Date of Award


Degree Type


Degree Name



Industrial and Manufacturing Systems Engineering

First Advisor

Ruth J Urbanic




During the past two decades, basic and applied research has led to an in-depth understanding of the cladding process as well as to a variety of potential applications. Industry had been reluctant to adopt this technology mainly due to high investment costs, and the unpredictable and nonlinear behavior of the process. However, the repair and refurbishment sector of production engineering is flourishing. Most engineering applications require high strength and corrosion resistant materials for long term reliability and performance of the components; consequently, laser cladding (LC) has been explored as a viable solution for an additive manufacturing (AM) approach. Laser cladding is one of the material AM processes used to produce a metallurgically well-bonded deposition layer and now it has been integrated into the industrial manufacturing lines to create a quality surface. To obtain a desired-quality resulting part, a deep understanding of the process mechanisms is required since laser cladding is a multiple-parameter-dependent process. Developing a bead shape to process parameter model is challenging due to the nonlinear and dynamic nature of the LC environment. This introduces unique predictive modeling challenges for both single bead and overlapping bead configurations. A set of cladding experiments have been performed for single and multiple bead scenarios, and the effects of the transient conditions on the bead geometry for these scenarios have been investigated. It is found that the lead-in and lead-out conditions differ, corner geometry influences the bead height, and when changing the input power levels, the geometry values oscillate differently than the input pulses. The dynamic, time varying heating and solidification, for multiple layer scenarios, leads to challenging process planning and real time control strategies. Models are developed for single and overlapping beads using the analysis of variance (ANOVA) and Generalized reduced gradient (GRG) approach along with regression analysis to determine the process trends and the best modeling approaches. Since laser cladding (LC) process has potential to make 3D components; determination of the fill volume for the ‘near net shape’ and the appropriate fill rate is the primary challenge. Although the additive approach reduces many issues related to process planning, there are still issues related to accuracy, surface finish, and build time that require improvement.