components, through simultaneous optimization of topology and distribution of multiple materials.

scholarly journals Performance of wearables and the effect of user behavior in additive manufacturing process

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
JuYoun Kwon ◽  
Namhun Kim
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Process Parameters ◽  
Manufacturing Process ◽  
High Performance ◽  
Essential Role ◽  
User Behavior ◽  
Process Parameter ◽  
Am Processes

AbstractAdditive manufacturing (AM) which can be a suitable technology to personalize wearables is ideal for adjusting the range of part performance such as mechanical properties if high performance is not required. However, the AM process parameter can impact overall durability and reliability of the part. In this instance, user behavior can play an essential role in performance of wearables through the settings of AM process parameter. This review discusses parameters of AM processes influenced by user behavior with respect to performance required to fabricate AM wearables. Many studies on AM are performed regardless of the process parameters or are limited to certain parameters. Therefore, it is necessary to examine how the main parameters considered in the AM process affect performance of wearables. The overall aims of this review are to achieve a greater understanding of each AM process parameter affecting performance of AM wearables and to provide requisites for the desired performance including the practice of sustainable user behavior in AM fabrication. It is discussed that AM wearables with various performance are fabricated when the user sets the parameters. In particular, we emphasize that it is necessary to develop a qualified procedure and to build a database of each AM machine about part performance to minimize the effect of user behavior.

Implicit Slicing for Functionally Tailored Additive Manufacturing

2016 ◽  
Author(s):  
John C. Steuben ◽  
Athanasios P. Iliopoulos ◽  
John G. Michopoulos
Keyword(s):  
Additive Manufacturing ◽  
Functional Performance ◽  
Three Dimensional ◽  
Computationally Efficient ◽  
Geometric Transformations ◽  
Crucial Component ◽  
Implicit Approach ◽  
G Code ◽  
Manufacturing Software ◽  
Future Work

One crucial component of the additive manufacturing software toolchain is a class of geometric algorithms known as “slicers.” The purpose of the slicer is to compute a parametric toolpath defined at the mesoscale and associated g-code commands, which direct an additive manufacturing system to produce a physical realization of a three-dimensional input model. Existing slicing algorithms operate by application of geometric transformations upon the input geometry in order to produce the toolpath. In this paper we introduce an implicit slicing algorithm that computes mesoscale toolpaths from the level sets of heuristics-based or physics-based fields defined over the input geometry. This enables computationally efficient slicing of arbitrarily complex geometries in a straight forward fashion. The calculation of component “infill” is explored, as a process control parameter, due to its strong influence on the produced component’s functional performance. Several examples of the application of the proposed implicit slicer are presented. It is demonstrated — via proper experimentation — that the implicit slicer can produce a mesoscale structure leading to objects of superior functional performance such as greatly increased stiffness and ultimate strength without an increase of mass. We conclude with remarks regarding the strengths of the implicit approach relative to existing explicit approaches, and discuss future work required in order to extend the methodology.

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