Additive manufacturing (AM) technology has been researched and developed for more than 20 years. Rather than removing materials, AM processes make three-dimensional parts directly from CAD models by adding materials layer by layer, offering the beneficial ability to build parts with geometric and material complexities that could not be produced by subtractive manufacturing processes. Through intensive research over the past two decades, significant progress has been made in the development and commercialization of new and innovative AM processes, as well as numerous practical applications in aerospace, automotive, biomedical, energy and other fields. This paper reviews the main processes, materials and applications of the current AM technology and presents future research needs for this technology.

Additive manufacturing: technology, applications and research needs

https://pure.hw.ac.uk/ws/files/10835033/final12Oct_11024_Melchels_et_al_Additive_Manufacturing_of_Tissues_and_Organs_R1_1_.pdf

Additive manufacturing of tissues and organs

Materials for additive manufacturing

Additive manufacturing (AM), the process of joining materials to make objects from three-dimensional (3D) model data, usually layer by layer, is distinctly a different form and has many advantages over traditional manufacturing processes. Commonly known as “3D printing,” AM provides a cost-effective and time-efficient way to produce low-volume, customized products with complicated geometries and advanced material properties and functionality. As a result of the 2013 National Science Foundation (NSF) Workshop on Frontiers of Additive Manufacturing Research and Education, this paper summarizes AM's current state, future potential, gaps and needs, as well as recommendations for technology and research, university–industry collaboration and technology transfer, and education and training.

Additive Manufacturing: Current State, Future Potential, Gaps and Needs, and Recommendations

Additive manufacturing techniques offer the potential to fabricate organized tissue constructs to repair or replace damaged or diseased human tissues and organs. Using these techniques, spatial variations of cells along multiple axes with high geometric complexity in combination with different biomaterials can be generated. The level of control offered by these computer-controlled technologies to design and fabricate tissues will accelerate our understanding of the governing factors of tissue formation and function. Moreover, it will provide a valuable tool to study the effect of anatomy on graft performance. In this review, we discuss the rationale for engineering tissues and organs by combining computer-aided design with additive manufacturing technologies that encompass the simultaneous deposition of cells and materials. Current strategies are presented, particularly with respect to limitations due to the lack of suitable polymers, and requirements to move the current concepts to practical application.

SFF processes have demonstrated the ability to produce parts with locally controlled composition. In the limit, processes such as 3D Printing can create parts with composition control on the length scale of 100 microns. To exploit this potential, new methods to model, exchange, and process parts with local composition need to be developed. An approach to modeling a part’s geometry, topology, and composition will be presented. This approach is based on subdividing the solid model into sub-regions and associating analytic composition blending functions with each region. These blending functions define the composition throughout the model as mixtures of the primary materials available to the SFF machine. Various design tools will also be presented, for example, specification of composition as a function of the distance from the surface of a part. Finally, the role of design rules specifying maximum concentrations and concentration gradients will be discussed. Introduction This research into modeling and designing components with locally controlled composition is part of a larger project funded by the National Science Foundation titled "The Distributed Design and Fabrication of Metal Parts and Tools by 3D Printing." The overall goal of this project is to identify the barriers preventing designers from accessing the unique and useful capabilities of SFF processes such as 3DP and provide solutions. One of the identified barriers is the inability for designers and manufacturers to work with models of graded compositions. To address this issue, we are researching methods to represent, design, exchange, and process these models with the intention of promoting the use and research of Local Composition Control through 3DP by a wider audience. Background: Local Composition Control (LCC) through 3D-Printing (3DP) Solid Freeform Fabrication (SFF) refers to a class of manufacturing processes that build objects in an additive fashion directly from a computer model. Although most build from a single material and in layers, a few SFF processes possess the capability to fabricate objects from multiple materials in a near point-wise fashion. The combination of these two features allows for the possibility of Local Composition Control (LCC) through which graded compositions can be manufactured from the base materials available to the SFF machine ,. One such SFF process capable of LCC is 3D Printing . Conventional 3DP manufactures a part by selectively binding powder together according to a computer model. The build cycle begins by spreading a layer of powder over the print bed. A print head then traverses the bed, selectively depositing binder over the regions corresponding to the interior of a slice of the Spread powder Apply binder Lower print bed Finished part @@@@@@ @@@@@@ @@@@@@ @@@@@@

Modeling and Designing Components with Locally Controlled Composition

Solid Freeform Fabrication (SFF) processes have demonstrated the ability to produce parts with locally controlled composition. In the limit, processes such as Three-Dimensional Printing(3DP) can create parts with composition to the length scale of 100 µm. To exploit this potential, new methods for automatic design of Functionally Gradient Material (FGM) parts need to be developed. This paper presents an efficient method for design and composition interrogation of FGM solids. The design tool based on the distance function from the surface of the part requires enhanced efficiency, and so does the interrogation of the part. The approach for improving efficiency includes preprocessing the model with bucket sorting and 3D digital distance transform, and an efficient point classification algorithm. Based on these tools, an efficient algorithm for distance function computation is developed for the design of FGM through distance to the surface of the part or distance to an .STL surface boundary. An efficient algorithm to evaluate composition at a point, along a ray or on a plane is also presented.

/pdf/algorithms-for-design-and-interrogation-of-functionally-45djqlu2a3.pdf

Algorithms for Design and Interrogation of Functionally Gradient Material Objects

The design of geometric shapes with physical constraints, such as hydrodynamic and aerodynamic constraints reflecting the functionality of the shapes, remains an important problem in cagd . This paper presents a method to design surfaces by incorporating physical constraints involving surface normal vectors. The design of functional surfaces is formulated as a linear problem using vector calculus. The final surface is an integral non-uniform B-spline surface, which is the solution of the linear equation system resulting from the least-squares fitting of the given grid points and the normal vectors at these points. The geometric design of propeller blade surfaces in conjunction with hydrodynamic analysis illustrates the method.

Geometric design of functional surfaces

Modeling and designing functionally graded material components for fabrication with local composition control

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Modeling and Designing Components with Locally Controlled Composition

Algorithms for Design and Interrogation of Functionally Gradient Material Objects

Geometric design of functional surfaces

Modeling and designing functionally graded material components for fabrication with local composition control