Complete Schedule
Presentation Type
Oral Presentation (UNI Access Only)
Abstract
Background of problem
- Creation of metal parts by molds
- Burnout process has an inconsistent and unknown time
- Can vary with furnace specifications
- Temperature and Oxygen Level
- Can vary by pattern itself
- Shape and Material
Start Date
8-4-2025 12:30 PM
End Date
8-4-2025 12:45 PM
Faculty Advisor
Jin Zhu
Department
Department of Applied Engineering and Technical Management
Student Type
Graduate Student
Copyright
©2025 Samuel Bast
File Format
application/pdf
Recommended Citation
Bast, Samuel, "Investment Casting AM Burnout Time Identification and Usage with Machine Learning" (2025). INSPIRE Student Research and Engagement Conference. 9.
https://scholarworks.uni.edu/csbsresearchconf/2025/all/9
Apr 8th, 12:30 PM
Apr 8th, 12:45 PM
Investment Casting AM Burnout Time Identification and Usage with Machine Learning
Background of problem
- Creation of metal parts by molds
- Burnout process has an inconsistent and unknown time
- Can vary with furnace specifications
- Temperature and Oxygen Level
- Can vary by pattern itself
- Shape and Material
Comments
This entry was a part of the following session: