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1 – 2 of 2Mehrshad Mehrpouya, Daniel Tuma, Tom Vaneker, Mohamadreza Afrasiabi, Markus Bambach and Ian Gibson
This study aims to provide a comprehensive overview of the current state of the art in powder bed fusion (PBF) techniques for additive manufacturing of multiple materials. It…
Abstract
Purpose
This study aims to provide a comprehensive overview of the current state of the art in powder bed fusion (PBF) techniques for additive manufacturing of multiple materials. It reviews the emerging technologies in PBF multimaterial printing and summarizes the latest simulation approaches for modeling them. The topic of “multimaterial PBF techniques” is still very new, undeveloped, and of interest to academia and industry on many levels.
Design/methodology/approach
This is a review paper. The study approach was to carefully search for and investigate notable works and peer-reviewed publications concerning multimaterial three-dimensional printing using PBF techniques. The current methodologies, as well as their advantages and disadvantages, are cross-compared through a systematic review.
Findings
The results show that the development of multimaterial PBF techniques is still in its infancy as many fundamental “research” questions have yet to be addressed before production. Experimentation has many limitations and is costly; therefore, modeling and simulation can be very helpful and is, of course, possible; however, it is heavily dependent on the material data and computational power, so it needs further development in future studies.
Originality/value
This work investigates the multimaterial PBF techniques and discusses the novel printing methods with practical examples. Our literature survey revealed that the number of accounts on the predictive modeling of stresses and optimizing laser scan strategies in multimaterial PBF is low with a (very) limited range of applications. To facilitate future developments in this direction, the key information of the simulation efforts and the state-of-the-art computational models of multimaterial PBF are provided.
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Abstract
Purpose
This study aims to introduce the DoraHand, and the basic capability and performance have been verified in this paper. Besides the idea of sharing modular design and sensor design, the authors want to deliver an affordable and practical dexterous hand to the research area to contribute to the robotic manipulation area.
Design/methodology/approach
This paper introduced the DoraHand, a novel scalable and practical modular dexterous hand, which, adopting modular finger and palm design, fully actuated joint and tactile sensors, can improve the dexterity for robotic manipulation and lower the complexity of maintenance. A series of experiments are delivered to verify the performance of the hand and sensor module.
Findings
The parameters of the DoraHand are verified and suitable for the research of robotics manipulation area, the sensing capability has been tested with the static experiment and the slip prediction algorithm. And, the advantage of modular design and extensible interface have been verified by the real application.
Research limitations/implications
The authors continue improving the DoraHand and extend it to more different applications. The authors want to make the DoraHand as a basic research platform in the robotic manipulation area.
Practical implications
The DoraHand has been sent to more than ten different research institutes for different research applications. The authors continue working on this hand for better performance, easier usage and more affordability.
Social implications
This kind of dexterous hand can help researchers get rid of complex physical issues and pay more attention to the algorithm part; it can help to make robotic manipulation work more popular.
Originality/value
The key design in the DoraHand is the modular finger and sensing module. With the special design in mechanical and electrical parts, the authors build reliable hardware and can support the diversity requirement in the robotic manipulation area. The hand with tactile sensing capability can be used in more research and applications with its extensibility.
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