Big Data, 3D Printing Technology, and Industry of the Future

Author:

Alabi Micheal Omotayo1

Affiliation:

1. University of the Witwatersrand, Johannesburg, South Africa

Abstract

This article describes how 3D printing technology, also referred to as additive manufacturing (AM), is a process of creating a physical object from 3-dimensional digital model layers upon layers. 3D printing technologies have been identified as an emerging technology of the 21st century and are becoming popular around the world with a wide variety of potential application areas such as healthcare, automotive, aerospace, manufacturing, etc. Big Data is a large amount of imprecise data in a variety of formats which is generated from different sources with high-speed. Recently, Big Data and 3D printing technologies is a new research area and have been identified as types of technologies that will launch the fourth industrial revolution (Industry 4.0). As Big Data and 3D printing technology is wide spreading across different sectors in the era of industry 4.0, the healthcare sector is not left out of the vast development in this field; for instance, the Big Data and 3D printing technologies providing needed tools to support healthcare systems to accumulate, manage, analyse large volume of data, early disease detection, 3D printed medical implant, 3D printed customized titanium prosthetic, etc. Therefore, this article presents the recent trends in 3D printing technologies, Big Data and Industry 4.0; including the benefits and the application areas of these technologies. Emerging and near future application areas of 3D printing, and possible future research areas in 3D printing and Big Data technologies as relating to industry 4.0.

Publisher

IGI Global

Subject

Rehabilitation,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine

Reference67 articles.

1. Agrawal, D., Bernstein, P., Bertino, E., Davidson, S., Dayal, U., Franklin, M., & Widom, J. (2012). Challenges and Opportunities with Big Data (white paper). Computing Research Association. Retrieved from http://cra.org/ccc/resources/ccc-led-whitepapers/

2. Big Data Visualization: Tools and Challenges.;S. M.Ali;2nd International Conference on Contemporary Computing and Informatics,2016

3. Allen, M. (2016). The Challenge of Big Data – It’s more than just big files. Retrieved 30 Oct. 2017 from https://pro2col.com/challenge-big-data-more-than-just-big-files/

4. AspireSys. (2017). Big Data with NoSQL (White Paper). Retrieved from www.aspiresys.com/WhitePapers/BigData_with_NoSQL_Whitepaper.pdf?pdf=nosql-whitepaper

5. BCG. (2016). The Boston Consulting Group. Sprinting to Value in Industry 4.0: Perspective from and Implications for U.S Manufacturers. Retrieved 30 Oct. 2017 from https://www.slideshare.net/TheBostonConsultingGroup/sprinting-to-value-in-industry-40

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