Prediction and Control of Thermal History in Laser Powder Bed Fusion

The long-term research goal of this dissertation is to enable flaw-free production of metal parts using the laser powder bed fusion (LPBF) additive manufacturing (AM) process. As a step towards this long-term goal, the goal of this work is to predict and control the thermal history of an LPBF part. The thermal history is the spatiotemporal distribution of temperature in an LPBF part as it is created layer by layer. Thermal history is the primary cause of flaw formation in LPBF. To realize this goal, the objective of this dissertation is to establish and advance a novel thermal modeling method based on the concept of spectral graph theory, which is more than 10 times faster than existing finite element-based methods for the same level of accuracy. The central hypothesis is that physics-guided prediction, optimization, and control of thermal history mitigates flaw formation and enhances functionally critical properties of LPBF-processed parts when compared to parts produced without control of thermal history. The practical rationale and need for this work are as follows. LPBF is becoming increasingly prevalent due to its ability to fabricate complex structures that would otherwise be impossible with traditional subtractive and formative manufacturing processes. The freedom of geometry afforded by AM processes such as LPBF enables designers to place a stronger emphasis on design efficiency rather than the manufacturability of components. It also facilitates greater supply chain flexibility, reducing part lead times and costs. For example, making an aerospace part weighing just one kilogram with traditional subtractive and formative techniques requires processing 20 kilograms of raw material—a buy-to-fly ratio of 20:1—and lead times for new parts are often several months long. LPBF reduces the buy-to-fly ratio to less than 5:1, and the lead time is just a few weeks. Despite these advantages, LPBF has seen limited industry adoption and use, especially in safety-critical applications, due to the tendency of the process to form flaws. Approximately one in three parts are affected by flaws. Flaw formation leads to inconsistent part properties and can cause catastrophic failures in safety-critical aerospace, defense, and biomedical applications. Flaw formation in LPBF parts is mainly attributed to the thermal history. Thermal history, in turn, is influenced by complex design-process-material-machine interactions that require mathematical modeling. Rapid and accurate prediction of the thermal history can enable practitioners to avoid flaw formation and achieve desired part properties by optimizing the part design and process parameters before the part is printed. This dissertation leverages the graph theory modeling to address the burgeoning practical need for a rapid, accurate, and experimentally validated physics-based approach for mitigating flaw formation and ensuring part quality in LPBF

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Industrial and Systems Engineering

Department dc:contributor.department

Industrial and Systems Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2024

Author dc:creator

• Riensche, Alexander Ray

Chair dc:contributor.committeechair

• Rao, Prahalada Krishna

Committee members dc:contributor.committeemember

• Kong, Zhenyu
• Bansal, Manish
• Williams, Christopher Bryant

• Additive Manufacturing
• Thermal Modeling
• Graph Theory
• Process Control

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:41256

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/121102