SUBJECT: Ph.D. Dissertation Defense
   
BY: Austen Thien
   
TIME: Friday, December 1, 2023, 12:00 p.m.
   
PLACE: MARC Building, 114
   
TITLE: Optimization and control for hybrid wire arc additive manufacturing
   
COMMITTEE: Dr. Christopher Saldana, Chair (ME)
Dr. Thomas Kurfess (ME)
Dr. Shreyes Melkote (ME)
Dr. Katherine Fu (ME)
Dr. Yao Xie (ISyE)
 

SUMMARY

Hybrid manufacturing is a promising manufacturing method that combines the geometrical accuracy of conventional subtractive manufacturing with the speed and material savings of additive manufacturing. Net shape components with functional surfaces can thus be created by cycling between the additive and subtractive operations. A popular and economic method of additive manufacturing is wire arc additive manufacturing (WAAM) which relies on arc-based deposition until a near net shape geometry is achieved. The selection of WAAM process parameters, particularly input deposition power and interlayer dwell time, greatly affects the as-deposited geometry. However, existing approaches to optimize and control as-deposited WAAM geometry are not grounded in the iterative nature of the hybrid manufacturing process and thus have not considered the full scope of optimal hybrid manufacturing process plans. Additionally, the relative instability of WAAM process conditions change throughout a build is not well understood. The proposed research will address this knowledge gap by pursuing the following research objectives: (1) understanding the impact of WAAM process parameters on process conditions and hybrid manufacturing production metrics, (2) development of a framework for model-based optimization of WAAM process parameters for hybrid manufacturing process planning, and (3) investigation on effective design of closed-loop control frameworks for in situ optimization of the WAAM hybrid manufacturing process. Ultimately, this dissertation will provide an understanding of how WAAM process parameters can be selected and how closed-loop control can be implemented to optimize hybrid manufacturing process planning.