Additive manufacturing – A new challenge for automation and robotics

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Abstract

Additive manufacturing (AM) is a rapidly growing technology descended from the first stereolithography systems. AM describes a variety of material deposition technologies for forming objects in a digital manner layer-by-layer under computer control. Now commonly known as 3D printing, AM quickly branched out into several key directions – material extrusion, sheet lamination, direct energy deposition, vat polymerization, powder bed fusion, binder jetting, and material jetting. The common factor in all AM branches is a foundation in robotics and automation. While most of the mechanical 3D printing structures are based on simple gantry systems, there are Gough-Stewart platforms and, more recently, six or more DoF manipulator-based systems that have been developed. Currently available commercial systems are based on open-loop control with minimum sensing capabilities; the latest systems in development are starting to take advantage of complex feedback loops and layers of advanced sensing and data logging. The Manufacturing Demonstration Facility of Oak Ridge National Laboratory is leading the efforts in applying advanced robotics in the creation of large-scale 3D printers. The recent demonstration of an additively manufactured excavator at the CONEXPO 2017 exhibition in Las Vegas showed that the use of cutting edge robotics and automation is essential for the next generation of additive systems. The future of AM will heavily rely on advanced robotics, machine learning, and the internet of things. This paper summarizes progress in AM; presents the practical aspects, challenges, and lessons learned in developing robotic-based AM systems; and outlines the needs and future directions of robotics for AM.

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Nycz, A., Noakes, M., & Cader, M. (2018). Additive manufacturing – A new challenge for automation and robotics. In Advances in Intelligent Systems and Computing (Vol. 743, pp. 3–13). Springer Verlag. https://doi.org/10.1007/978-3-319-77179-3_1

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