The DOI matches its Crossref record; 128 of the 128 references it cites were found in a registry or an index.
3D-printed sensors: Current progress and future challenges
Abstract
Abstract Due to the technological advances, sensors have found a significant role in different aspects of human life. The sensors have been fabricated via various manufacturing processes. Recently, additive manufacturing (AM) has become a common method for fabrication of a wide range of engineering components in many industries. This manufacturing method, commonly known as three-dimensional (3D) printing is based on melting and solidification that leads to production of a component with high dimensional accuracy and smooth surface finish. As precision and elegant techniques are needed in manufacturing of the sensors, AM has been utilized in fabrication of these parts in the last few years. In this study, we summarized and classified applications of different AM methods in manufacturing of sensors. In this context, we briefly reviewed and compared AM techniques and categorized 3D-printed sensors based on their applications. Moreover, fabrication of sensors via AM is explained in details, challenges and future prospect of this manufacturing process are discussed. Investigations on the performed studies proved that higher printing resolution, faster speed and higher efficiency are needed to reach a remarkable advance in the production of 3D-printed sensors. The presented data can be utilized not only for comparison, improvement and optimization of fabrication processes, but also is beneficial for next research in production of highly sensitive sensors.
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Cites
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Cited by
On the environmental impacts of 3D printing technology
Khosravani, M. R., & Reinicke, T. (2020) · Applied Materials Today · doi:10.1016/j.apmt.2020.100689 · Cited by 284
Self-citationMachine learning in predicting mechanical behavior of additively manufactured parts
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Metadata
- Authors
- Khosravani, M. R., & Reinicke, T.
- Venue
- Sensors and Actuators A: Physical
- Publisher
- Elsevier BV
- Published
- 2020-04
- Volume
- 305
- Pages
- 111916
- ISSN
- 0924-4247 (ISSN-L)
- OpenAlex
- W3007235325
- Cited by
- 331
- References
- 128
- FWCI
- 17.07
- Type
- journal article
- Language
- en
- Open access
- closed
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