Sponsor
Lawrence Funke, PhD
Ohio Northern University
Mechanical Engineering
l-funke@onu.edu
Advisor(s)
Lawrence Funke, PhD
Ohio Northern University
Mechanical Engineering
l-funke@onu.edu
Document Type
Poster
Start Date
23-4-2021 9:00 AM
Abstract
Fused deposition modeling (FDM) additive manufacturing, while versatile, has performance limitations in certain geometries, such as arcs, and holes. Previous research led to iterative learning control (ILC) being selected as the control algorithm to procedurally generate parts that are more accurate than their prior counterparts. Since a baseline for the printer and scanner has been established, experiential testing with the ILC is in progress. Currently a “bounding box” approach is used to determine an error metric which is fed into the ILC to create the next iteration of printed parts. If this ILC approach is successful, the final part resulting from this iterative process of improvement will be more accurate, as it will more closely resemble the desired part, compared to the result achieved if only the default control approach was used. The ultimate goal of the research and development of the ILC is to allow for inexpensive desktop machines to produce parts with a level of accuracy that is comparable to high end industrial FDM machines.
Recommended Citation
Opara, Matthew N., "The Use of Iterative Learning Control to Improve the Accuracy of Additive Manufacturing" (2021). ONU Student Research Colloquium. 42.
https://digitalcommons.onu.edu/student_research_colloquium/2021/posters/42
Restricted
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. Previous research led to iterative learning control (ILC) being selected as the control algorithm to procedurally generate parts that are more accurate than their prior counterparts. Since a baseline for the printer and scanner has been established, experiential testing with the ILC is in progress. Currently a “bounding box” approach is used to determine an error metric which is fed into the ILC to create the next iteration of printed parts. If this ILC approach is successful, the final part resulting from this iterative process of improvement will be more accurate, as it will more closely resemble the desired part, compared to the result achieved if only the default control approach was used. The ultimate goal of the research and development of the ILC is to allow for inexpensive desktop machines to produce parts with a level of accuracy that is comparable to high end industrial FDM machines.