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Lattice structures with different desired physical properties are promising for a broad spectrum of applications. The availability of additive manufacturing (AM) technology has relaxed the fabricating limitation of lattice structures. However, manufacturing constraints still exist for AM-fabricated lattice structures, which have a significant influence on the printing quality and mechanical properties of lattice struts. In this paper, a design and optimization strategy is proposed for lattice structures with the consideration of manufacturability to ensure desired printing quality. The concept of manufacturable element is used to link the design and manufacturing process. A meta-model is constructed by experiments and the artificial neural network to obtain the manufacturing constraints. Sizes of struts are optimized by a bidirectional evolutionary structural optimization-based algorithm with these manufacturing constraints. An arm of quadcopter is redesigned and optimized to validate the proposed method. Its result shows that optimized heterogeneous lattice structures can improve the stiffness of the model compared to the homogeneous lattice structure and the original design. Both the Von-Mises stress and the maximum displacement are reduced without increasing the weight of designed part. And by considering the manufacturability constraints, the optimized design has been successfully fabricated by the selected additive manufacturing process. Note to Practitioners—Lattice structures might fail to be fabricated by the additive manufacturing technique if the designed model exceeds the processability of the machine. Our approach has the capability of considering the manufacturing constraints in the design and optimization process. We conducted experiments to investigate the manufacturability and proposed a method that can give the domain of the design variables for a selected manufacturing process. And we also designed an algorithm that can optimize the lattice structure inside the domain of design variables. It ensures that the lattice model can be successfully fabricated by the selected process and the performance is dramatically increased compared to the original design. Engineers can use our approach to optimize the lattice structure automatically without knowing the knowledge of optimization and manufacturability. [ABSTRACT FROM AUTHOR]

Mesoscale cellular structures with different desired physical properties are promising for a broad spectrum of applications. The availability of Additive Manufacturing (AM) technology has significantly relaxed the fabricating limitation of cellular structures. It enables the design of cellular structure with complex cell topologies and relative density distribution. In this paper, a multifunctional design method for heterogeneous cellular structures is proposed. To introduce this method, Function-Performance-Property-Design parameter model is proposed at first. This proposed model can help designers to analyze the complex relations between focused functions and their related design parameters. Based on the proposed F-P-P-D model, the template of compromise Decision Support Problem (DSP) is applied to generate the optimization formulation which can generally consider the performances defined for several different functions. To solve the defined optimization problem, a multifunctional design simulation infrastructure is proposed for the designed heterogeneous cellular structures. Based on this simulation infrastructure, both the value of the objective function and its gradients can be evaluated. Then, Sequential Quadratic Programming (SQP) solver can be applied to solve the defined optimization formulation. The optimal relative density of cellular structures can be achieved and converted to the heterogeneous cellular structures at the end. A case study is provided at the end of this paper. For this case study, two different cell topologies and several different combinations of optimization parameters are used. A brief discussion is made to conclude the effects of cell topologies and other optimization parameters on the optimization results. Generally, the result of this design case validates the efficiency of the proposed design method. This method provides a useful design tool for users to take advantage of heterogeneous cellular structures for multifunctional purposes. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) also known as 3D printing technology has drawn increasing attention from the industrial world. It provides the capability of freeform fabrication to achieve high complexity as well as significant reduction of a supply chain which further enhances the profit margin for manufacturers. However, while claiming on the advantage on the environmental aspect, there is very limited research on the environmental impact of AM technologies. Most of existing environmental assessment models for AM processes are developed based on a general Life Cycle Assessment (LCA) framework. Due to the limited scope and boundary of these models, design results are usually taken as the input. These existing models may work well for traditional manufacturing processes. However, when it comes to AM process, these methods are no longer valid, since the design freedoms which may have a great impact on sustainability are always neglected. To deal with this issue, a general framework which can integrate a design stage in LCA for minimizing the product environmental impact of AM process in particular for binder-jetting process is proposed. The detailed description of each major stage of the proposed framework is presented. This framework has been applied to evaluate the environmental impact of fabricating an engine bracket by binder-jetting process. In this case study, a comparison of environmental impact between CNC and binder-jetting fabrication process is made. The result shows that binder-jetting consumes significantly less energy and produce less CO 2 to produce a topologically optimized part than CNC milling for the same product. This case study demonstrates a key role of design optimization in the proposed framework. This proposed framework can be further modified for other typical AM process in the future. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to provide a comprehensive review of the state-of–the-art design methods for additive manufacturing (AM) technologies to improve functional performance.Design/methodology/approach In this survey, design methods for AM to improve functional performance are divided into two main groups. They are design methods for a specific objective and general design methods. Design methods in the first group primarily focus on the improvement of functional performance, while the second group also takes other important factors such as manufacturability and cost into consideration with a more general framework. Design methods in each groups are carefully reviewed with discussion and comparison.Findings The advantages and disadvantages of different design methods for AM are discussed in this paper. Some general issues of existing methods are summarized below: most existing design methods only focus on a single design scale with a single function; few product-level design methods are available for both products’ functionality and assembly; and some existing design methods are hard to implement for the lack of suitable computer-aided design software.Practical implications This study is a useful source for designers to select an appropriate design method to take full advantage of AM.Originality/value In this survey, a novel classification method is used to categorize existing design methods for AM. Based on this classification method, a comprehensive review is provided in this paper as an informative source for designers and researchers working in this field. [ABSTRACT FROM AUTHOR]

Unlike traditional manufacturing methods, additive manufacturing can produce parts with complex geometric structures without significant increases in fabrication time and cost. One application of additive manufacturing technologies is the fabrication of customized lattice-skin structures which can enhance performance of products while minimizing material or weight. In this paper, a novel design method for the creation of periodic lattice structures is proposed. In this method, Functional Volumes (FVs) and Functional Surfaces (FSs) are first determined based on an analysis of the functional requirements. FVs can be further decomposed into several sub-FVs. These sub-FVs can be divided into two types: FV with solid and FV with lattice. The initial design parameters of the lattice are selected based on the proposed guidelines. Based on these parameters, a kernel based lattice frame generation algorithm is used to generate lattice wireframes within the given FVs. At last, traditional bidirectional evolutionary structural optimization is modified to optimize distribution of lattice struts’ thickness. The design method proposed in this paper is validated through a case study, and provides an important foundation for the wide adoption of additive manufacturing technologies in the industry. [ABSTRACT FROM AUTHOR]

Advanced manufacturing methods like multi-material additive manufacturing are enabling realization of multiscale materials with intricate spatially varying microstructures and thus, material properties. This blurs the boundary between material and structure, paving the way to lighter, stiffer, and stronger structures. Taking advantage of these tunable multiscale materials warrants development of novel design methods that effectively marry the concepts of material and structure. We propose such a design to manufacture workflow and demonstrate it with laminated continuous fiber-reinforced composites that possess variable stiffness enabled by spatially varying microstructure. This contrasts with traditional fiber-reinforced composites which typically have a fixed, homogenous microstructure and thus constant stiffness. The proposed workflow includes three steps: (1) Design automation—efficient synthesis of an optimized multiscale design with microstructure homogenization enabling efficiency, (2) Material compilation—interpretation of the homogenized design lacking specificity in microstructural detail to a manufacturable structure, and (3) Digital manufacturing—automated manufacture of the compiled structure. We adapted multiscale topology optimization, a mesh parametrization-based algorithm and voxel-based multimaterial jetting for these three steps, respectively. We demonstrated that our workflow can be applied to arbitrary 2D or 3D surfaces. We validated the complete workflow with experiments on two simple planar structures; the results agree reasonably well with simulations. [ABSTRACT FROM AUTHOR]

Lightweight cellular structure generation and topology optimization are common design methodologies in additive manufacturing. In this work, we present a novel optimization strategy for designing functionally graded cellular structures with desired mechanical properties. This approach is mainly by generating variable-density gyroid structure and then performing graded structure optimization. Firstly, the geometric properties of the original gyroid structures are analyzed, and the continuity and connectivity of the structures are optimized by adding a penalty function. Then, a homogenization method is used to obtain mechanical properties of gyroid-based cellular structures through a scaling law as a function of their relative densities. Secondly, the scaling law is added directly into the structure optimization algorithm to compute the optimal density distribution in part being optimized. Thirdly, the density mapping and interpolation approach are used to map the output of structure optimization into the parametric gyroid structure which results in an optimum lightweight lattice structure with uniformly varying densities across the design space. Lastly, the effectiveness and robustness of the optimized results are analyzed through finite element analysis and experiments. [ABSTRACT FROM AUTHOR]