Dr. Abdalla R. Nassar Profile

Dr. Abdalla R. Nassar

Enterprise Additive Manufacturing Lead at John Deere

SPIE Involvement:

Author | Instructor

Proceedings Article | 24 April 2020 Presentation

Laser ultrasonic testing of titanium alloy parts inside the directed energy deposition additive manufacturing chamber (Conference Presentation)

Chaitanya Bakre, Gerald Boddie, Cory Jamieson, Abdalla Nassar, Edward Reutzel, Cliff Lissenden

Proceedings Volume 11381, 1138105 (2020) https://doi.org/10.1117/12.2559129

KEYWORDS: Ultrasonics, Additive manufacturing, Directed energy weapons, Titanium, Nondestructive evaluation, Surface roughness, Metals, Q switched lasers, Nd:YAG lasers, Interferometers

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Proceedings Article | 6 April 2016 Paper

Sensing for directed energy deposition and powder bed fusion additive manufacturing at Penn State University

Abdalla Nassar, Edward Reutzel, Stephen Brown, John Morgan, Jacob Morgan, Donald Natale, Rick Tutwiler, David Feck, Jeffery Banks

Proceedings Volume 9738, 97380R (2016) https://doi.org/10.1117/12.2217855

KEYWORDS: Imaging systems, Pyrometry, Image processing, Additive manufacturing, Sensing systems, Cameras, Temperature metrology, Directed energy weapons, Laser optics, Calibration

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Proceedings Article | 14 May 2015 Paper

A brief survey of sensing for metal-based powder bed fusion additive manufacturing

Bryant Foster, Edward Reutzel, Abdalla Nassar, Corey Dickman, Benjamin Hall

Proceedings Volume 9489, 94890B (2015) https://doi.org/10.1117/12.2180654

KEYWORDS: Additive manufacturing, Metals, Control systems, Image processing, Sensors, Cameras, Laser systems engineering, 3D modeling, Infrared cameras, Process control

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Purpose – Powder bed fusion additive manufacturing (PBFAM) of metal components has attracted much attention, but the inability to quickly and easily ensure quality has limited its industrial use. Since the technology is currently being investigated for critical engineered components and is largely considered unsuitable for high volume production, traditional statistical quality control methods cannot be readily applied. An alternative strategy for quality control is to monitor the build in real time with a variety of sensing methods and, when possible, to correct any defects as they occur. This article reviews the cause of common defects in powder bed additive manufacturing, briefly surveys process monitoring strategies in the literature, and summarizes recently-developed strategies to monitor part quality during the build process.

Design/methodology/approach – Factors that affect part quality in powder bed additive manufacturing are categorized as those influenced by machine variables and those affected by other build attributes. Within each category, multiple process monitoring methods are presented.

Findings – A multitude of factors contribute to the overall quality of a part built using PBFAM. Rather than limiting processing to a pre-defined build recipe and assuming complete repeatability, part quality will be ensured by monitoring the process as it occurs and, when possible, altering the process conditions or build plan in real-time. Recent work shows promise in this area and brings us closer to the goal of wide-spread adoption of additive manufacturing technology.

Originality/value - This work serves to introduce and define the possible sources of defects and errors in metal-based PBFAM, and surveys sensing and control methods which have recently been investigated to increase overall part quality. Emphasis has been placed on novel developments in the field and their contribution to the understanding of the additive manufacturing process.

Course Instructor

SC1237: Additive Manufacturing of Metals – Powder Bed Fusion and Directed Energy Deposition

Additive manufacturing (AM) is rapidly being adopted by industry as a means to fabricate once-impossible components in a matter of days and weeks rather than months. This course presents the key elements of powder bed fusion and directed energy deposition AM. With a focus on these two, most popular AM processes, the course will first guide the audience though the digital thread for component fabrication, then to the consequences of hardware implementations and the effects of post-processing on part quality. In-process sensing and post-process non-destructive evaluation methods will also be covered. Audience members will leave with a high-level understanding of the technology and an appreciation for the many benefits and challenges of metals additive manufacturing.

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