Additive manufacturing of metal components through directed energy deposition or powder bed fusion is a complex undertaking, often involving hundreds or thousands of individual laser deposits. During processing, conditions may fluctuate, e.g. material feed rate, beam power, surrounding gas composition, local and global temperature, build geometry, etc., leading to unintended variations in final part geometry, microstructure and properties. To assess or control as-deposited quality, researchers have used a variety of methods, including those based on sensing of melt pool and plume emission characteristics, characteristics of powder application, and layer-wise imaging.<p> </p> Here, a summary of ongoing process monitoring activities at Penn State is provided, along with a discussion of recent advancements in the area of layer-wise image acquisition and analysis during powder bed fusion processing. Specifically, methods that enable direct comparisons of CAD model, build images, and 3D micro-tomographic scan data will be covered, along with thoughts on how such analyses can be related to overall process quality.
<strong>Purpose</strong> – 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. <p> </p> <strong>Design/methodology/approach </strong>– 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. <p> </p> <strong>Findings </strong>– 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. <p> </p><strong>Originality/value</strong> - 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.
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.