Browsing by Author "De Meter, Edward Christopher"

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    GIBSS: a framework for the multi-level simulation of manufacturing systems
    De Meter, Edward Christopher (Virginia Polytechnic Institute and State University, 1989)
    A systems approach for manufacturing system design calls for the division of a system design into sub-designs, and their specification over multiple levels of detail. Through an iterative design and evaluation process, a system design progresses from an abstraction to an implemental specification. To facilitate the evaluation process, models of sub-designs must be applicable to modular assembly, even if the sub-designs are heterogeneously specified. Computer simulation modeling is currently the most flexible method of manufacturing system analysis. When used in the multi-level design process, two forms of simulation models are encountered, uni-level and multi-level. A simulation model of a manufacturing system is considered uni-level if objects of equivalent type within the system are modeled at the same level of detail. On the other hand, a model is considered multi-level if objects of equivalent type are not modeled at the same level of detail. Unfortunately, current simulation frameworks do not integrate modular construction with the various discrete event and continuous simulation techniques needed to support multi-level modeling. This dissertation describes GIBSS (Generalized Interaction Based Simulation Specification), a simulation framework which supports the modular construction of uni-level and multi-level simulation models. Under GIBSS, the mechanisms and attributes of a manufacturing system simulation are distributed among various classes of independent sub-models. These classes are passive, internal interaction, external interaction, and master simulation. GIBSS describes the mechanics of each of these classes, as well as their method of synchronization. Using GIBSS, sub-models are created, executed, and validated independently, and then brought together to execute in parallel or near parallel fashion. As a result, uni-level and multi-level system simulation models are assembled from multiple sub-models. GIBSS eliminates a barrier to the rapid evaluation of manufacturing system designs. It facilitates the multi-level design process, and is the basis of a research effort, dedicated to the development of a new generation of computer-aided manufacturing system design environments.
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    The integration of visual and tactile sensing for the definition of regions within a robot workcell
    De Meter, Edward Christopher (Virginia Polytechnic Institute and State University, 1986)
    Vision systems are widely used in robot workcells for sensory feedback. The resolution of a vision system is usually good enough to locate an object so that it can be grasped, but not good enough to accurately locate an insertion hole. Tactile probes are used to accurately locate objects. However, they require a data base containing the approximate location of an object in order to be used effectively. This thesis presents the development of a robot workcell which utilizes a vision system and tactile probe to identify, locate, and orientate two types of circuit board fixtures. The vision system approximately locates the corner points of each fixture in the robot workcell. The tactile system uses the data base created by the vision system to conduct a tactile search for each fixture and to accurately define the coordinates of each corner point. After a fixture is accurately located, a region (sub-coordinate system) is defined about the fixture. The location of each insertion hole within a fixture is defined relative to the region and the robot subsequently inserts the tactile probe into each hole. The vision system developed can define any two dimensional object and can locate the corner points of any straight edged object, whose adjacent sides have an included angle greater than 90 degrees. The tactile system is self calibrating and has a repeatability of 0.009 inches. A probe insertion error analysis was conducted on the system. The average probe insertion error for the system was determined to be 0.0337 inches. In addition, it was determined that probe insertion error increases with the distance between a hole and the origin of its defining region, and that the major source of probe insertion error is the robot language's (AML/E Verion 4.0) inability to accurately define points within a region.