Integration of Design for Manufacturing Methods With Topology Optimization in Additive Manufacturing

2017 ◽  
Vol 139 (6) ◽  
Author(s):  
Rajit Ranjan ◽  
Rutuja Samant ◽  
Sam Anand
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Design Methodology ◽  
Relevant Literature ◽  
Design Guidelines ◽  
Layer By Layer ◽  
Material Deposition ◽  
First Case ◽  
Improvement Method ◽  
Am Processes

Additive manufacturing (AM) processes are used to fabricate complex geometries using a layer-by-layer material deposition technique. These processes are recognized for creating complex shapes which are difficult to manufacture otherwise and enable designers to be more creative with their designs. However, as AM is still in its developing stages, relevant literature with respect to design guidelines for AM is not readily available. This paper proposes a novel design methodology which can assist designers in creating parts that are friendly to additive manufacturing. The research includes formulation of design guidelines by studying the relationship between input part geometry and AM process parameters. Two cases are considered for application of the developed design guidelines. The first case presents a feature graph-based design improvement method in which a producibility index (PI) concept is introduced to compare AM friendly designs. This method is useful for performing manufacturing validation of pre-existing designs and modifying it for better manufacturability through AM processes. The second approach presents a topology optimization-based design methodology which can help designers in creating entirely new lightweight designs which can be manufactured using AM processes with ease. Application of both these methods is presented in the form of case studies depicting design evolution for increasing manufacturability and associated producibility index of the part.

Design for Manufacturability in Additive Manufacturing Using a Graph Based Approach

2015 ◽  
Author(s):  
Rajit Ranjan ◽  
Rutuja Samant ◽  
Sam Anand
Keyword(s):  
Additive Manufacturing ◽  
Relevant Literature ◽  
Design Guidelines ◽  
Layer By Layer ◽  
Design Rules ◽  
Novel Approach ◽  
To Come ◽  
The Relationship ◽  
Am Processes ◽  
Complex Parts

Additive Manufacturing (AM) processes are used to fabricate complex parts using a layer by layer approach. This enables designers to be more creative with their designs and build parts which may be difficult to manufacture using conventional processes. However, as AM is in its infancy, relevant literature with respect to design guidelines for AM is not readily available. This research proposes a novel approach to implement design guidelines in AM using a systematic graph based approach. These design rules will assist designers to come up with efficient part designs that can be manufactured with minimum part errors. The design rules are formulated by studying the relationship between input part geometry and AM process parameters. A feature graph based design analysis method is proposed along with a Producibility Index (PI) which is used to compare the designs. Modifications in part design based on these rules and their comparison is presented in the form of three case studies.

scholarly journals A STRUCTURED APPROACH TO REDUCE DESIGN ITERATIONS IN ADDITIVE MANUFACTURING

2021 ◽  
Vol 1 ◽  
pp. 231-240
Author(s):  
Laura Wirths ◽  
Matthias Bleckmann ◽  
Kristin Paetzold
Keyword(s):  
Additive Manufacturing ◽  
Spare Parts ◽  
Design Guidelines ◽  
Final Part ◽  
Layer By Layer ◽  
Powder Bed ◽  
Batch Sizes ◽  
Manufacturing Technologies ◽  
Structured Approach ◽  
Design Freedom

AbstractAdditive Manufacturing technologies are based on a layer-by-layer build-up. This offers the possibility to design complex geometries or to integrate functionalities in the part. Nevertheless, limitations given by the manufacturing process apply to the geometric design freedom. These limitations are often unknown due to a lack of knowledge of the cause-effect relationships of the process. Currently, this leads to many iterations until the final part fulfils its functionality. Particularly for small batch sizes, producing the part at the first attempt is very important. In this study, a structured approach to reduce the design iterations is presented. Therefore, the cause-effect relationships are systematically established and analysed in detail. Based on this knowledge, design guidelines can be derived. These guidelines consider process limitations and help to reduce the iterations for the final part production. In order to illustrate the approach, the spare parts production via laser powder bed fusion is used as an example.

Optimization of Metallic Powder Filaments for Additive Manufacturing Extrusion (MEX)

2021 ◽  
Author(s):  
Fábio Silva Cerejo ◽  
Daniel Gatões ◽  
Teresa Vieira
Keyword(s):  
Additive Manufacturing ◽  
Low Cost ◽  
Metallic Powder ◽  
Powder Injection ◽  
Layer By Layer ◽  
Powder Injection Moulding ◽  
Powder Particles ◽  
Powder Content ◽  
Metallic Parts ◽  
Am Processes

Abstract Additive manufacturing (AM) of metallic powder particles has been establishing itself as sustainable, whatever the technology selected. Material Extrusion (MEX) integrates the ongoing effort to improve AM sustainability, in which low-cost equipment is associated with a decrease of powder waste during manufacturing. MEX has been gaining increasing interest for building 3D functional/structural metallic parts because it incorporates the consolidated knowledge from powder injection moulding/extrusion feedstocks into the AM scope—filament extrusion layer-by-layer. Moreover, MEX as an indirect process can overcome some of the technical limitations of direct AM processes (laser/electron-beam-based) regarding energy-matter interactions. The present study reveals an optimal methodology to produce MEX filament feedstocks (metallic powder, binder and additives), having in mind to attain the highest metallic powder content. Nevertheless, the main challenges are also to achieve high extrudability and a suitable ratio between stiffness and flexibility. The metallic powder volume content (vol.%) in the feedstocks was evaluated by the critical powder volume concentration (CPVC). Subsequently, the rheology of the feedstocks was established by means of the mixing torque value, which is related to the filament extrudability performance.

Advancements in Manufacturing Technology With Additive Manufacturing and Its Context With Industry 4.0

2021 ◽  
pp. 1-24
Author(s):  
Ganzi Suresh
Keyword(s):  
Additive Manufacturing ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Three Dimensional ◽  
Metal Alloys ◽  
Layer By Layer ◽  
Post Processing ◽  
Clear Insight ◽  
Am Processes ◽  
Insight Into

Additive manufacturing (AM) is also known as 3D printing and classifies various advanced manufacturing processes that are used to manufacture three dimensional parts or components with a digital file in a sequential layer-by-layer. This chapter gives a clear insight into the various AM processes that are popular and under development. AM processes are broadly classified into seven categories based on the type of the technology used such as source of heat (ultraviolet light, laser) and type materials (resigns, polymers, metal and metal alloys) used to fabricate the parts. These AM processes have their own merits and demerits depending upon the end part application. Some of these AM processes require extensive post-processing in order to get the finished part. For this process, a separate machine is required to overcome this hurdle in AM; hybrid manufacturing comes into the picture with building and post-processing the part in the same machine. This chapter also discusses the fourth industrial revolution (I 4.0) from the perspective of additive manufacturing.

scholarly journals Taking into account thermal residual stresses in topology optimization of structures built by additive manufacturing

2018 ◽  
Vol 28 (12) ◽  
pp. 2313-2366 ◽  
Author(s):  
Grégoire Allaire ◽  
Lukas Jakabčin
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Residual Stresses ◽  
Heat Fluxes ◽  
Powder Layer ◽  
Layer By Layer ◽  
Thermal Deformations ◽  
Thermal Residual Stresses ◽  
Structural Design Optimization ◽  
Manufacturing Techniques

We introduce a model and several constraints for shape and topology optimization of structures, built by additive manufacturing techniques. The goal of these constraints is to take into account the thermal residual stresses or the thermal deformations, generated by processes like Selective Laser Melting, right from the beginning of the structural design optimization. In other words, the structure is optimized concurrently for its final use and for its behavior during the layer-by-layer production process. It is well known that metallic additive manufacturing generates very high temperatures and heat fluxes, which in turn yield thermal deformations that may prevent the coating of a new powder layer, or thermal residual stresses that may hinder the mechanical properties of the final design. Our proposed constraints are targeted to avoid these undesired effects. Shape derivatives are computed by an adjoint method and are incorporated into a level set numerical optimization algorithm. Several 2D and 3D numerical examples demonstrate the interest and effectiveness of our approach.

Investigation of Parameter Spaces for Topology Optimization With Three-Dimensional Orientation Fields for Multi-Axis Additive Manufacturing

2020 ◽  
Vol 143 (5) ◽  
Author(s):  
Joseph R. Kubalak ◽  
Alfred L. Wicks ◽  
Christopher B. Williams
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Design Space ◽  
Mechanical Performance ◽  
Unit Length ◽  
Three Dimensions ◽  
Layer By Layer ◽  
Material Distribution ◽  
Orientation Fields ◽  
Material Orientation

Abstract The layer-by-layer deposition process used in material extrusion (ME) additive manufacturing results in inter- and intra-layer bonds that reduce the mechanical performance of printed parts. Multi-axis (MA) ME techniques have shown potential for mitigating this issue by enabling tailored deposition directions based on loading conditions in three dimensions (3D). Planning deposition paths leveraging this capability remains a challenge, as an intelligent method for assigning these directions does not exist. Existing literature has introduced topology optimization (TO) methods that assign material orientations to discrete regions of a part by simultaneously optimizing material distribution and orientation. These methods are insufficient for MA–ME, as the process offers additional freedom in varying material orientation that is not accounted for in the orientation parameterizations used in those methods. Additionally, optimizing orientation design spaces is challenging due to their non-convexity, and this issue is amplified with increased flexibility; the chosen orientation parameterization heavily impacts the algorithm’s performance. Therefore, the authors (i) present a TO method to simultaneously optimize material distribution and orientation with considerations for 3D material orientation variation and (ii) establish a suitable parameterization of the orientation design space. Three parameterizations are explored in this work: Euler angles, explicit quaternions, and natural quaternions. The parameterizations are compared using two benchmark minimum compliance problems, a 2.5D Messerschmitt–Bölkow–Blohm beam and a 3D Wheel, and a multi-loaded structure undergoing (i) pure tension and (ii) three-point bending. For the Wheel, the presented algorithm demonstrated a 38% improvement in compliance over an algorithm that only allowed planar orientation variation. Additionally, natural quaternions maintain the well-shaped design space of explicit quaternions without the need for unit length constraints, which lowers computational costs. Finally, the authors present a path toward integrating optimized geometries and material orientation fields resulting from the presented algorithm with MA–ME processes.

Design for Fiber-Reinforced Additive Manufacturing

2015 ◽  
Vol 137 (11) ◽  
Author(s):  
Hauke Prüß ◽  
Thomas Vietor
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
Design Methodology ◽  
Fiber Reinforced ◽  
Reinforcing Fibers ◽  
Rapid Production ◽  
3D Printers ◽  
Composite Production ◽  
Faster Development ◽  
Am Processes

The continuously decreasing life cycle of modern products leads to new challenges for product development. Additive manufacturing (AM) processes are able to support faster development by rapid production of samples and prototypes. However, the material properties of components produced by common (plastic-) 3D-printers are often insufficient for functional prototyping. A well-established way to improve the properties of plastics is the embedding of reinforcing fibers. Thus, this paper shows a method for fiber-reinforced 3D-printing. Through this combination, several restrictions of conventional composite production can be eased and additional freedoms of design are gained. To support the design of such parts, an adapted design methodology for fiber-reinforced 3D-printing is developed.

Build Direction for Improved Process Plan in Multi-Material Additive Manufacturing

2014 ◽  
Author(s):  
Bashir Khoda
Keyword(s):  
Additive Manufacturing ◽  
Material Object ◽  
Layer By Layer ◽  
Multiple Features ◽  
Process Plan ◽  
Material Deposition ◽  
Heterogeneous Object ◽  
Build Time ◽  
Material Process ◽  
Manufacturing Techniques

Current additive manufacturing processes mostly accustomed with mono-material process plan algorithm to build object layer by layer. However, building a multi-material or heterogeneous object with an additive manufacturing system is fairly new but emerging concept. Unlike mono-material object, heterogeneous object contains multiple features or inhomogeneous architecture and can be decomposed into two dimensional heterogeneous layers with islands where each island represents associated feature’s properties. The material deposition path-plan in such multi-feature/multi-contour layers requires more resources and may affect the part integrity, quality, and build time. A novel framework is presented in this paper to determine the optimum build direction for heterogeneous object by differentiating the slice based on the resources requirement. Slices are bundled based on the heterogeneity and the effect of build directions are quantified considering the feature characteristics and manufacturing attributes. The proposed methodology is illustrated by examples with 50% or more homogeneous slices along the optimum build direction. The outcome would certainly benefit the process plan for multi-material additive manufacturing techniques.

scholarly journals Analysis and characterization of additive manufacturing processes

2021 ◽  
Vol 13 (4) ◽  
pp. 167-180
Author(s):  
Andra TOFAN-NEGRU ◽  
Cristian BARBU ◽  
Amado STEFAN ◽  
Ioana-Carmen BOGLIS
Keyword(s):  
Additive Manufacturing ◽  
Complex Geometry ◽  
Cutting Tools ◽  
Manufacturing Processes ◽  
Layer By Layer ◽  
Advantages And Disadvantages ◽  
Finishing Processes ◽  
Short Time ◽  
Physical Phenomena ◽  
Am Processes

Recently, additive manufacturing (AM) processes have expanded rapidly in various fields of the industry because they offer design freedom, involve layer-by-layer construction from a computerized 3D model (minimizing material consumption), and allow the manufacture of parts with complex geometry (thus offering the possibility of producing custom parts). Also, they provide the advantage of a short time to make the final parts, do not involve the need for auxiliary resources (cutting tools, lighting fixtures or coolants) and have a low impact on the environment. However, the aspects that make these technologies not yet widely used in industry are poor surface quality of parts, uncertainty about the mechanical properties of products and low productivity. Research on the physical phenomena associated with additive manufacturing processes is necessary for proper control of the phenomena of melting, solidification, vaporization and heat transfer. This paper addresses the relevant additive manufacturing processes and their applications and analyzes the advantages and disadvantages of AM processes compared to conventional production processes. For the aerospace industry, these technologies offer possibilities for manufacturing lighter structures to reduce weight, but improvements in precision must be sought to eliminate the need for finishing processes.

A Graph Theoretic Approach for Near Real-Time Prediction of Part-Level Thermal History in Metal Additive Manufacturing Processes

2019 ◽  
Author(s):  
Reza Yavari ◽  
Kevin D. Cole ◽  
Prahalad Rao
Keyword(s):  
Finite Element Analysis ◽  
Heat Flux ◽  
Finite Element ◽  
Graph Theory ◽  
Additive Manufacturing ◽  
Layer By Layer ◽  
Theory Approach ◽  
Element Analysis ◽  
Part Quality ◽  
Am Processes

Abstract The goal of this work is to predict the effect of part geometry and process parameters on the instantaneous spatial distribution of heat, called the heat flux or thermal history, in metal parts as they are being built layer-by-layer using additive manufacturing (AM) processes. In pursuit of this goal, the objective of this work is to develop and verify a graph theory-based approach for predicting the heat flux in metal AM parts. This objective is consequential to overcome the current poor process consistency and part quality in AM. One of the main reasons for poor part quality in metal AM processes is ascribed to the heat flux in the part. For instance, constrained heat flux because of ill-considered part design leads to defects, such as warping and thermal stress-induced cracking. Existing non-proprietary approaches to predict the heat flux in AM at the part-level predominantly use mesh-based finite element analyses that are computationally tortuous — the simulation of a few layers typically requires several hours, if not days. Hence, to alleviate these challenges in metal AM processes, there is a need for efficient computational thermal models to predict the heat flux, and thereby guide part design and selection of process parameters instead of expensive empirical testing. Compared to finite element analysis techniques, the proposed mesh-free graph theory-based approach facilitates layer-by-layer simulation of the heat flux within a few minutes on a desktop computer. To explore these assertions we conducted the following two studies: (1) comparing the heat diffusion trends predicted using the graph theory approach, with finite element analysis and analytical heat transfer calculations based on Green’s functions for an elementary cuboid geometry which is subjected to an impulse heat input in a certain part of its volume, and (2) simulating the layer-by-layer deposition of three part geometries in a laser powder bed fusion metal AM process with: (a) Goldak’s moving heat source finite element method, (b) the proposed graph theory approach, and (c) further comparing the heat flux predictions from the last two approaches with a commercial solution. From the first study we report that the heat flux trend approximated by the graph theory approach is found to be accurate within 5% of the Green’s functions-based analytical solution (in terms of the symmetric mean absolute percentage error). Results from the second study show that the heat flux trends predicted for the AM parts using graph theory approach agrees with finite element analysis with error less than 15%. More pertinently, the computational time for predicting the heat flux was significantly reduced with graph theory, for instance, in one of the AM case studies the time taken to predict the heat flux in a part was less than 3 minutes using the graph theory approach compared to over 3 hours with finite element analysis. While this paper is restricted to theoretical development and verification of the graph theory approach for heat flux prediction, our forthcoming research will focus on experimental validation through in-process sensor-based heat flux measurements.

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