Liquid Resins-Based Additive Manufacturing

2017 ◽  
Vol 05 (02) ◽  
pp. 1740004 ◽  
Author(s):  
Fei Wang ◽  
Fuke Wang

In this review, additive manufacturing technologies using liquid resins as materials are reviewed from the perspective of printing technologies and materials. Most importantly, recent progress of new printing technologies and printers as well as novel printing materials and their applications are summarized, based on which potential future research directions are discussed at the end of this review.

2020 ◽  
Vol 62 (5) ◽  
pp. 503-516
Author(s):  
Emel Taban ◽  
Olatunji Oladimeji Ojo

Abstract Flexible and digital manufacturing technologies like additive manufacturing (AM) have evolved as the future of modern manufacturing with the capability of obtaining multi-dimensional components and material functionality improvement. In the past decade, the additive manufacturing of steel has advanced into an effective approach for controlling local microstructure and fabricating hybrid build with tailored performance. As an emerging technology, there are still some challenges in the additive manufacturing of steel that need to be circumvented in order to attain the full potentials of this novel technology. This review paper examines the current state of additively manufactured steel as well as the associated microstructure, mechanical properties, and corrosion of as-built steel. An insight into further and future research directions is provided.


2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Jiankan Liao ◽  
Daniel R. Cooper

Abstract Additive manufacturing (AM) is widely recognized as a critical pillar of advanced manufacturing and is moving from the design shop to the factory floor. As AM processes become more popular, it is paramount that engineers and policymakers understand and then reduce their environmental impacts. This article structures the current work on the environmental impacts of metal powder bed processes: selective laser melting (SLM), direct metal laser sintering (DMLS), electron beam melting (EBM), and binder jetting (BJ). We review the potential benefits and pitfalls of AM in each phase of a part's lifecycle and in different application domains (e.g., remanufacturing and hybrid manufacturing). We highlight critical uncertainties and future research directions throughout. The environmental impacts of AM are sensitive to the specific production and use-phase context; however, several broad lessons can be extracted from the literature. Unlike in conventional manufacturing, powder bed production impacts are dominated by the generation of the direct energy (electricity) required to operate the AM machines. Combined with a more energy-intensive feedstock (metal powder), this means that powder bed production impacts are higher than in conventional manufacturing unless production volumes are very small (saving tool production impacts), and/or there are significant material savings through part light weighting or improved buy-to-fly ratios.


2020 ◽  
Vol 8 (42) ◽  
pp. 21947-21960 ◽  
Author(s):  
Peng Ding ◽  
Haitao Zhao ◽  
Tingshuai Li ◽  
Yongsong Luo ◽  
Guangyin Fan ◽  
...  

This review summarizes recent progress in the development of metal-based electrocatalysts for the reduction of CO2 to formic acid/formate. The current challenges and the future research directions of metal-based materials are also proposed.


Author(s):  
Jiankan Liao ◽  
Daniel R. Cooper

Abstract Additive manufacturing (AM) is widely recognized as a critical pillar of advanced manufacturing and is moving from the design shop to the factory floor. As AM processes become more popular, it is paramount that engineers and policymakers understand and then reduce their environmental impacts. This article structures the current work on the environmental impacts of metal powder bed processes: selective laser melting (SLM), direct metal laser sintering (DMLS), electron beam melting (EBM), and binder jetting (BJ). We review the potential benefits and pitfalls of AM in each phase of a part’s lifecycle and in different application domains (e.g., remanufacturing, hybrid manufacturing etc.). We highlight critical uncertainties and future research directions throughout. The environmental impacts of AM are sensitive to the specific production and use-phase context; however, several broad lessons can be extracted from the literature. Unlike in conventional manufacturing, powder bed production impacts are dominated by the generation of the direct energy (electricity) required to operate the AM machines. Combined with a more energy-intensive feedstock (metal powder) this means that powder bed production impacts are higher than in conventional manufacturing unless production volumes are very small (saving tool production impacts) and/or there are significant material savings through part light weighting or improved buy-to-fly ratios.


Author(s):  
Yuchu Qin ◽  
Qunfen Qi ◽  
Peizhi Shi ◽  
Paul J. Scott ◽  
Xiangqian Jiang

AbstractPart orientation is a critical task in the process of additive manufacturing product realisation. Recently, various computer-aided methods for this task have been presented in the literature. The coexistence of different methods generates a series of questions: What are the common characteristics of these methods? What are the specific characteristics of each method? What are the main issues in computer-aided part orientation for additive manufacturing currently? What are the potential research directions in this field in the future? To approach these questions, a review of the existing computer-aided part orientation methods for additive manufacturing is presented in this paper. This review starts with a clarification of a part orientation problem and a classification of the existing methods into two categories according to their process of solving the problem. An overview of the representative methods in each category is then carried out from the aspects of approaches for orientation search, generation, or selection, estimation of build orientation factors, determination of weights of factors, establishment of overall objective function, and demonstration of effectiveness. After that, a discussion about the main issues in computer-aided part orientation for additive manufacturing is documented based on the overview. Finally, a suggestion of some future research directions in this field is reported.


Author(s):  
Hassan Aldawsari ◽  

With the exponential rise in the use of drones anywhere anytime, malicious use by outlaws is increasing as well. This calls for protective, detective, preventive measures to counter these attacks. This paper aims to review literature on drone detection and classification that utilizes a myriad of modalities ranging from using thermal infrared sensors to radar detections. In addition, there is a summary of a detailed discussion on drone classification along with recent progress and development in drone detection using machine learning, all of which is performed in an attempt to identify means to thwart such attacks. Furthermore, some future research directions, related to this new field of study, are discussed.


Author(s):  
Laurent Itti ◽  
Ali Borji

This chapter reviews recent progress in computational modelling of visual attention. The authors start with early concepts and models, which have emphasized stimulus-driven guidance of attention towards salient objects in the visual world. They then present a taxonomy of the many different approaches which have emerged in recent research efforts. They then turn to the more complex problem of modelling top-down, task- and goal-driven influences on attention. While early top-down models have been more qualitative in nature, the authors describe several recent fully computational approaches that address top-down biasing in space, over features, and towards objects. This chapter finally provides an outlook and describes promising future research directions.


1993 ◽  
Vol 34 (4) ◽  
pp. 403-415 ◽  
Author(s):  
Steve E Humphries ◽  
France Mailly ◽  
Vilmundur Gudnason ◽  
Philippa Talmud

The Condor ◽  
2009 ◽  
Vol 111 (2) ◽  
pp. 211-225 ◽  
Author(s):  
Jay D. Carlisle ◽  
Susan K. Skagen ◽  
Barbara E. Kus ◽  
Charles van Riper ◽  
Kristina L. Paxton ◽  
...  

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