Additive manufacturing of smart metallic structures

A freeform fabrication process based on ultrasonic metal welding enables production of dense, gapless 3D structures of dissimilar metals, smart materials, heat management devices, and electronic components.
11 February 2014
Marcelo Dapino

Worldwide sales of additive manufacturing products and services (those created using digital models) is estimated to reach $11 billion in 2021, up from $2 billion in 2012.1 Despite this anticipated level of growth, the value of additive manufacturing to industry is unclear. This is especially true for industry that relies heavily on mass production. As a relatively new technology, additive manufacturing has yet to reach the levels of throughput, cost structure, and standardization required in industry sectors such as automotive and electronics. That said, the technology presents a key opportunity to reduce the mass of vehicle structures (‘lightweighting’) and increase the functionality of products. In-depth research is needed to address the challenges and move additive manufacturing from the laboratory to practical applications.

We seek to study, demonstrate, and realize the benefits of ultrasonic additive manufacturing (UAM) in industry, with particular emphasis on vehicle design and fabrication.2–5 UAM is a solid-state manufacturing process that combines additive joining of thin metal tapes with subtractive milling operations to generate near net-shape metallic parts.6 A rotating sonotrode driven by piezoelectric transducers applies high-frequency vibrations (>20kHz) to a foil, creating a scrubbing action and plastic deformation between the foil and the material to which it is being welded: often a metallic baseplate, a part, or other foils (see Figure 1). The scrubbing action displaces surface oxides, contaminants, and collapses asperities (surface irregularities), exposing nascent surfaces that instantaneously bond under a compressive force. A computer numerical control stage allows for selective material removal and machining to final dimensions, though the low thermal loading in UAM implies that finished parts suffer no distortion. Hence no remedial machining is required. The very high power UAM system we recently installed uses 9kW of ultrasonic power to achieve quality joints of dissimilar materials (see Figure 2).

Figure 1. Schematic of the ultrasound additive manufacturing (UAM) process, which uses ultrasonic vibrations and pressure to join foil stock to a baseplate or other foils. The process is solid state, with no fusion.

Figure 2. New very high power (9kW, 20kN) UAM system enables joining of dissimilar metals (such as structural aluminum, copper, and steels) along with embedded sensors, actuators, and electronic components.

Because the exact mechanism for UAM joining hard metals is unknown, we need in-depth computational and experimental investigations of the process. For modeling we developed multiscale computational formulations of the UAM layering process, extending from the scale of the process down to the microstructure of parts made with it. We consider this scale range—which is approximately eight orders of magnitude and incorporates the multi-physics nature of the process—to understand how to optimize process-property relationships in UAM. Given the complex nature of this process, experiments are necessary to optimize parameters for new alloy combinations, to guide the model development, and to test new materials and structures made with the process (see Figures 3 and 4).

Figure 3. Aluminum hinge actuated by shape memory (nickel titanium) wires. SMA: Shape memory alloy.

Figure 4. Cross section of a build including copper, stainless steel, and a cooling channel.

Recent multiscale models developed by our group had a simplified framework with three scales:7 structural, material macrostructure, and material microstructure. Previously, there was insufficient modeling at the microstructure level. Therefore, we used a bottom-up approach starting at the microstructure. At that scale, a single alumina fiber (used for reinforcement) and surrounding aluminum matrix created a representative volume element (RVE) that we used as a building block for describing a UAM composite. We created the macrostructure scale, defined as a single foil layer, by periodic assembly of RVEs, considering periodic boundary conditions. At the structural scale, we combined several tapes to create a composite. At this level, macroscopic material properties are defined and the interactions between the composite and UAM process take place. We implemented these scales in COMSOL Multi-Physics, a commercial finite element analysis solver. We applied compressive and shear loads typical of very high power UAM and modeled surface roughness effects and different fiber geometries. We found that surface roughness (as transferred to the tape from the sonotrode's texture) had a significant effect on bonding, with large asperities, inducing greater plastic deformation and therefore improved bonding (see Figure 5).

Figure 5. Plastic deformation for 6μm roughness at 13μm sonotrode deflection.

We have conducted design of experiments analysis on UAM builds fabricated under various treatment combinations and mechanically tested in shear and multiaxial tension. Work on aluminum-aluminum and titanium-aluminum builds used a Taguchi L18 experimental design matrix that factors temperature, normal force, welding velocity, and vibration amplitude.8, 9 We used analysis of variance statistical testing to calculate trends and understand the effect of process parameters on mechanical strength.

Critical advantages of UAM for the transportation industry are reducing mass and part count, and embedding advanced features directly within a structure. To realize these benefits, research is needed to better understand the mechanisms that govern joining of dissimilar joints involving harder metals, such as stainless steel, titanium alloys (Ti6Al4V, for example), and structural aluminum (such as 6XXX and 7XXX alloys). On the applications side, our work will continue to focus on embedding features into metals, such as smart material sensors and actuators, electronic components, and thermal management devices, among others.

Support for purchase and deployment of the very high power UAM system was provided by the Ohio Department of Transportation, Wright Projects Program, grant TECH 12-067. The technical contributions of Karl Graff (Edison Welding Institute) and Mark Norfolk (Fabrisonic) are acknowledged.

Marcelo Dapino
Ohio State University
Columbus, OH

Marcelo Dapino is the Honda R&D Americas designated Chair in Engineering. His interests are research, development, and manufacture of smart material systems. Dapino serves on the executive committee for the Aerospace division of the American Society of Mechanical Engineers (ASME) and has organized major ASME and SPIE conferences.

1. Wohlers Report. Research and analysis of additive manufacturing worldwide, 2013.
2. M. J. Dapino, Ultrasonic additive manufacturing of smart structures, Proc. SPIE 9059, 2014. (Invited paper.)
3. A. J. Hehr, J. D. Pritchard, M. J. Dapino, Interfacial shear strength estimates of NiTi-aluminum matrix composites fabricated via ultrasonic additive manufacturing, Proc. SPIE 9059, p. 905906, 2014. doi:10.1117/12.2046317
4. J. J. Scheidler, M. J. Dapino, Stiffness tuning of FeGa structures manufactured by ultrasonic additive manufacturing, Proc. SPIE 9059, p. 905907, 2014. doi:10.1117/12.2046247
5. P. J. Wolcott, A. J. Hehr, M. J. Dapino, Optimal welding parameters for very high power ultrasonic additive manufacturing of smart structures with aluminum 6061 matrix, Proc. SPIE 9059, p. 905908, 2014. doi:10.1117/12.2046291
6. K. F. Graff, Ultrasonic additive manufacturing, ASM Handbook 6A, Welding Fundamentals and Processes, p. 731, ASM Int'l, 2011.
7. A. Roberts, M. J. Dapino, Manufacturing process optimization of ultrasonic bonding of metallic composites, Army Topic A12a-T004, 2012. Proposal A12A-004-0106
8. C. Hopkins, P. J. Wolcott, M. J. Dapino, A. C. Truog, S. S. Babu, Optimizing ultrasonic additive manufactured Al 3003 properties with statistical modeling, J. Eng. Mater. Technol. 134(1), p. 011004, 2012.
9. C. D. Hopkins, M. J. Dapino, S. A. Fernandez, Statistical characterization of ultrasonic additive manufacturing Ti/Al composites, ASME J. Eng. Mater. Technol. 132(4), p. 041006, 2010.
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