Additive manufacturing integration with topology optimization methodology for innovative product design

2017 ◽  
Vol 93 (1-4) ◽  
pp. 467-479 ◽  
Author(s):  
Teresa Primo ◽  
Maurizio Calabrese ◽  
Antonio Del Prete ◽  
Alfredo Anglani
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Product Design ◽  
Innovative Product ◽  
Optimization Methodology

Design Tool for Topology Optimization of Self Supporting Variable Density Lattice Structures for Additive Manufacturing

2021 ◽  
pp. 1-36
Author(s):  
Matthew McConaha ◽  
Vysakh Venugopal ◽  
Sam Anand
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Lattice Structure ◽  
Variable Density ◽  
Design Tool ◽  
Lattice Structures ◽  
Interpolation Scheme ◽  
Void Space ◽  
Lattice Density ◽  
Optimization Methodology

Abstract Additive manufacturing (AM) allows for the inclusion of complicated geometric features that are impractical or impossible to manufacture by other means. Among such features is the collection of intricate and periodic strut-like geometries known as lattice structures. Lattice structures are desirable for their ability to provide stiffness through a large number of supporting members while employing void space within the geometry as a means to reduce part material volume. Strut thicknesses of every lattice in a part are generally not well optimized in order to maximize part stiffness, and often every lattice unit cell is identical throughout the part. This work presents a lattice density optimization methodology able to find the optimal graded lattice density distribution for maximizing the part stiffness and also improving the additive manufacturability of the part. The material property interpolation scheme used in SIMP optimization is replaced by a representative volume element (RVE)-based interpolation scheme that more accurately captures the material properties of the prescribed lattice structure at an arbitrary density. A filter has been developed that allows for the trimming of unnecessary lattices while simultaneously ensuring that the geometry remains self-supporting during the AM build process. This filter is incorporated seamlessly within the topology optimization routine. This increases the optimality of the resulting design compared to full-domain lattice filling and increases the viability of the design from a manufacturing standpoint compared to unconstrained lattice trimming.

scholarly journals Triple-Helix Structured Model Based on Problem-Knowledge-Solution Co-evolution for Innovative Product Design Process

2020 ◽  
Vol 33 (1) ◽  
Author(s):  
Qian Hui ◽  
Yan Li ◽  
Ye Tao ◽  
Hongwei Liu
Keyword(s):  
Product Design ◽  
Design Process ◽  
Design Problem ◽  
Triple Helix ◽  
Problem Solution ◽  
Innovative Product ◽  
Innovative Design ◽  
Structured Model ◽  
Knowledge Spaces ◽  
Product Design Process

AbstractA design problem with deficient information is generally described as wicked or ill-defined. The information insufficiency leaves designers with loose settings, free environments, and a lack of strict boundaries, which provides them with more opportunities to facilitate innovation. Therefore, to capture the opportunity behind the uncertainty of a design problem, this study models an innovative design as a composite solving process, where the problem is clarified and resolved from fuzziness to satisfying solutions by interplay among design problems, knowledge, and solutions. Additionally, a triple-helix structured model for the innovative product design process is proposed based on the co-evolution of the problem, solution, and knowledge spaces, to provide designers with a distinct design strategy and method for innovative design. The three spaces interact and co-evolve through iterative mappings, including problem structuring, knowledge expansion, and solution generation. The mappings carry the information processing and decision-making activities of the design, and create the path to satisfying solutions. Finally, a case study of a reactor coolant flow distribution device is presented to demonstrate the practicability of this model and the method for innovative product design.

scholarly journals A Shape Optimization Method for Part Design Derived from the Buildability Restrictions of the Directed Energy Deposition Additive Manufacturing Process

Designs ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 19
Author(s):  
Andreas K. Lianos ◽  
Harry Bikas ◽  
Panagiotis Stavropoulos
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Energy Deposition ◽  
Design Method ◽  
Current Trend ◽  
Internal Stresses ◽  
Material Distribution ◽  
Load Case ◽  
Design Elements ◽  
Industrial Sectors

The design methodologies and part shape algorithms for additive manufacturing (AM) are rapidly growing fields, proven to be of critical importance for the uptake of additive manufacturing of parts with enhanced performance in all major industrial sectors. The current trend for part design is a computationally driven approach where the parts are algorithmically morphed to meet the functional requirements with optimized performance in terms of material distribution. However, the manufacturability restrictions of AM processes are not considered at the primary design phases but at a later post-morphed stage of the part’s design. This paper proposes an AM design method to ensure: (1) optimized material distribution based on the load case and (2) the part’s manufacturability. The buildability restrictions from the direct energy deposition (DED) AM technology were used as input to the AM shaping algorithm to grant high AM manufacturability. The first step of this work was to define the term of AM manufacturability, its effect on AM production, and to propose a framework to estimate the quantified value of AM manufacturability for the given part design. Moreover, an AM design method is proposed, based on the developed internal stresses of the build volume for the load case. Stress tensors are used for the determination of the build orientation and as input for the part morphing. A top-down mesoscale geometric optimization is used to realize the AM part design. The DED Design for Additive Manufacturing (DfAM) rules are used to delimitate the morphing of the part, representing at the same time the freeform mindset of the AM technology. The morphed shape of the part is optimized in terms of topology and AM manufacturability. The topology optimization and AM manufacturability indicator (TMI) is introduced to screen the percentage of design elements that serve topology optimization and the ones that serve AM manufacturability. In the end, a case study for proof of concept is realized.

scholarly journals Topology Optimization for additive manufacturing with distortion constraints

2021 ◽  
Vol 386 ◽  
pp. 114095
Author(s):  
Grzegorz Misiun ◽  
Emiel van de Ven ◽  
Matthijs Langelaar ◽  
Hubert Geijselaers ◽  
Fred van Keulen ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing
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