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機械設(shè)計制造及其自動化外文翻譯-----柔性制造系統(tǒng)的發(fā)展運用在實際制造中的范例-機械設(shè)計(編輯修改稿)

2025-06-25 23:44 本頁面
 

【文章內(nèi)容簡介】 of class corresponding to the real manufacturing cell is shown in , and represents the factory model. In VFMC, characteristics of the factory model include a detailed representation of machine behavior over time, a structure to the model that can configure and reconfigure easily, and a realistic and threedimensional animation of machine behavior over time. Virtual machines defined within this model may be used to estimate accurately the merit of a process plan, and, based on this evaluation, determine appropriate process conditions to improve (and even optimize) the plan. Virtual robot contributes to unload and load parts into/from machines, and is used to find optimal paths without any collisions. With virtual operation, the fidelity of the machining and robot utilizing time and cost estimates is expected to improve. In addition, accurate modeling will predict the quality of the machined part, which cannot be determined easily and reliably without producing several physical prototypes. This information is invaluable to both the designer and the process planner. Physical entities such as machines and workpieces have the explicit representation as 3D models for their shapes, positions, and orientations. 3D models are conveniently used for calculating, geometrical attributes, checking spatial relations, and displaying puter graphics. Process model By assigning a finite set of states to each device in a cell (idle, busy, failed, etc.), the process of cell control can be modeled as a process of matching specific state change events to specific cell control actions, decision algorithms, or scripts. With this model, cell processes are represented a Task Initiation Diagram (TID) using an objectoriented approach. The methodology behind developing TID regards the tasks to be performed by the cell or any of its constituent machines for being primal, and employs the multilayered approach. Sensory signals indicating the change of state of machines are used to trigger or initiate tasks. A task may be simple and require a relatively short 5 time to execute, or may be plex and lengthy. Formally, a Task Initiation Diagram (TID) is defined as the fourtuple TID=(T, SR, C, O). Task Initiation Diagrams are posed of two basic ponents: a set of Rest states SR and a set of tasks T. Tasks, in turn, are classified into three groups: the cell configuration dependant task (Td), the cell configuration independent task (Ti), and the cycle transit task (Tt). Cell configuration dependent tasks are those which require some coordination among cell ponents to carry out the task. For example, the task load as in aRobot load a part to:aMill requires that the actions of aRobot and aMill be coordinated. Cell configuration independent tasks require only one cell ponent to perform the task. The task move To as in Robot move to:MachineName configuration independent one, because it is carried out by the Robot without interacting with other ponents. Tt tasks are used for the transition from one cycle to another, and thus derived automatically by the system in order to plete a production job. State SR indicates rest states where cell constituents must be wait for next task. This state is given at any instant by the collection of states of its constituents. These posite states are depicted in the Task Initiation Diagram by ellipses, ., R11/3 or M13/4. The last number of the symbols indicates how many individual states are required to determine this posite state. To plete the diagram, it is necessary to define the relationship between the states and the tasks. This can be done by specifying two functions connecting states to tasks: the condition functionC, and the output functionO. The condition function C defines, for each task Ti, the set of states for task C(Ti). Some condition functions may use guiding parameters in addition to a set of states. As an example, C(Tt) uses a Remaining Processing Time (RPT) to cause transition to the desired state. The output function O defines for each Task Ti the set of output States for the transition O(Ti). The Operation Initiation Diagram (OID) is the second layer diagram of the Task Initiation Diagram (TID). In the same way of TID to represent the model, the Operation Initiation Diagram OID is defined as the fourtuple, OID(task)=(OP,Sv,C,O). The symbol OP defines set of operation required for a given task. The operation, OP, is categorized into two groups: guided operations OPg and unconditional operations OPu. A guided operation is one that requires an external trigger to start it. Unconditional operations are ones that start automatically on the onset of all the necessary states. The symbol Sv indicates the set of visitstate. The visitstate, Sv, indicates an interaction between two machines and hence requires coordination among them. The symbol of this state has the pattern RM for the robot, as an example, the state RvMnm. The small letter v represents the visitstate of the robot associated with location, Mn represents a machine served by the robot, and m represents the index of one of the visit locations. During the pletion of the task, the busy states are employed, and indicate 6 transitional states between operations or two executions without interaction. They can be recognized from the robot state symbol, Rtn. The small letter t indicates the state of the robot associated with transition. These states are useful in avoiding collisions with obstacles. The condition operator C, defines the set of state and guiding conditions necessa
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