Additive Manufacturing
"Mapping" Expands
Process Capabilities


Additive manufacturing (AM) is a rapidly evolving field—technologies, materials, and equipment are constantly being improved. AM techniques use CAD models to create 3D prototypes or final production parts by fusing micro-layers of material together, instead of machining these parts from solid blocks of material. Processes range from 3D printing machines to commercial laser and electron-beam direct-metal AM systems.

Different types of direct-metal AM systems have largely been developed independently of each other, often relying on high levels of experimentation. As a result, little transfer of processing knowledge has occurred across different metal alloy systems and direct metal processes. Engineers have limited understanding about how process variables can be altered outside of the variable sets that have been established for each machine and alloy system by the manufacturer. Being able to change process variables is essential for using direct metal AM to produce high-end components. This not only allows the building of 3D shapes, but also the control mechanical properties, reduction of thermal stresses, and improvements to surface finish.

Current commercially available direct-metal processes operate across a wide range of process variables. What do these systems share in common? How can process variables be manipulated to create more functionality and higher performance? Expanding these capabilities would also enable more design flexibility in key industries such as aerospace and medical implants.

Professor Jack Beuth and his team of researchers are working on developing a wider range of metal powders for high volume manufacturing processes. Image:





Process Mapping

In an effort to provide expanded capabilities to direct-metal AM users and developers, engineers at Carnegie Mellon University in Pittsburgh have developed “process mapping” methods that show how process variables can be changed under steady-state and transient conditions, for several AM technologies.

Led by mechanical engineering professor Jack Beuth, the Carnegie Mellon team focused its mapping study on commercial laser and electron-beam direct-metal AM systems.

Mapping consisted of tracking five process variables that are critical to any thermally based AM process—heat source power, heat source travel speed, material feed rate, existing temperature of the part or component upon which new material is deposited, and feature geometry (local geometry of the part).

“Our process mapping shows the relationships between process variables, such as beam powers, beam travel speeds, and material feed rates, and process outcomes like microstructural features and melt pool dimensions,” says Beuth. “We can present this data in formats that processing engineers can use, such as two-dimensional power-velocity plots.”

This approach can yield insights into the physics of the AM process, which deepens the understanding of the dependence of process outcomes on different variables. For example, engineers can see how melt pool response times are affected by abrupt changes in beam powers and travel speeds, with application to real-time melt pool feedback control systems. Melt pool geometry, microstructure, and residual stress can also be impacted by changes in feature geometry, process, and the alloy system being used. This approach can be applied to all direct metal AM systems.

Moving Forward

“We are able to show how understanding all these processes can be approached in the same way,” says Beuth. For example, engineers can take insights from one type of process (such as high deposition rate electron beam welding-based processes) and transfer that working knowledge to other processes (such as high precision, low deposition rate laser powder bed processes), in ways that have not been previously considered.

The same approach can be applied to other thermally based AM processes, such as those for polymers.  

With support by NSF, NIST, America Makes (formerly NAMII), and the state of Pennsylvania, Beuth is developing process maps for all the current commercially available, direct-metal AM processes. For one project, Beuth’s team is developing a method for indirectly controlling some microstructural features through real-time monitoring and control of key melt pool dimensions. Another project is looking at the time it takes for the melt pool to respond to controlled changes in beam powers and travel speeds. 

A key issue in direct-metal AM is the amount of time it takes to "qualify" a process for the fabrication of a component. Currently this requires extensive experimentation that includes deposition, sectioning, polishing, and imaging of microstructures—all of which is very time-consuming.

“Through our process mapping methods,” adds Beuth, “we are identifying regions of process variable space where certain microstructural features can be expected, which can greatly reduce process qualification times. This will speed up production, improve quality, and reduce overall manufacturing costs.” 

Mark Crawford is an independent writer.

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Process mapping of direct-metal additive manufacturing technologies shows the relationships between process variables and process outcomes, under both steady-state and transient conditions.

Prof. Jack Beuth,
Carnegie Mellon University


March 2014

by Mark Crawford,