外文翻譯--不規(guī)則制造系統(tǒng)的動(dòng)態(tài)代理人模型和說明書

1、<p>　　附錄1：翻譯（英文）</p><p>　　Modeling and specifcations of dynamic agents in fractal manufacturing systems</p><p>　　Kwangyeol Ryua, Youngjun Sonb, Mooyoung Junga,*</p><p>　　a Dep

2、artment of Industrial Engineering, Pohang University of Science and Technology, Pohang, South Korea Systems and Industrial Engineering Department, The University of Arizona, Tucson, AZ, USA </p><p>　　b Re

3、ceived 9 September 2002; accepted 16 April 2003</p><p>　　Abstract In order to respond to a rapidly changing manufacturing environment and market, manufacturing systems must be flexible, adaptable, and reusab

4、le. The fractal manufacturing system (FrMS) is one of the new manufacturing paradigms that address the need for these characteristics. The FrMS is comprised of a number of ‘‘basic components’’, each of which consists of

5、five functional modules: (1) an observer, (2) an analyzer, (3) an organizer, (4) a resolver, and (5) a reporter. Each of these mod</p><p>　　Abbreviations: FrMS, fractal manufacturing system; BFU, basic fract

6、al unit; DRP, dynamic restructuring process; UML, uni?ed modeling language; HMS, holonic manufacturing system; BMS, bionic/biological manufacturing system; CNP, contract net protocol; MANPro, mobile agent-based negotiati

7、on process; NMA, network monitoring agent; EMA, equipment monitoring agent; SEA, schedule evaluation agent; DRA, dispatching-rule rating agent; RSA, real-time simulation agent; SGA, schedule generation agent; GFA,</p&

8、gt;<p>　　* Corresponding author. Tel.: t82-54-279-2191; fax: t82-54-279-5998.</p><p>　　0166-3615/$ – see front matter # 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0166-3615(03)00099-X </

9、p><p>　　1. Introduction</p><p>　　Facing intensified competition in a growing global market, manufacturing enterprises have been reengineering their production systems to achieve computer integrated

10、 manufacturing (CIM). Major goals of CIM include, but are not necessarily limited to, lowering manufacturing costs, rapidly responding to changing customer demands, shortening lead times, and increasing the quality of pr

11、oducts [1–3]. However, the development of a CIM system is an incredibly complex activity, and the evolution to CIM h</p><p>　　The objective of this paper, therefore, is to clearly define and model fractal-sp

12、ecifc characteristics for a manufacturing system to have such characteristics. In order to develop the agents, interand intra-fractal activities are first clarified. Then, dynamic activities for each agent and relationsh

13、ips 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 deal</p><p>

14、　　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

15、 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 reorganiz

16、ed in response to unexpected events such as machine breakdown.</p><p>　　Fig. 1. Reorganization of the system using a dynamic restructuring process in the FrMS.</p><p>　　However, when the target

17、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 manufactur

18、ing 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

19、 has similar functions to those of </p><p>　　Fig. 2. Functional modules and relationships of a fractal in an FrMS.</p><p>　　transmit composite information to correspondent fractals. The function

20、 of an analyzer is to analyze alternative job profiles with status information, to rate dispatching rules, and to simulate analyzed job profiles in real-time. The analyzer finally reports results to the resolver so that

21、the resolver can use them to make decisions. A resolver plays the most important role in a fractal, generating job profiles, goal-formation processes, and decision-making processes. During goal-formation proces</p>

22、<p>　　2.2. Agents in an FrMS </p><p>　　Agent technology has been widely used for various applications including information filtering and gathering [16], knowledge management [17], supply chain ma

23、nagement [18], manufacturing architecture, system and design [19–21]. While the features and characteristics of an agent vary depending on the application, some common features found across different applications are as

24、follows: Autonomy: capability of controlling and acting for itself in order to achieve goals. Mobility: capability of migra</p><p>　　2.2.1. Agents for an observer</p><p>　　Network monitoring age

25、nt (NMA-S): It monitors messages from other fractals through TCP/IP. It receives messages from the upper/same/lower-level fractals, such as requests for negotiations, negotiation replies, job orders, status information,

26、etc. The NMA delivers those messages to the resolver or the analyzer. Equipment monitoring agent (EMA-S): It monitors messages directly coming from equipment through a serial communication protocol such as RS232/ 422. In

27、formation on the status of equipment i</p><p>　　2.2.2. Agents for an analyzer </p><p>　　Schedule evaluation agent (SEA-S): A SEA evaluates job profiles generated by the resolver. It helps the re

28、solver to select the best job profile with respect to the current situation of the fractal. Dispatching-rule rating agent (DRA-S): It chooses the best dispatching rule for achieving its goals among several rules, such as

29、 shortest processing time (SPT), earliest due date (EDD), and so on. Real-time simulation agent (RSA-S): It performs real-time simulations in the on-line state with the resul</p><p>　　2.2.3. Agents for a res

30、olver</p><p>　　Schedule generation agent (SGA-M): It generates operational commands or alternative job profiles for achieving the fractal’s goals. After evaluation and analysis of alternatives in the analyze

31、r, the SGA selects the best job profile. It must have mobility in order to use SEA, DRA, and RSA in the analyzer.</p><p>　　Goal formation agent (GFA-S): It modifies incomplete goals delivered from the upper-

32、level fractal, and tries to make the goals complete by considering the current situation of the fractal. GFA divides the goal of the fractal into several sub-goals, and sends them to the sub-fractals. Task governing agen

33、t (TGA-S): A TGA generates tasks from the best job profile and its goals. It also performs tasks after arriving at the target fractal. When it finishes performing tasks, it sends acknowledgement t</p><p>　　2

34、.2.4. Agents for an organizer</p><p>　　Fractal status manager (FSM-S): The FSM collects and manages the information on the status of fractals that is used for analyzing job profiles in the analyzer. It also

35、makes negotiation replies to the status requests from other fractals. Fractal address manager (FAM-S): The FAM manages information about the addresses of fractals in lower levels and at the same level. A fractal address

36、is the fractal’s physical address on the network, such as an IP address. The reporter uses a fractal’s address t</p><p>　　2.2.5. Agents for a reporter </p><p>　　Network command agent (NCA-M): Al

37、l tasks or messages are delivered to other fractals by the NCA. NCA gets the network address of the destination from the FAM and notifies the TGAs and NEAs of it before starting to migrate to other places to comply with

38、the traveling list. Equipment command agent (ECA-S): When ECA gets tasks for controlling equipment from a TGA, it specifies or divides the tasks into several commands that can be accepted and performed by the equipment.

39、Then it sends the machine c</p><p>　　2.3. Agent modeling with UML </p><p>　　To make system architecture manageable and understandable, the artifacts of a system-intensive process can be expresse

40、d, specified, visualized, constructed, and documented. In recent years, a unified modeling language has emerged from earlier methods for analysis and design of object-oriented (OO) systems. In 1997, UML became recognized

41、 and accepted as a potential notation standard by Object Management Group (OMG) for modeling multiple perspectives of various systems [23]. UML is a simple, expre</p><p>　　2.3.1. Why UML? </p><p&g

42、t;　　UML provides several advantageous features for modeling a system [25]. First, it enables modeling of systems using OO concepts because its semantics come from Booch, object modeling technique (OMT), and object-orient

43、ed software engineering (OOSE). In particular, the use of a ‘‘package’’supporting OO concepts allows users to refine models iteratively. Second, it uni?es several modeling perspectives, enabling modeling of different kin

44、ds of systems (business versus software) and different developme</p><p>　　The fractal agents are modeled by using a class diagram as shown in Fig. 3. A class diagram describes the types of objects that are u

45、sed within an objectoriented system, and de?nes the types of relationships between them. Attributes and operations of each class are used to de?ne the types of objects and the constraints between them. Four types of rela

46、tionships available in the class model of UML are association, aggregation, generalization, and dependency (instantiates). The class diagram in Fig</p><p>　　Fig. 3. Class diagram of fractal agents.</p>

47、<p>　　Fig. 4. The class diagram of DMA.</p><p>　　The activities and transitions of the states of the DMA are modeled via the activity diagram in Fig. 5. A rectangle with rounded ends is used to de?ne

48、an activity or a behavior of an object; a rounded rectangle is used to represent a state of an object in the activity diagram; and a diamond is used when a decision is needed. Transitions between actions or states are re

49、presented as an arrow. Transitions may have events, a stereotype, arguments, conditions, and actions with such UML syntax as ‘‘ev</p><p>　　Fig. 5. The activity diagram of DMA.</p><p>　　symbolic

50、values (c0, c1, . . ., c8) to simplify the diagram. ha; b; ci indicates that one of a, b, or c is a prerequisite ?ow for the condition, and [a] means that the condition cannot be applicable after a. Other logic (activiti

51、es, states, decisions, and transitions) in Fig. 5 can be inferred from the English in the figure.</p><p>　　3. Activities of agents in the FrMS </p><p>　　In the FrMS, agents handle all processes

52、and jobs without human intervention. Some activities are processed within the fractal, while other activities require cooperation with other agents that exist in another fractal. Activities of agents are classified into

53、two categories: intra-fractal activity (the activities that are processed in one fractal) and inter-fractal activity (the activities that are processed by the cooperation of several fractals). The classification of activ

54、ities of agents in </p><p>　　3.1. Intra-fractal activity In order to control an FrMS, agents are involved in processing jobs with their specific roles. The activities of agents that are performed within a fr

55、actal are similar to those of other manufacturing systems including input/output control, scheduling, task generation, performance of tasks, and equipment control. Inputs from other fractals and equipment are controlled

56、by the NMA and EMA, respectively. Many agents must cooperate for scheduling activities. The agents dea</p><p>　　3.2. Inter-fractal activity</p><p>　　A negotiation between fractals is the most im

57、portant process in an FrMS because it is essential in order for the agents to make decisions and to process jobs autonomously and coherently.</p><p>　　Fractal Intra-fractal activity ? Input/output control ?

58、Scheduling ? Task generation ? Real-time simulation ? Information management ? Job (task) processing ? Database control ? Equipment control ? Intra-decision-making</p><p>　　Inter-fractal activity ? Negotiati

59、on ? Goal-orientation process ? Dynamic restructuring process Fractal Intra-fractal activity</p><p>　　···· Fig. 6. Intra- and inter-activity of agents.</p><

60、;p>　　Fig. 7. CNP-based negotiation vs. MANPro-based negotiation.</p><p>　　NEA is in charge of negotiation, which is created by DMA. To impose a negotiation ability on agents, the contract net protocol (CN

61、P) proposed by Smith [26] is still widely used. However, the CNP is expensive in terms of network bandwidth when the negotiation process implies a heavy communication load. For this reason, the negotiation process in thi

62、s paper follows the MANPro introduced by Shin et al. [27]. The MANPro applies the mobility and the cloning mechanism of an agent. The greatest advanta</p><p>　　Agents in the FrMS always pursue their own goal

63、s. If necessary, they issue a bid and negotiate with others to make a complete goal. The goal-formation process is the process of generating goals by coordinating processes among participating fractals and modifying them

64、 as necessary [13]. The GFA is the agent that exists for this purpose. The GFA receives an incomplete goal from a NMA and makes sub-goals or modifies the current goal of the fractal. During the goal-formation process, th

65、e GFA coopera</p><p>　　4. Fractal-specific characteristics and UML models </p><p>　　Characteristics that differentiate an FrMS from other manufacturing systems include (1) self-similarity, (2) s

66、elf-organization, and (3) goal-orientation. Speci?cally, the dynamic restructuring process, which is part of self-organization, is the most distinctive characteristic. This section describes fractal-speci?c characteristi

67、cs with respect to UML models, focusing on their procedures and the relationships among participating agents.</p><p>　　4.1. Self-similarity </p><p>　　Self-similarity, an inherent characteristic

68、of a fractal, refers not only to the structural characteristics of organizational design, but circumscribes the manner of performing a job (service), as well as the formulation and pursuit of goals [13]. To achieve goals

69、 in a manufacturing system, there can be various possible solutions with respect to the individual problems. Even if there may exist several components with the same goal in the system, conditions or situations in the su

70、rrounding enviro</p><p>　　4.2. Self-organization</p><p>　　Self-organization is related to a theoretical method and an operational method in the FrMS. The theoretical method referred to as self-o

71、ptimization is de?ned as the application of suitable numerical approaches to optimize the performance of fractals in a system. It provides the FrMS with a mathematical background for designing the structures, composition

72、s, and relationships of fractals. From various optimization techniques, fractals select and use a proper method to have a more optimal specifica</p><p>　　4.3. Goal-orientation</p><p>　　Goal-orie

73、ntation corresponds to the motivated activities of agents in fractals. To coherently achieve agents’ and fractals’ goals during the process, goal consistency, which is supported by an inheritance mechanism, should be mai

74、ntained. The FrMS continues to develop each goal autonomously in order to operate and harmonize the system by resolving confiicts. Basically, efficient production may be a usual goal. In accordance with the surrounding e

75、nvironment, however, a goal may be changed to somet</p><p>　　Fig. 8. Activity diagram for dynamic restructuring process.</p><p>　　The negotiation in the MANPro has four phases: (1) preparation,

76、(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 other

77、s, 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, an<

78、/p><p>　　5. Data management in the FrMS </p><p>　　5.1. Data model for resources in the FrMS</p><p>　　Resources in this paper mean physical equipment in the FrMS such as robots, milling

79、 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 classificatio

80、n 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 equipme</p><p>　　

81、Fig. 9. MANPro-based negotiation in the FrMS.</p><p>　　E = (MP; MH; MT; BS)</p><p><b>　　Where</b></p><p>　　MP=(MRP; MFP; MIP; PD); </p><p>　　MH=(FMH; MMH);

82、</p><p>　　MT=(FMT; MMT); BS=(ABS; PBS):</p><p>　　Equipment that transforms a product is classi?ed as belonging to the MP class. MP is partitioned into four different classes including material r

83、emoval 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 n

84、ot need one. Equipment classified into MRP performs chip-making processes or material</p><p>　　Fig. 10. Activity diagram of NEA.</p><p>　　removal processes, e.g. machining centers, turning machi

85、nes, drilling machines, and so on. Equipment classified into MFP performs shape-changing processes without making chips from a product, e.g. forming, forging, assembly, and so on. All equipment that inspects a product be

86、longs to MIP. Equipment classified into PD performs auxiliary processes without changing material volume or shape. For example, PD equipment may change a product’s orientation or some non-geometrical property of the prod

87、uct.</p><p>　　Equipment that transfers products between pieces of equipment is in the MH class. MH normally indicates several types of robots, and it is partitioned into fixed material handler (FMH) and mova

88、ble material handler (MMH). The controller of MH class equipment requires synchronization with equipment associated with the transfer of products. If a robot operates within a designated position without moving, it belon

89、gs to FMH; otherwise it belongs to MMH. Human operators also can be classified as MMH.</p><p>　　Fig. 11. Class diagram for classification of equipment.</p><p>　　Equipment that moves products fro

90、m one location to another location is in the MT class. MT is partitioned into fixed material transporter (FMT) and movable material transporter (MMT) in the same way that the MH class is partitioned. Conveyors belong to

91、FMT, and AGVs, fork trucks, and human operators belong to MMT. </p><p>　　Equipment that stores products is in the BS class. General equipment that stores products is classified into either ABS or PBS. If sto

92、rage equipment requires its own controller, it belongs to the ABS class; otherwise it belongs to the PBS class. Some requirements for ABS equipment controllers include synchronization with MH class equipment, location al

93、location, capacity control, etc. Since PBS equipment does not have its own controller, it must be controlled and maintained by some other controll</p><p>　　5.2. Information for controlling equipment</p>

94、;<p>　　The information and messages used in the FrMS can be classi?ed into two major categories: (1) durable information and messages and (2) instantaneous information and messages. ‘‘Durable’’ means the operation

95、s and communication messages that exist during the entire lifecycle of a fractal. When a fractal is created for the purpose of controlling equipment, it can handle control-related operations and messages until it is dest

96、ructed or its role is changed. On the other hand, ‘‘instantaneous’’ descri</p><p>　　5.3. Management of resource data</p><p>　　The management of resources in the FrMS is modeled by using a use-ca

97、se diagram of UML as illustrated in Fig. 12. A use-case can be described as a specific way of using the system from a user’s perspective. A use-case diagram contains actors, use cases, and interactions or relationships b

98、etween actors and use cases. Types of interactions include associations, dependencies, and generalizations. </p><p>　　The agent called FSM manages information about the resources. If a fractal becomes an equ

99、ipment controller, the FSM manages equipment status while dealing with equipment commands or signals as well as fractal status. In addition to the FSM, the following agents are also related to the equipment: (1) FAM, (2)