Sponsor
Lawrence Funke, Ph. D
Ohio Northern University
Mechanical Engineering
l-funke@onu.edu
Advisor(s)
Lawrence Funke, Ph. D
Ohio Northern University
Mechanical Engineering
l-funke@onu.edu
Document Type
Poster
Start Date
24-4-2020 9:00 AM
Abstract
Fused deposition modeling (FDM) additive manufacturing, while versatile, has performance limitations in certain geometries, such as arcs, and holes. Iterative Learning Control (ILC) is good at accounting for disturbances to a system that are constant, but difficult to model and correct. Since the printer is doing repetitive actions, but not producing accurate parts, it is thought that ILC could be used to compensate for the disturbances thus improving accuracy. In order to start the development of the control system it was first necessary to get a baseline for the printer and scanner. Based on the initial results of the testing it was concluded that both the printer and scanner were a source of error and thus would both need to be accounted for by the ILC. This error can be attributed to, on the printer side of things, uneven cooling, manufacturing imperfections, and even the way a G-Code file is made, and, on the scanner side of things, the capture resolution, and alignment imperfections. The ultimate goal of the research and development of the ILC is to allow for inexpensive “RepRap” machines to produce parts with a level of accuracy that is closer to high end industrial FDM machines.
Recommended Citation
Opara, Matthew N., "The Use of Iterative Learning Control to Improve the Accuracy of Additive Manufacturing" (2020). ONU Student Research Colloquium. 20.
https://digitalcommons.onu.edu/student_research_colloquium/2020/posters/20
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Available to ONU community via local IP address and ONU login.
The Use of Iterative Learning Control to Improve the Accuracy of Additive Manufacturing
Fused deposition modeling (FDM) additive manufacturing, while versatile, has performance limitations in certain geometries, such as arcs, and holes. Iterative Learning Control (ILC) is good at accounting for disturbances to a system that are constant, but difficult to model and correct. Since the printer is doing repetitive actions, but not producing accurate parts, it is thought that ILC could be used to compensate for the disturbances thus improving accuracy. In order to start the development of the control system it was first necessary to get a baseline for the printer and scanner. Based on the initial results of the testing it was concluded that both the printer and scanner were a source of error and thus would both need to be accounted for by the ILC. This error can be attributed to, on the printer side of things, uneven cooling, manufacturing imperfections, and even the way a G-Code file is made, and, on the scanner side of things, the capture resolution, and alignment imperfections. The ultimate goal of the research and development of the ILC is to allow for inexpensive “RepRap” machines to produce parts with a level of accuracy that is closer to high end industrial FDM machines.