Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)

Legacy Department

Mechanical Engineering

Committee Member

Dr. Georges Fadel, Committee Chair

Committee Member

Dr. Ilenia Battiato, Committee Co-Chair

Committee Member

Dr. Fadi Abu-Farha

Committee Member

Dr. Hongseok Choi

Committee Member

Dr. Xin Zhao


During the past few years, the need for multi-material parts or heterogeneous objects (HOs) has surfaced with the rapid growth of laser technology, material science and additive manufacturing techniques. Direct Metal Deposition (DMD) process, a metal based additive manufacturing technique, can locally deposit dissimilar metal powders to produce HOs as needed. While some theoretical and experimental studies have been conducted to investigate the DMD process, there are still some challenges such as the process parameters design, optimization, and adjustment during the fabrication of HOs that have not been well elucidated. This dissertation aims at developing the manufacturing science needed to design a laser additive manufacturing system capable of mixing two or more dissimilar powders to manufacture heterogeneous meta-materials objects. This research would enable moving beyond rapid “prototyping” into the realm of functional heterogeneous metal based additive manufacturing (HMAM). Therefore, the objective of this research is to develop the science needed to support the design and manufacture of HOs, placing materials where needed, when needed, in the proportions specified by the design, and combining them in-situ to achieve significant performance enhancements. The dissertation starts by showing the whole picture of the design process, then identify where the challenges and improvement opportunities rest. The whole DMD system design includes the geometrical design of the powder delivering nozzles, the optimal design of the process parameters when depositing dissimilar materials, and the control or planning of the process parameters during the DMD fabrication of HOs. The Laser Engineered Net Shaping (LENSTM) system developed at Sandia and commercialized by Optomec® Inc. is referred to and used to implement the research. An Artificial Neural Network (ANN) based method is proposed using FEM (Finite Element Method) as simulation tool to find the optimal geometry of the injection nozzles in order to maximize the process efficiency. Then, a mathematical model-based design method is proposed combining a multi-objective optimization algorithm to optimize the process parameters including the injection angles, injection velocities, and injection nozzle diameters for the two materials, as well as the laser power and the scanning speed. Finally, a comprehensive study investigating the relationship between the desired part's composition and the process parameters is conducted to fabricate a part with precise composition compared to the heterogeneous components design information. This dissertation provides a better understanding of the physical process in the DMD manufacturing of HOs. This work would help design the whole DMD system, and make it a more efficient, more precise and more flexible process.



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