The potential of additive manufacturing in the smart factory industrial 4.0: A review

Additive manufacturing (AM) or three-dimensional (3D) printing has introduced a novel production method in design, manufacturing, and distribution to end-users. This technology has provided great freedom in design for creating complex components, highly customizable products, and efficient waste minimization. The last industrial revolution, namely industry 4.0, employs the integration of smart manufacturing systems and developed information technologies. Accordingly, AM plays a principal role in industry 4.0 thanks to numerous benefits, such as time and material saving, rapid prototyping, high efficiency, and decentralized production methods. This review paper is to organize a comprehensive study on AM technology and present the latest achievements and industrial applications. Besides that, this paper investigates the sustainability dimensions of the AM process and the added values in economic, social, and environment sections. Finally, the paper concludes by pointing out the future trend of AM in technology, applications, and materials aspects that have the potential to come up with new ideas for the future of AM explorations

Flow-based fabrication: An integrated computational workflow for design and digital additive manufacturing of multifunctional heterogeneously structured objects

Structural hierarchy and material organization in design are traditionally achieved by combining discrete homogeneous parts into functional assemblies where the shape or surface is the determining factor in achieving function. In contrast, biological structures express higher levels of functionality on a finer scale through volumetric cellular constructs that are heterogeneous and complex. Despite recent advancements in additive manufacturing of functionally graded materials, the limitations associated with computational design and digital fabrication of heterogeneous materials and structures frame and limit further progress. Conventional computer-aided design tools typically contain geometric and topologic data of virtual constructs, but lack robust means to integrate material composition properties within virtual models. We present a seamless computational workflow for the design and direct digital fabrication of multi-material and multi-scale structured objects. The workflow encodes for and integrates domain-specific meta-data relating to local, regional and global feature resolution of heterogeneous material organizations. We focus on water-based materials and demonstrate our approach by additively manufacturing diverse constructs associating shape-informing variable flow rates and material properties to mesh-free geometric primitives. The proposed workflow enables virtual-to-physical control of constructs where structural, mechanical and optical gradients are achieved through a seamless design-to-fabrication tool with localized control. An enabling technology combining a robotic arm and a multi-syringe multi nozzle deposition system is presented. Proposed methodology is implemented and full-scale demonstrations are included

Optimal Design of Functionally Graded Parts

Several additive manufacturing processes are capable of fabricating three-dimensional parts with complex distribution of material composition to achieve desired local properties and functions. This unique advantage could be exploited by developing and implementing methodologies capable of optimizing the distribution of material composition for one-, two-, and three-dimensional parts. This paper is the first effort to review the research works on developing these methods. The underlying components (i.e., building blocks) in all of these methods include the homogenization approach, material representation technique, finite element analysis approach, and the choice of optimization algorithm. The overall performance of each method mainly depends on these components and how they work together. For instance, if a simple one-dimensional analytical equation is used to represent the material composition distribution, the finite element analysis and optimization would be straightforward, but it does not have the versatility of a method which uses an advanced representation technique. In this paper, evolution of these methods is followed; noteworthy homogenization approaches, representation techniques, finite element analysis approaches, and optimization algorithms used/developed in these studies are described; and most powerful design methods are identified, explained, and compared against each other. Also, manufacturing techniques, capable of producing functionally graded materials with complex material distribution, are reviewed; and future research directions are discussed

Multi-material additive manufacturing of electronics components: A bibliometric analysis

The study presents a bibliometric analysis of studies conducted on multi-materials printing of electronic com-ponents via additive manufacturing technologies. Using the R package and the associated biblioshiny, the study analyzed publications from Web of Science and Scopus. The study analyzed 405 research articles after removing 104 duplicates. The study applied performance analysis, keyword analysis, and network analysis. The perfor-mance analysis showed that the publications on multi-materials additive manufacturing are multi-disciplinary. Whilst the publications span almost three decades, most contributions started after 2015. The United States of America is the country with the highest production. The keyword analysis showed a changed focus before and after 2015. The trending topics show that the most recent trend is in the 'aerospace industry'. Finally, the thematic analysis shows that the emerging themes in the area are interfaces, moisture, diffusion, microstructure, mechanical properties, and powder metallurgy. These emerging themes are discussed as they are conceived as the future directions of multi-materials printing of electronic components and devices. The current trend of research focuses on understanding and improving the interfacial bonding between the various multi-material interfaces. Overcoming the weak interfacial bonding issues would improve the mechanical properties of multi-materials electronic components

Water-Based Robotic Fabrication: Large-Scale Additive Manufacturing of Functionally Graded Hydrogel Composites via Multichamber Extrusion

Additive manufacturing (AM) of regenerated biomaterials is in its infancy despite the urgent need for alternatives to fuel-based products and in spite of the exceptional mechanical properties, availability, and biodegradability associated with water-based natural polymers. This study presents water-based robotic fabrication as a design approach and enabling technology for AM of biodegradable hydrogel composites. Our research focuses on the combination of expanding the dimensions of the fabrication envelope, developing structural materials for additive deposition, incorporating material-property gradients, and manufacturing architectural-scale biodegradable systems. This work presents a robotically controlled AM system to produce biodegradable-composite objects combining natural hydrogels, such as chitosan and sodium alginate, with other organic aggregates. It demonstrates the approach by designing, building, and evaluating the mechanics and controls of a multichamber extrusion system. Finally, it provides evidence of large-scale composite objects fabricated by our technology that display graded properties and feature sizes ranging from micro- to macroscale. Fabricated objects may be chemically stabilized or dissolved in water and recycled within minutes. Applications include the fabrication of fully recyclable products or temporary architectural components such as tent structures with graded mechanical and optical properties. Proposed applications demonstrate environmental capabilities such as water-storing structures, hydration-induced shape forming, and product disintegration over time.Massachusetts Institute of Technology. Media Laboratory (Mediated Matter research group)Massachusetts Institute of Technology. Department of Mechanical engineering (Additive Manufacturing (2.S998), Spring 2014

A voxel-based method of constructing and skinning conformal and functionally graded lattice structures suitable for additive manufacturing

Additive Manufacturing (AM) enables the production of geometrically complex parts that are difficult to manufacture by other means. However, conventional CAD systems are limited in the representation of such parts. This issue is exacerbated when lattice structures are combined or embedded within a complex geometry. This paper presents a computationally efficient, voxel-based method of generating lattices comprised of practically any cell type that can conform to an arbitrary external geometry. The method of conforming involves the tessellation and trimming of unit cells that can leave ‘hanging’ struts at the surface, which is a possible point of weakness in the structure. A method of joining these struts to form an external two dimensional lattice, termed a ‘net-skin’ is also described. Traditional methods of manufacturing lattice structures generally do not allow variation of cell properties within a structure; however, additive manufacturing enables graded lattices to be generated that are potentially more optimal. A method of functionally grading lattices is, therefore, also described to take advantage of this manufacturing capability

Revolutionary additive manufacturing : an overview

Consumer demands are moving away from standardized to customized products, as such, the evolution of alternative manufacturing techniques has become imperative. Additive manufacturing (AM) is a process of building components layer by layer as against the traditional methods which are subtractive in nature. Though AM offers lots of advantages over traditional manufacturing techniques, its wide application is still however in the infancy phase. Despite all the benefits derived from AM technology, there are still a lot of unresolved issues with the technology that has hindered its performance thereby limiting its application to high tolerant jobs. This paper takes a look at some important AM technologies, some problems currently facing AM technology at large and proposes some solutions to these problems. A major known drawback in AM is poor dimensional accuracy and poor surface finish, only the layer height and melt pool temperature are controlled to solve this problem in the literature. The stair-stepping effect in adaptive manufacturing is rooted in a natural phenomenon of surface tension which is the cause of the poor surface finish and in combination with other factors is responsible for the poor dimensional accuracy. An adaptive controller is proposed for removing stair-stepping effect to improve the dimension accuracy, the surface finish and the mechanical properties of the components. Successful implementation of these proposed controllers will greatly improve the performance of AM technologies and also aid its wide application for end use products. Further research work is also suggested to improve the overall AM performance

From 3D Models to 3D Prints: an Overview of the Processing Pipeline

Due to the wide diffusion of 3D printing technologies, geometric algorithms for Additive Manufacturing are being invented at an impressive speed. Each single step, in particular along the Process Planning pipeline, can now count on dozens of methods that prepare the 3D model for fabrication, while analysing and optimizing geometry and machine instructions for various objectives. This report provides a classification of this huge state of the art, and elicits the relation between each single algorithm and a list of desirable objectives during Process Planning. The objectives themselves are listed and discussed, along with possible needs for tradeoffs. Additive Manufacturing technologies are broadly categorized to explicitly relate classes of devices and supported features. Finally, this report offers an analysis of the state of the art while discussing open and challenging problems from both an academic and an industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and Innovation action; Grant agreement N. 68044