Brooks Automation (United States)

In this talk we present a statistical model for quantifying the thermal ionization process of an excited impurity ion in a level just below the conduction band of the host while the impurity ion is under constant excitation. YAG:Ce is used as an example. We assume that under constant pumping of the Ce3+ ion into the 5d1 with a blue LED, a condition of thermal and diffusive equilibrium will exist between the conduction electrons and the electrons in the excited 5d1 level of Ce3+ ion. Using the Gibbs sum, we calculate the probability for an excited Ce3+ ion to be thermally ionized, leading to an electron in the conduction band. The density of conduction electrons is then calculated over a wide range of temperatures and excitation densities. The observed quenching of emission at high temperature in Ce-doped YAG with low Ce concentrations is also investigated within this model. It is shown that the experimentally-observed nonradiative losses in this phosphor can be reasonably simulated assuming losses occur via nonradiative decay from the conduction band to the Ce4+ ground state.

Recently a major trend in flexible and precision assembly automation, and in automation in general, has been in robots that can safely work next to people. Increasingly, as part of collaborative automation, such robots are also designed to collaborate as teams with other robots. These intelligent machines are called cobots, or collaborative robots, and are reducing the cost and time to install robots in many applications. Flexible and precision assembly refers to an assembly system that can build multiple similar products with little or no reconfiguration of the assembly system. It can serve as a model for some of the emerging applications in flexible and precision automation. Precision assembly implies assembly with precise motions and operations. Recently, machine learning interacting with the robots’ sensors enables robots to assemble parts and components with precision that exceeds their own motion precision. A truly flexible assembly system would enable precision assembly, include flexible part feeding, grasping, and fixturing, as well as a variety of mating and fastening processes that can be quickly added or deleted without costly engineering. There is a limited science base for how to design flexible assembly systems in a manner that will yield predictable and reliable throughputs. The emergence of geometric modeling systems (as part of CAD) has enabled work in geometric reasoning in the past few years. Geometric models have been applied in areas such as machine vision for object recognition, design, and throughput analysis of flexible part feeders, dynamic simulation of assembly stations and assembly lines. Still lacking are useful techniques for automatic model generation, planning, error representation, error prevention (avoidance), and error recovery. Future software architectures for flexible and precision automation should include geometric modeling and reasoning capabilities to support autonomous, sensor-driven systems.

In plain English, this simply means that the more light there is, the higher the voltage drop through the photo resistor.

In this chapter we will introduce a 7 segment display counter design. The counter counts from 0 to 9 and then resets to 0 and starts again. The Raspberry Pi can also send a control message to force the counter to have a particular value. We will re-use all of the VHDL code from Chapter 15 and add a 7 segment display counter module.

Substrate-handling robots for pick-place operations in semiconductor manufacturing applications are subject to strict substrate placement repeatability specifications. It has been observed that the placement locations at a given workstation tend to exhibit distinct clusters, each of which can be associated with another workstation accessed by the robot in the past, resulting in an undesirable increase of the overall placement repeatability range. In the present paper, this memory-like repeatability phenomenon is studied, and attributed to multistage synchronous belt drives, which are utilized to transmit motion from centralized motors to individual links and end-effectors of the robot arms. The phenomenon is investigated experimentally, and simulated using a simplified lump-parameter model. The effects of selected belt drive design parameters are examined, and the results are utilized to improve the positioning repeatability performance of a typical substrate-handling robot.

PurposeThe purpose of this paper is to investigate the vibration suppression of industrial track robot and propose a practical solution.Design/methodology/approachRoot‐cause analysis through dynamic modeling, and vibration suppression using the acceleration smoother.FindingsThe vibration is due to insufficient damping based on the model analysis. The solution achieved significant performance improvement without redesign of robot hardware and controller.Research limitations/implicationsThe design of the proposed acceleration smoother is still empirical based, which is unable to achieve optimal design.Practical implicationsThis solution is very easy to implement. It is robust, reliable and is able to generate consistent results.Originality/valueA very practical industrial solution, especially useful for upgrading the existing systems in the field without redesign the hardware and controller.

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An actuation mechanism for a dual-arm scara-type robot for automated pick-place operations in semiconductor and flatpanel-display manufacturing applications is described. The mechanism consists of a pivoting platform and two linkages coupled to the platform through a pair of revolute joints. The opposite ends of the linkages are connected to the upper arms of the robot by another pair of revolute joints, forming a pair of three-bar mechanisms coupled through the pivoting platform. When the platform is in its neutral position, both of the arms are retracted. The geometry of the components of the mechanism is selected so that rotation of the platform from the neutral position in one direction produces desirable radial motion of one arm while the other arm is kept almost stationary in the retracted position. The arms exchange their roles when the platform rotates from the neutral position in the opposite direction. Alternatively, to achieve absolutely no motion of the retracted arm while the other one extends, the pivoting motion of the platform can be replaced by a rocking arrangement with two pivot points. In this configuration, the locations of the two pivot points coincide with the locations of the revolute joints between the linkages and the upper arms when the platform is in the neutral position. As a result, rotation of the platform with respect to one of the pivot points produces no motion of the corresponding arm while the other one extends. Compared to a conventional design, which utilizes a pair of motors coupled to the robot arms through a pair of belt arrangements, the present mechanism eliminates one of the two motors, including its electronic circuitry, and replaces the belt drives with rigid linkages, thus reducing the complexity and cost, and improving the reliability and cleanliness of the robotic system.

This paper describes a Genetic Algorithm (GA) based approach for area coverage using micro-robots. The method can be used for controlled drug delivery or tumor treatment using micro-robots. The algorithm aims to find a near-optimal path that covers a given area entirely, except obstacles defined as biological barriers or drug side effect restricted zones. The proposed GA approach is a dynamic online path planning approach, which is able to achieve planning during motion and to response to detected obstacles. Different from point-to-point path planning, the proposed operators for the GA are specially designed for area coverage. Comparisons of the approach with high-level static optimal search algorithms and low-level fixed path planning approaches are also presented. Simulation results are given to show the effectiveness of the approach.

Aggressive throughput performance of automated tools for semiconductor and flat-panel-display manufacturing applications have led to development of substrate-handling robots with multiple end-effectors. For maximum throughput levels, a method for calculating a time-optimum substrate transfer trajectory without causing any of the substrates carried by the robot to slide, and without violating other prescribed constraints, is required. This paper presents an algorithm which provides the required functionality with desirable computational efficiency and reliability. The key idea is to identify the set of fundamental trajectory shapes which cover all possible combinations of constraints for a given category of moves, e.g., moves along a straight line or along a circular arc, decompose the fundamental shapes into segments where a single constraint is active, and determine the time-optimum motion profiles in the segments. The fundamental shapes for each of the categories are found as simplified versions of the generic shape which corresponds to the case when all of the constraints are active. Each of the shapes has a set of conditions associated with it to determine whether the shape can be used for a particular move. An example comparison of a motion profile generated based on pre-defined time-optimum shapes with a conventional s-curve trajectory demonstrates that the present algorithm produces substantially faster motion, resulting in an improved throughput performance of the robot.