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Human space exploration to date has been limited to low Earth orbit and the moon. The International Space Station (ISS) provides a unique opportunity for researchers to prove out the technologies that will enable humans to safely live and work in space for longer periods and venture farther into the solar system. The ability to manufacture parts in-space rather than launch them from earth represents a fundamental shift in the current risk and logistics paradigm for human space exploration. The purpose of this mission is to prove out the fused deposition modeling (FDM) process in the microgravity environment, evaluate microgravity effects on the materials manufactured, and provide the first demonstration of on-demand manufacturing for space exploration.

In 2014, NASA, in cooperation with Made in Space, Inc., launched a 3D printer to the ISS with the goal of evaluating the effect of microgravity on the fused deposition modeling (FDM) process and prove out the technology for use on long duration, long endurance missions where it could leveraged to reduce logistics requirements and enhance crew safety by enabling a rapid response capability. This paper presents the results of testing of the first phase of prints from the technology demonstration mission, where 21 parts where printed on orbit and compared against analogous specimens produced using the printer prior to its launch to ISS.

Mechanical properties, dimensional variations, structural differences and chemical composition for ground and flight specimens are reported. Hypotheses to explain differences observed in ground and flight prints are also developed. Phase II print operations, which took place in June and July of 2016, and ground-based studies using a printer identical to the hardware on ISS, will serve to answer remaining questions about the phase I data set. Based on Phase I analyses, operating the FDM process in microgravity has no substantive effect on the material produced.

Demonstrates that there is no discernable, engineering significant effect on operation of FDM in microgravity. Implication is that material characterization activities for this application can be ground-based.

Summary of results of testing of parts from the first operation of 3D printing in a microgravity environment.

The purpose of this paper is to evaluate the tool experiences using torque during welding as a means of in-process sensing for tool wear. Metal matrix composites (MMCs) are materials with immense potential for aerospace structural applications. The major barrier to implementation of these materials is manufacturability, specifically joining MMCs to themselves or other materials using fusion welding. Friction stir welding (FSW) is an excellent candidate process for joining MMCs, as it occurs below the melting point of the material, thus precluding the formation of degradative intermetallics’ phases present in fusion welded joints. The limiting factor for use of FSW in this application is wear of the tool. The abrasive particles which give MMCs their enhanced properties progressively erode the tool features that facilitate vertical mixing and consolidation of material during welding, resulting in joints with porosity. While wear can be mitigated by careful selection of process parameters and/or the use of harder tool materials, these approaches have significant complexities and limitations.

This study evaluates using the torque the tool experiences during welding as a means of in-process sensing for tool wear. Process signals were collected during linear FSW of Al 359/SiC/20p and correlated with wear of the tool probe. The results of these experiments demonstrate that there is a correlation between torque and wear, and the torque process signal can potentially be exploited to monitor and control tool wear during welding.

Radial deterioration of the probe during joining of MMCs by FSW corresponds to a decrease in the torque experienced by the tool. Experimentally observed relationship between torque and wear opens the door to the development of in-process sensing, as the decay in the torque signal can be correlated to the amount of volume lost by the probe. The decay function for tool wear in FSW of a particular MMC can be determined experimentally using the methodology presented here. The decay of the torque signal as the tool loses volume presents a potential method for control of the wear process.

This work has near-term commercial applications, as a means of monitoring and controlling wear in process could serve to grow commercial use of MMCs and expand the design space for these materials beyond net or near-net-shape parts.

This paper aims to investigate methods of implementing in‐process fault avoidance in robotic friction stir welding (FSW).

Investigations into the possibilities for automatically detecting gap‐faults in a friction stir lap weld were conducted. Force signals were collected from a number of lap welds containing differing degrees of gap faults. Statistical analysis was carried out to determine whether these signals could be used to develop an automatic fault detector/classifier.

The results demonstrate that the frequency spectra of collected force signals can be mapped to a lower dimension through discovered discriminant functions where the faulty welds and control welds are linearly separable. This implies that a robust and precise classifier is very plausible, given force signals.

Future research should focus on a complete controller using the information reported in this paper. This should allow for a robotic friction stir welder to detect and avoid faults in real time. This would improve manufacturing safety and yield.

This paper is applicable to the rapidly expanding robotic FSW industry. A great advantage of heavy machine tool versus robotic FSW is that the robot cannot supply the same amount of rigidity. Future work must strive to overcome this lack of mechanical rigidity with intelligent control, as has been examined in this paper.

This paper investigates fault detection in robotic FSW. Fault detection and avoidance are essential for the increased robustness of robotic FSW. The paper's results describe very promising directions for such implementation.

This paper aims to investigate two control mechanisms on the two parameters, namely, spindle speed and tool pin position, while performing friction stir welding (FSW) for aluminium metal matrix composites (Al-MMC) using the concept of system identification.

FSW is a feasible choice for joining of Al-MMC over the fusion welding due to the formation of the narrow heat-affected zone and minimizing the formation of intermetallic compounds at weld interface. The goal in FSW is to generate enough thermal energy by friction between the workpiece and rotating tool. Heat energy is generated due to mechanical interaction because of the difference in velocity between the workpiece and rotating tool. The generated heat is proportional to the tool pin position and the spindle speed. In the present work, a Smith Predictor Control scheme and adaptive control scheme are developed during joining of Al6061/SiC/B4C Al-MMC by FSW. Adaptive controller is developed to control the tool pin position while Smith Predictor control is developed to control the spindle speed. Initially, the Al-MMC plates are prepared at five combinations of SiC and B4C reinforcements and welded at three level parameter settings followed by tensile testing. The experimental data are used in estimating the plant transfer function model using system identification. The control schemes are then developed for the estimated plant model and the same are validated using a standard PID controller. In both the control schemes, PID controller results in a sluggish response. Experimental validations are performed for the developed control schemes followed by microscopic studies of the weldments.

In both the control schemes, PID controller results in a sluggish response. Experimental validations are performed for the developed control schemes followed by microscopic studies of the weldments.

Results from the study concluded that the developed MRAC and Smith predictor scheme effectively controlled the vibrations and spindle speed effectively.

It is observed that the scanning electron microscopy micrographs of the Al-MMC’s welded using developed control schemes resulted in good boding with homogenous distribution of reinforcement particles.

This paper aims to comprehensively review ultrasonic additive manufacturing (UAM) process history, technology advancements, application areas and research areas. UAM, a hybrid 3D metal printing technology, uses ultrasonic energy to produce metallurgical bonds between layers of metal foils near room temperature. No melting occurs in the process – it is a solid-state 3D metal printing technology.

The paper is formatted chronologically to help readers better distinguish advancements and changes in the UAM process through the years. Contributions and advancements are summarized by academic or research institution following this chronological format.

This paper summarizes key physics of the process, characterization methods, mechanical properties, past and active research areas, process limitations and application areas.

This paper reviews the UAM process for the first time.