自动化立体车库管理系统的研究(英文文献+CAD图纸)
be changed to something like completing production at the earliest possible time or minimizing defects. The change of the goal in high level gives rise to the changes of the goals in subfractals. At the bottom-level, when a fractal controls a machining center, shortening the processing time or the optimization of tool paths may be exemplary goals. From the top-level to the bottom-level, the goals of each fractal are sequentially generated and pruned by the goal-formation process. Each goal is achieved and assessed in the opposite direction after the goal-formation. Warnecke [13] pointed out that the goalformation process is a reliable method for revealing any conflicts between competing goals. The system should allow fractals to negotiate their goals with other fractals at any time, since it is very hard to anticipate which situations will require negotiation.
 Fig. 8. Activity diagram for dynamic restructuring process.
The negotiation in the MANPro has four phases: (1) preparation, (2) cloning, (3) traveling and evaluation, and (4) awarding [27]. Figs. 9 and 10 illustrate the MANPro-based negotiation process and the activity diagram of NEA, respectively. When a fractal needs to negotiate with others, the DMA during the preparation phase determines a route for agent’s traveling and creates a NCA. Then, during the cloning phase, the DMA creates a NEA containing information about a negotiation, pre-evaluation, and con?ict-resolution methods. After moving to the reporter, the NEA is encrypted by the NCA and then starts the navigation following its traveling list to gather negotiation replies from others. During a traveling and evaluation phase, the NEA pre-evaluates negotiation replies from other fractals. If the reply does not meet the pre-evaluation requirement, then it is dropped. Otherwise, it is added to the reply_list. To simplify the UML model in Fig. 10, the pre-evaluation activity is modeled as one activity. After making a complete reply_list, the NEA goes back to the DMA and reports the results necessary for the decision-making. If DMA determines an awardee (fractal), then it generates TGAs and sends them to the awardee after they are encrypted by NCAs. When the fractal receives tasks from the issuer, it sends back an acceptance message so that the issuer can destruct the NEA that was used for the negotiation.
5. Data management in the FrMS
5.1. Data model for resources in the FrMS
Resources in this paper mean physical equipment in the FrMS such as robots, milling machines, turning machines, and so on. A manufacturing system is made up of a number of items of equipment. Wysk et al. [28] identified several classes of equipment, which have now been used as a basis for classification in this research. Equipment is classified into four major types including material processor (MP), material handler (MH), material transporter (MT), and buffer storage (BS). Each piece of equipment in the factory is classi?ed as belonging to one and only one of these classes. Formally, the equipment (E) is de?ned according to the following set notation, and modeled with the UML class diagram as shown in Fig. 11.
 Fig. 9. MANPro-based negotiation in the FrMS.
E = (MP; MH; MT; BS)
Where
MP=(MRP; MFP; MIP; PD);
MH=(FMH; MMH);
MT=(FMT; MMT); BS=(ABS; PBS):
Equipment that transforms a product is classi?ed as belonging to the MP class. MP is partitioned into four different classes including material removal processor (MRP), material forming processor (MFP), material inspection processor (MIP), and passive device (PD). Equipment belonging to MRP, MFP, or MIP requires an equipment controller whereas PD equipment does not need one. Equipment classified into MRP performs chip-making processes or material

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