自动化立体车库管理系统的研究(英文文献+CAD图纸)
activity, and the evolution to CIM has been slower than expected [4,5]. This can be directly attributed to high software development and maintenance costs. Therefore, in order to achieve a competitive advantage in the turbulent global market, the manufacturing enterprise must change manufacturing processes from all angles including ordering, product design, process planning, production, sales, etc. As a control model for implementing CIM systems, hierarchical decomposition of shop floor activities has been commonly used in the shop floor control system (SFCS), the central part of a CIM system [2]. Generally, a central database provides a global view of the overall system, and controllers generate schedules and execute them. Hierarchical control is easy to understand and is less redundant than other distributed control architectures such as heterarchical control. However, it has a crucial weak point, which is that a small change in one level may significantly and adversely affect the other levels in the hierarchy. Therefore, it is normally said that hierarchical control of CIM systems is much more suitable for production in a steady environment than in a dynamically changing environment because it is so diffcult to apply control hierarchy changes immediately to the equipment. Furthermore, it is diffcult to meet dynamically changing customer requirements because the hierarchical control architecture is not flexible enough to handle the reconfiguration of the shop. Therefore, the manufacturing system of tomorrow should be flexible, highly reconfigurable, and easily adaptable to the dynamic environment. Furthermore, it should be an intelligent, autonomous, and distributed system composed of independent functional modules. To cope with these requirements, new manufacturing paradigms such as a bionic/biological manufacturing system (BMS) [6,7], a holonic manufacturing system  (HMS) [8,9], and a fractal manufacturing system (FrMS) [10–13] have been proposed. Tharumarajahet al. [14] provide a comprehensive comparison among a BMS, a HMS, and an FrMS in terms of design and operational features. An FrMS is a new manufacturing concept derived from the fractal factory introduced by Warnecke [13]. It is based on the concept of autonomously cooperating multi-agents referred to as fractals. The basic component of the FrMS, referred to as a basic fractal unit (BFU), consists of five functional modules including an observer, an analyzer, a resolver, an organizer, and a reporter [10,11]. The fractal architectural model represents a hierarchical structure built from the elements of a BFU, and the design of a basic unit incorporates a set of pertinent attributes that can fully represent any level in the hierarchy [12]. In other words, the term ‘fractal’ can represent an entire manufacturing shop at the highest level or a physical machine at the bottom-level. Each BFU provides services according to an individual-level goal and acts independently while attempting to achieve the shoplevel goal. An FrMS has many advantages for a distributed and dynamic manufacturing environment. Automatic reconfiguration of a system through a dynamic restructuring process (DRP) is the most distinctive characteristic of the FrMS. In this paper, the scope of the reconfiguration does not include reconfigurable hardware [15] and external layout design. Rather, it focuses on the interior structure of software components that can be reorganized with software manipulations. The reconfiguration or restructuring in this paper considers both dynamic clustering of the agents and construction/destruction/cloning of agents, which affect the number of agents in the system. The function of a fractal is not specifically designated at the time of its first installation in the FrMS. The reconfiguration addressed in this paper also includes situations where the agents’ enrollments are changed, meaning that the agents are assigned a new goal and new jobs, but their composition does not change. This paper focuses on formal modeling of agents and fractal-specific characteristics that will provide a foundation for the development of the FrMS. Because associated difficulties have, to date, prevented a fractal-based system from being embodied, it is necessary to first explicitly define a concept, mechanisms, and characteristics.
The objective of this paper, therefore, is to clearly define and model fractal-specifc characteristics for a manufacturing system to have such

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