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Additive Manufacturing (AM) is an innovative manufacturing process which offers near-net shape fabrication of complex components, directly from CAD models, without dies or substantial machining, resulting in a reduction in lead-time, waste, and cost. For example, the buy-to-fly ratio for a titanium component machined from forged billet is typically 10-20:1 compared to 5-7:1 when manufactured by AM. However, the production rates for most AM processes are relatively slow and AM is consequently largely of interest to the aerospace, automotive and biomedical industries. In addition, the solidification conditions in AM with the Ti alloy commonly lead to undesirable coarse columnar primary β grain structures in components. The present research is focused on developing a fundamental understanding of the influence of the processing conditions on microstructure and texture evolution and their resulting effect on the mechanical properties during additive manufacturing with a Ti6Al4V alloy, using three different techniques, namely; 1) Selective laser melting (SLM) process, 2) Electron beam selective melting (EBSM) process and, 3) Wire arc additive manufacturing (WAAM) process. The most important finding in this work was that all the AM processes produced columnar β-grain structures which grow by epitaxial re-growth up through each melted layer. By thermal modelling using TS4D (Thermal Simulation in 4 Dimensions), it has been shown that the melt pool size increased and the cooling rate decreased from SLM to EBSM and to the WAAM process. The prior β grain size also increased with melt pool size from a finer size in the SLM to a moderate size in EBSM and to huge grains in WAAM that can be seen by eye. However, despite the large difference in power density between the processes, they all had similar G/R (thermal gradient/growth rate) ratios, which were predicted to lie in the columnar growth region in the solidification diagram. The EBSM process showed a pronounced local heterogeneity in the microstructure in local transition areas, when there was a change in geometry; for e.g. change in wall thickness, thin to thick capping section, cross-over’s, V-transitions, etc. By reconstruction of the high temperature β microstructure, it has been shown that all the AM platforms showed primary columnar β grains with a <001>β.

Wire Arc Additive Manufacturing (WAAM) has recently developed into a viable manufacturing process for large, complex metal parts. The WAAM process uses a Gas Metal Arc Welding (GMAW) torch mounted to an automated motion platform to execute a predetermined path plan based on a desired CAD geometry. As the desired geometry becomes more complex, it is advantageous to utilize out-of-position welding techniques used by human welders to stabilize the weld pool during the deposition of large overhangs. To ensure part accuracy and quality, adding layers of real-time control to manage various aspects of the WAAM process is critical. First, a controller is developed to maintain the contact-to-workpiece distance in the GMAW process to control the layer height of the deposited weld bead. Next, through exploring the relationship between base plate inclination angle, welding torch orientation, and bead shape, a system is developed to monitor the profile of the deposited weld bead and calculate the shape of the current bead to compare the current shape to a desired bead shape. Finally, the effect of interpass temperature on the geometric conformity of a deposited part is explored to improve the efficiency of the WAAM process and ensure geometric conformity and process stability.

In this study, a number of established additive manufacturing processes were evaluated for their suitability repairing high-pressure die cast tooling. The processes included in this study are laser hot wire (LHW), electron beam freeform fabrication (EBF3), gas metal arc welding (GMAW), Laser Engineered Net Shaping (LENS®), and direct metal deposition (DMD). To determine each process’ suitability, blocks of maraging 250 steel were deposited on H-13 base metal. The results show that the maraging deposits are capable of providing good strength (>160 ksi), toughness (>15 ft-lbs), and hardness (45 HRC) for die tooling applications, but care must be taken to limit the occurrence of defects, particularly porosity. Of the processes tested, the LHW, DMD, and LENS® processes had the best balance of deposit properties. However, additional work will be required to optimize the processing parameters for each process.

The heat-affected zone (HAZ) is the most common region of weld failures. The weld failures are directly related to the microstructure. Microstructure control of the HAZ is crucial to weld quality and prevention of weld failures. However, publications on modeling the development of the HAZ are relatively limited. Moreover, no efforts have been made to predict the HAZ microstructures in real-time. The primary goal of this research is to present a methodology to enable real-time predictions of microstructure evolution in the HAZ and its mechanical properties. This goal was achieved by an approach based on materials science principles and real-time sensing techniques. In this study, the entire welding process was divided into a series of sub-processes. Real-time multiple measurements from multiple sensors were incorporated into the sub-processes. This resulted in an integrated welding system upon which the predictions for the final HAZ microstructure are based. As part of the integrated system, the microstructural model was used to predict the TTT curves, volume fractions of the decomposition products, and hardness numbers of the heat-affected zones of steel alloys. Actual welds were performed under two different sets of conditions, and the resulting experimental data were compared with predictions made using the microstructural model. The predicted and experimental microstructure and hardness are found to be in good agreement, indicating that the microstructural model can be used in real applications. This research can act as an important component of future research to enable physics-based flexible control of welding.

Gas metal arc welding (GMAW) is a joining process widely used in various industries such as automotive and ship building due to its low cost and high productivity. Weld quality during GMAW is basically determined by the stability of metal transfer. Unstable metal transfer will result in weld discrepancies, and excess spatter on the welded assembly. The objective of this dissertation is to develop models to understand metal transfer and various instabilities during metal transfer, and to develop algorithms to monitor various weld discrepancies and control weld geometry in GMAW. Due to the process complexity, there exist many challenges in developing process models, and these often require extensive numerical computations. To address these problems, an analytical model is developed for GMAW in the globular mode to simulate drop dynamics and drop detachments. The metal transfer frequency and stability are predicted at different wire feeding rates, and the results validated by experimental observations. The model can be used as a tool to estimate regions of instability during globular metal transfer. Furthermore, arc start instability is studied in detail using high speed camera images and the welding signals, voltage and current. The effect of this instability on weld quality (weld geometry, spatter) is studied by parametric models. As part of this study, a control algorithm is developed to compensate for weld geometry in gas metal arc spot welding under the influence of arc start instability. Finally, a discrepancy detection method and algorithm is developed to automatically monitor and classify various weld discrepancies during pulsed mode metal transfer. The weld discrepancy detection algorithms are tested in an industry site to automatically monitor the quality of welds for pulsed mode metal transfer.

Aluminum alloys have been increasingly used in the automotive industry as an alternative to steels to improve fuel economy, reduce emissions, and enhance vehicle safety and performance. One of the major processes for joining aluminum parts is gas metal arc welding (GMAW) because of its high productivity, flexibility and low cost. However, aluminum GMAW is prone to various defects and weld quality is commonly evaluated using manual inspection procedures, which are labor intensive and may introduce inconsistence. Furthermore, the knowledge of aluminum GMAW is insufficient to have a consistent and efficient way to evaluate weld quality. The objective of this thesis is to obtain a comprehensive understanding of aluminum GMAW process and develop quality monitoring and estimation methods, which can be used in the automated production environment to continuously improve the weld quality and system consistency. Fundamental research has been conducted to study the welding process signals with synchronized metal droplet transfer images using an online data and high-speed image acquisition system. Based on these experiments, welding signature analyses in both time and frequency domains are performed to reveal the correlation between the droplet transfer process and the welding voltage and current signals. Algorithms have been developed to characterize individual droplet transfer dynamics, detect the existence of secondary droplets and estimate droplet sizes. A model is then developed to estimate weld bead geometry based on the welding signature analysis and liquid surface modeling. The model uses a numerical liquid surface model to represent the steady-state profile of welding pool, which is updated drop by drop with information from incoming droplets obtained by analyzing the welding signals. The weld geometry estimation is applied to real welding signals in both globular and spray transfer modes and the results show a good match to the physical weld geometries. A method is also developed to detect and classify different weld defects in pulsed GMAW (GMAW-P). The method first uses a state-space model to numerically represent a stable welding process. The state-space model is then used to predict the voltage signals using the measured current signals as the inputs. Voltage prediction residuals are calculated and found to be correlated to process disturbances and different welding defects. The prediction residuals are further characterized and classified to identify different weld defects. The method is validated to have a 100% defect detection rate and an 84% overall correct classification rate for different weld defects.

Gas metal arc welding (GMAW) is widely used in industry for joining steel and aluminum alloys. Experimental studies are usually confined by cost and time factors, and largely depend on the availability of sample workpieces and welding facilities. Numerical simulations, therefore, are economical alternative approaches to gain insight into GMAW. Due to the lack of understanding of the physical phenomena associated with GMAW short-circuiting transfer, this process is analyzed in Chapter II in this dissertation. The two-dimensional model developed incorporates the thermal, fluid and electromagnetic mechanisms involved in GMAW. A front-tracking numerical procedure is applied to explicitly track the profile of the free surface in GMAW short-circuiting transfer. The model is applied to predict the short-circuiting duration time under different welding currents and surface tension temperature coefficients. The Marangoni effect was found to play a significant role in determining the short-circuiting duration time. Drop formation has great impact on the quality of weldments. Most existing numerical models are based on two- or three-dimensional analyses that usually take hours or even days to run. Developing an algorithm that can be applied to real-time control of the drop transfer in GMAW prompted the research presented in Chapters III and IV. In Chapter III, a highly efficient numerical algorithm for the drop formation in GMAW is developed. The formulation takes into account gravity, inertial, surface tension and electromagnetic forces. By assuming the variables of interest are a function of the axial coordinate only, the governing equations are simplified to a one-dimensional approximation in the axial coordinate. The algorithm is benchmarked by simulating a drop of water suspended from an orifice (Eggers and Dupont, 1994; Peregrine, 1990). The model is then further developed to accommodate the nonisothermal effect in drop formation, and implemented to study the effect of the surface tension temperature coefficient on drop formation in GMAW in Chapter IV. It is observed that a positive surface tension temperature coefficient accelerates the drop formation process while a negative coefficient impedes the growth and detachment of the drop.

Gas metal arc welding (GMAW) is the most commonly used arc welding method in industry for joining steels and aluminum alloys. But due to the mathematical difficulties associated with the free surface motion of the molten droplet and the weld pool, the process is not well understood and the development of new welding procedures in the manufacturing industry highly depends on expensive, time-consuming and experience-based trial and error. In this dissertation, numerical methods are developed to overcome the difficulties and to simulate the metal transfer and weld pool development in the GMAW of sheet metals. The simulations are validated by experiments and used to study an industrial welding process. A numerical procedure is first developed to model the free surface motion in fusion welding processes. Thermal and electromagnetic models are integrated with the fluid models. Recommendations are made on the selection and improvement of publicly available numerical algorithms, while alternative methods are also reviewed. A model combining the enthalpy, effective-viscosity and volume-of-fluid methods is then developed to simulate the metal transfer process in globular, spray and short-circuiting transfer modes. The model not only describes the influence of gravity, electromagnetic force and surface tension on droplet profile and transfer frequency, but also models the nonisothermal phenomena such as heat transfer and phase change. The melting front motion, the droplet detachment and oscillation, the satellite formation and the fluid convection within the droplet are analyzed. It has been found that the taper formation in spray transfer is closely related to the heat input on the unmelted portion of the welding wire, and the taper formation affects the globular-spray transition by decelerating the transfer process. Experiments with a high-speed motion analyzer validate the simulation results. The model is then extended to simulate the initiation, development and solidification of the weld pool, with consideration of the droplet impingement on the pool surface. The characteristics of physical variables in the weld pool are analyzed. Burn-through of thin sheet metals and penetration of a multi-layered workpiece are also simulated. Experiments are used to verify the predicted weld penetration. Finally, numerical simulation is used to analyze an industrial welding process---the gas metal arc spot welding of multi-layered workpieces. The traditional spot welding and plug welding methods are simulated. It is shown that the plug method can ensure a stable short-circuiting transfer through a pre-made hole. Both the simulation and tensile-shear tests show that the plug method improves the penetration consistency by ensuring the effective joint diameter.