自动化立体车库管理系统的研究(英文文献+CAD图纸)
characteristics. In order to develop the agents, interand intra-fractal activities are first clarified. Then, dynamic activities for each agent and relationships between agents are modeled. In order to more fully develop the FrMS, several fractal-specific characteristics are also modeled. To support embodiment of modeled characteristics, a method for dealing with information about products, orders, and resources in the FrMS is investigated. Through this research, mechanisms of agents and characteristics of the FrMS can be described with simple diagrams that make the system easier to understand. The work contained in this paper extends the FrMS from previous papers by emphasizing and detailing its characteristics. The activities of agents are specified using activity models so that the agents can use the activity models to forecast their next activities at run-time. The rest of this paper is organized as follows: Section 2 describes functions and dynamic activities of agents using functional and activity models of unified modeling language (UML). In Section 3, inter-  and intra-fractal activities are specified. Several fractal-specific characteristics are described using UML models in Section 4. Section 5 describes a method for dealing with information about products and resources in the FrMS. Section 6 concludes the paper.
2. Agent-based fractal manufacturing system (FrMS) 2.1. Background of an FrMS An overview of the FrMS is depicted in Fig. 1. Every controller at every level in the system has a selfsimilar functional structure composed of functional modules. In addition, each of these modules, regardless of its hierarchical level, consists of a set of agents. After the initial setup of a system, the configuration of the system may need to be reorganized in response to unexpected events such as machine breakdown. The system will also need to be reconfigured when the set of parts to be produced in the system changes due to a change in customer needs. In these cases, fractals in the FrMS autonomously and dynamically change their structure, via the actions of agents for the appropriate working mechanisms of the fractals. Fig. 1 shows two facility layouts and the corresponding compositions of fractals before and after the restructuring process. When a machine (M) and a robot (R3) are added to the system, fractals reorganize their interior configurations with the mechanism of dynamic restructuring process in a way that the system continues to work with greatest efficiency. A fractal consists of five functional modules illustrated with their relationships in Fig. 2. The functions of each module can be defined depending upon the application domain.
 
Fig. 1. Reorganization of the system using a dynamic restructuring process in the FrMS.
However, when the target domain is determined, the main functions of each module will be consistent throughout the system. For example, the function of a resolver may be different depending upon whether it is defined for controlling a manufacturing system or for managing supply chains. However, the main function of a resolver in a manufacturing system is similar to other resolvers in that system regardless of their level in the hierarchy. A bottom-level fractal has similar functions to those of a conventional equipment controller in a SFCS. A fractal, which is directly connected to equipment (e.g. machine, robot, etc.), receives sensory signals of equipment and returns messages or commands. The function of an observer is to monitor the state of the unit, to receive messages and information from outer fractals, and to

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