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It is well known that variations in the microstructure of lead free solders greatly affect their thermomechanical properties. Sn grain size, orientation and number, as well as secondary Ag3Sn and Cu6Sn5 precipitate sizes and numbers, are all seen to influence the mechanical response of solder joints during isothermal and thermal cycling. The solidification temperature of a SnAgCu solder joint dramatically affects its microstructure. Generally, smaller solder balls (e.g. CSP) undercool more, and thus their microstructure and properties are very different than larger solder balls (e.g. BGA).We report results of a study of the effects of solder joint volume, and pad sizes, on the microstructure and thermomechanical properties of solder joints. Solder joint shapes and dimensions spanned the ranges typical of BGA and CSP assemblies. Temperatures of solidification during cool-down were quantified by differential scanning calorimetry. Sn grain structures were characterized by crossed polarizer microscopy and scanning electron microscopy with electron backscattered diffraction. Precipitate sizes and distributions were measured using backscattered scanning electron microscopy. Corresponding properties, including hardness, strength and fatigue resistance were measured before and after aging for various lengths of times at temperatures up to 125ºC. Smaller solder joints on smaller pads were shown to be harder and stronger than larger ones, but to age faster and eventually end up softer and weaker. IntroductionThe thermomechanical response of near eutectic, SnAgCu solder joints depends upon solder microstructure. Sn is the major component in many Pb free alloys. Sn displays large anisotropies in its mechanical properties, so that the mechanical response of large grained, near eutectic, Sn-AgCu alloys depends upon Sn grain morphology. The distributions of Ag3Sn and Cu6Sn5 precipitates in this Pb free solder also affect its mechanical properties. To understand the mechanical behavior of Sn-Ag-Cu solder joints, the evolution of Sn grain morphologies, Sn grain orientations, and precipitate (Ag3Sn and Cu6Sn5) microstructures must be characterized.Near eutectic compositions (Ag and Cu concentrations near 3.5 and 0.9 weight percent respectively) of SnAgCu reveal β-Sn dendrites surrounded by a network of Ag3Sn and Cu6Sn5. The β-Sn dendrites are generally formed by growth from one of three Sn grains formed in a six-fold, cyclic twinning solidification event. Large differences in the numbers and sizes of the secondary Ag3Sn and Cu6Sn5 precipitates can exist from sample to sample and within given

In this study, a smart and affordable system that utilizes an RGB-D camera to measure the exact position of an operator with respect to an adjacent robotic manipulator was developed. This developed technology was implemented in a simulated human operation in an automated manufacturing robot to achieve two goals; enhancing the safety measures around the robot by adding an affordable smart system for human detection and robot control and developing a system that will allow the between the human-robot collaboration to finish a predefined task. The system utilized an Xbox Kinect V2 sensor/camera and Scorbot ER-V Plus to model and mimics the selected applications. To achieve these goals, a geometric model for the Scorbot and Xbox Kinect V2 was developed, a robotics joint calibration was applied, an algorithm of background segmentation was utilized to detect the operator and a dynamic binary mask for the robot was implemented, and the efficiency of both systems based on the response time and localization error was analyzed. The first application of the Add-on Safety Device aims to monitor the working-space and control the robot to avoid any collisions when an operator enters or gets closer. This application will reduced and remove physical barriers around the robots, expand the physical work area, reduce the proximity limitations, and enhance the human-robots interaction (HRI) in an industrial environment while sustaining a low cost. The system was able to respond to human intrusion to prevent any collision within 500 ms on average, and it was found that the system's bottleneck was PC and robot inter-communication speed. The second application was developing a successful collaborative scenario between a robot and a human operator, where a robot will deposit an object on the operator's hand, mimicking a real-life human-robot collaboration (HRC) tasks. The system was able to detect the operator's hand and it's location then command the robot to place an object on the hand, the system was able to place the object within a mean error of 2.4 cm, and the limitation of this system was the internal variables and data transmitting speed between the robot controller and main computer. These results are encouraging and ongoing work aims to experiment with different operations and implement gesture detection in real-time collaboration tasks while keeping the human operator safe and predicting their behavior.

This paper focuses on designing a search algorithm that the DustySWARM team used in the 2019 NASA Swarmathon competition. The developed search algorithm will be implemented and tested on multiple rovers, a.k.a. Swarmies or Swarm Robots. Swarmies are compact rovers, designed by NASA to mimic Ants behavior and perform an autonomous search for simulated Mars resources. This effort aimed to assist NASA's mission to explore the space and discover new resources on the Moon and Mars. NASA's going-on project has the goal to send robots that explore and collect resources for analysis before sending Astronauts, as the swarm option is safer and more affordable. All rovers must utilize the exact algorithm and collaborate and cooperate to find all available resources in their search path and retrieve them to the space station location. Additionally, swarmies will autonomously search while avoiding obstacles and mapping the surrounding environment for future missions. This algorithm allows a swarm of six robots to search an unknown area for simulated resources called AprilTags (cubes with QR codes). The code was developed using C/C++, GitHub, and Robotics Operation Systems (ROS) and tested by utilizing the Gazebo Simulation environment and by running physical trials on the swarmies. The team analyzed a few algorithms from previous years and other researchers then developed the Radiating L-Shape Search (RLS) Algorithm. This paper will summarize the algorithm design, code development, and trial results that were provided to the NASA Space Exploration Engineering team.

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