The ability to produce consistent material properties across a single or series of platforms, particularly over time, is the major objective in metal additive manufacturing (MAM) research. If this can be achieved, it will result in widespread adoption of the technology for industry and place it into mainstream manufacturing. However, before this can happen, it is critical to develop an understanding of how processing parameters influence the thermal conditions which dictate the mechanical properties of MAM builds. Research work reported in the literature of MAM is generally based on a set of parameters and/or the review of a few parameter changes, and observing the effects that these changes (i.e., microstructure, mechanical properties) have. While these articles provide results with some insight, there lacks a standard approach that can be used to allow meaningful comparisons and conclusions to be made concerning the optimization of the processing variables. This study provides a template which can be used for making comparisons across DED platforms. The tests are performed with a design of experiments (DOE) philosophy directed to evaluate the effect of selected parameters on the measured properties of the DED builds. Specifically, a laser engineering net shaping system (LENS) is used to build multilayered 316L coupons and analyze how build parameters such as laser power, travel speed, and powder feed rate influence the thermal conditions that will define both microstructure and microhardness. A fundamental conclusion of this research is that it is possible to repeatedly obtain a consistent microstructure that contains a fine cellular substructure with a low level of porosity (less than 1.1%) and with microhardness that is equal to or better than wrought 316L. This is mainly achieved by maintaining an associated powder flow to travel speed ratio at the power level, ensuring an appropriate net heat input for the build process.

In order to capitalize on the cost-effectiveness of additive manufacturing (AM), it is critical to understand how to build components with consistency and high quality. Directed energy deposition (DED) is an AM method for creating parts layer by layer through the use of a moving heat source and powder material inserted into the melt pool generated on the substrate. DED, like most AM processes, is highly complex due to the rapid thermal gradients experienced during processing. These thermal gradients are determined by a variety of processing parameters, which include laser power, powder feed rate, travel speed, layer height hatch spacing, etc. A lot of effort has been carried out in the additive manufacturing community to understand what these critical parameters are and how they influence the thermal gradients. Despite all these efforts, AM industries rely on a trial-and-error-based approach to find the right set of parameters to produce a quality part. This is time-consuming and not a cost-effective use of AM technology. The aim of our research is to reduce the amount of experimental data in combination with numerical analysis to optimize this relationship. Physics-based two-dimensional melt-pool modeling and experimental results from an OPTOMEC 850M LENS will be utilized to investigate the effects of processing parameters on melt-pool geometry, and the results from this study will provide key processing guidelines to achieve desirable clad geometry and powder efficiency for the DED method.

Digital tools for design and manufacturing have led to a new revolution in how products are conceptualized and made. These advancements have led to the democratization of ideation and creation of personalized products, as well as many other innovations. However, the coronavirus disease 2019 (COVID-19) pandemic has exposed a critical flaw in the digital thread: the manufacturing systems of today remain inflexible to rapid changes brought on by emergency and crisis responses. The inefficiencies of this inflexibility caused by disconnects in supply and demand chains have become especially evident. We present a vision for a digital system—an open online product marketplace—that would enable product designers to rapidly connect with capable producers in meeting urgent customer demands. As such, this digital system would facilitate ordering, orchestration, and fulfillment, as well as continuous improvement of manufacturing-as-a-service systems. It would support flexible, sustainable, and resilient supply and demand chains beyond the COVID-19 period by enabling rapid specification matching for tailored or customized products to existing available manufacturing capabilities.