I have an immediate opening for a postdoctoral scholar position in my group. Interested candidates should email me their CV and a cover letter describing their background and qualifications. Further information can be found in the full advertisement.


Current Projects

Incremental Sheet Forming

A freeform process where a single-point tool is used to deform a metal sheet point by point until the final geometry is achieved. This process is economical for prototyping and small batch production since expensive tooling and dies are not required. Our group has created iterative learning controllers to automatically adjust tool commands based on measurements, collected by a digital image correlation system, of previous builds. The convergence characteristics of the controllers for both single and multiple sheet forming were explored for various controller gains and part geometric characteristics such as radius of curvature. Experimental results show that geometric errors can be reduced by an order of magnitude when using the iterative learning controllers. Our group also investigated the force fluctuations commonly seen in the incremental sheet forming process. A significant source of these errors was determined to arise from robot geometric errors and forming models were extended to account for these errors. Experimental studies were conducted and force fluctuations were reduced by half.

Laser Metal Deposition

A metal blown powder bed additive manufacturing process capable of fabricating large parts and parts with graded materials, adding engineering features onto parts, and cost-effective part repair. However, it is quite challenging to regulate the morphology of parts fabricated by laser metal deposition due to a variety of sources that cause variation in the process, making it difficult to certify high-value parts for the aerospace, defense, and biomedical industries. Our group is researching layer-to-layer control techniques where measurements gathered during and immediately after the fabrication of a layer are used to automatically adjust the process parameters for the subsequent layer. Our control algorithms can be easily implemented on industrial machines, even those with closed control architectures. Our group created two-dimensional (space and layer) models of the laser metal deposition process that characterize the important process features needed to understand the part’s fabricated morphology and elucidate critical dynamic properties, such as open-loop stability. Experiments studies have been conducted to validate the models and illustrate the utility of layer-to-layer control.

Battery Estimation and Control

Our group is conducting work towards advancing the capabilities of battery management systems via control-oriented modeling, state-of-charge and state-of-health estimation, and the creation of fast charging methodologies. A single particle model was used to create an output injection observer to estimate battery state-of-charge (and Lyapunov analysis was used to determine the design rules to construct a stable observer. An adaptive output injection observer was then created to ensure good estimation, even at high C rates, by performing on-line estimation of the disturbance model parameters. Lyapunov analysis was again employed to determine the conditions under which state and disturbance model parameters will converge and, in the presence of sensor noise, when they are bounded. Our group has extended the single particle model by including electrolyte physics and simulation studies show the improved prediction performance for constant discharge and dynamic current profiles. Our group is currently investigating a fast charging technique that adjusts the current to maintain a constant surface gradient to regulate degradation while charging.

Volumetric Error Compensation

A technique to modify tool paths to correct for geometric errors of industrial machines that are a result of component fabrication and assembly. Machine tool and robot calibration is slow and unable to capture complex kinematic errors such as sagging and twisting in large machine tools and errors resulting from harmonic drives in industrial robots. Our group has created a new volumetric error compensation technique for industrial equipment. A laser tracker is used to measure geometric errors over the entire visible joint space and 6 Degree of Freedom (6DoF) geometric error model is constructed to describe the errors occurring between subsequent joints. Each translational and rotational error for each joint is described by a set of joint-position dependent basis functions and a maximum likelihood estimator is employed to identify error model coefficients. Using this model, an optimization algorithm is used to populate machine tool compensation tables, or the inverse Jacobian method is used to modify robot joint commands. The method has been applied to numerous machine tools and robots in industrial settings and volumetric error can be decreased by an order or magnitude within one shift.

Additive Manufacturing of Glass

Additive manufacturing of glass fabricates complex glass parts by feeding a filament or fiber into a molten pool of glass formed by a laser energy source. The process opens up the design space for glass products as it can be used to fabricate fully dense transparent free-form parts for gradient index optics, complex structures for embedded optics and waveguides, and freeform structures. Our group conducted studies to understand the process and discover process parameter spaces suitable for fabrication. Two issues that limit this process are bubble formation at high deposition rates and the challenge of placing the glass in a desired location. Our group created temperature controllers that allow glass to be deposited without bubbles at high deposition rates. Also, our group derived a path planning methodology that allows the direction of substrate motion to be aligned with the direction of deposition such that glass can be deposited with minimal morphology variation.

Wire Saw Machining

Wire saw machining utilizes fixed abrasive diamond wire saw machining is often used to cut hard and brittle materials, especially for wafers in the semiconductor and optoelectronics industries. This process has excellent flexibility as it produces a narrower kerf, low cutting forces, and minimal material waste. Based on analyzing the forces generated from the chip formation and friction of a single abrasive, our group created an analytical cutting force model and validated it with extensive experimental work. our group created an adaptive force controller to account for disturbances that naturally occur during the process. Experimental implementations showed that by regulating the normal force, the surface finish could be decreased by 60%. Our group modeled wire vibrations analytically and conducted experimental studies that demonstrate a clear correlation between part surface morphology and wire saw vibration amplitude.

Selective Laser Melting

An additive manufacturing process where a layer of powder is sintered at specified locations via a laser, the bed is lowered, new powder is spread, and the process is repeated. Changes in heat transfer characteristics of the part as it is being built further and further from the substrate, the part geometry and its thermal boundary conditions, and the time between layers at a specific locations causes variations in the resulting microstucture and often failed builds. Our group has been investigating monitoring and control techniques that use spatial sensors such as infrared cameras to gather voxel-based measurements to determine the state of the process and prevent failures. Research shows that sensor resolution dramatically affects measurements of the melt pool characteristics and often creates misleading results. Voxel-based infrared camera and spectrometry measurements are mapped to part microstructure and mechanical properties, and these measurements are used to control part integrity. Our group created layer-to-layer control methodology where measurements gathered during and immediately after the fabrication of a layer are used to automatically adjust the process parameters for the subsequent layer. These algorithms have the benefit that they can be directly implemented on industrial machines.

Previous Projects

Freeze Extrusion Fabrication of Ceramics

An extrusion process where an aqueous-based ceramic paste is extruded in a freezing environment layer by layer. This process is ideal for the fabrication of ceramic parts with complex geometries and multiple materials. Quality fabrication is complicated by variations in viscosity from batch to batch, variations in the environmental temperature, and liquid phase migration. Our group created a first principle, control-oriented model of the extrusion force. This nonlinear, first-order dynamic model describes the steady extrusion forces, as well as the during the start and stop of extrusion, and how the dynamic response changes as air bubbles are released from the paste. A first principle mode of the filament freezing time that is two orders of magnitude faster to solve was also created. Our group created tracking controllers consisting of feedforward and feedback mechanisms to regulate the extrusion force. Experimental studies demonstrated that force control is necessary to build large parts and to remove pores due to bubble release.

Friction Stir Welding

A solid state joining process where a rotating tool is plunged between parts to plasticize material, which forms a weld between the parts as the tool leaves the processing zone. Regulating the forces that develop in this process are important since if the cup on the tool shaft lifts off the part, material will leave the welding zone and running voids and wormholes, i.e., internal voids, will result. Our group created nonlinear, data-driven dynamic models of the friction stir welding process that related the forces generated during the process to the process parameters. These models included servomechanism dynamics, including delays in the sensor systems. These models were used to construct control algorithms that utilized a Smith Predictor-Corrector structure to account for the inherent delays in the system. Experimental studies demonstrated that regulating the force allowed superior welds when gaps were present between the sheets due to fixturing, and running voids and wormholes could be prevented.


A set of metal removal processes where chips are sheared from a stock of material until the final part shape is realized. To improve operation productivity and part quality, our group created force controllers to regulate the cutting force is a face milling process. The controllers automatically adjusted feed rate when the part depth of cut changed. Machining chatter is the unstable interaction between the cutting force and structural vibrations. Our group investigated how the nonlinear force-feed effect modifies stability lobe diagrams that describe the stable and unstable (i.e., chatter) regions in the process parameter space. By using linearization techniques, it was found that as the feed is increased, the stability bound increases since the coefficient describing the power relationship from force to feed is typically less than unity. Our group also investigated the machining of thin titanium parts. Process maps were created so that the designer could select process parameters where the variation in the force normal to the part would be driven to zero.


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