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Abstract: In the highly competitive market, cooperative multi-agent transaction and negotiation mechanism have become an important research topic. This paper uses multi-agent technology to construct a multi-section flexible manufacturing system (FMS) model, and utilizes simulation to build a manufacturing environment based on JADE framework for multi-agent to combine with dispatching rules, such as shortest imminent processing time (SIPT), first come first serve (FCFS) earliest due date (EDD), and Buffer Sequence. This paper finds that using multi-agent technique for multi-section FMS model can enhance the production efficiency in practice. Meanwhile, in this study, multi-agent systems combined with dynamic dispatching can be used to identify the best dispatching rules combination for achieving largest throughput, and thus it can provide the reference for production scheduling in advance. [Copyright &y& Elsevier]

In this paper, a layered network that interconnects a distributed queue subnetwork with another distributed queue bridge network is considered. As slot control scheme in this network, a loopback retransmission scheme preventing slot discarding and an adaptive node load control function are proposed. In the communication within the subnetwork, no transmitted slot is discarded during processing. However, it is necessary to consider protection against discarding due to buffer overflow in the bridge of the distributed queue bridge network interconnecting the subnetworks. In order to prevent reduction of slot use efficiency caused by discarding in the bridge, it is desirable to eliminate discarding. Also, in order to prevent discarding of slots arriving at the bridge from the subnetworks, slot transmission at each node must be controlled. In this paper, in order to prevent slot discarding caused by buffer overflow of the bridge, a method is proposed for loopback retransmission of the slot on the bridge network or subnetwork. It is shown that discarding can be eliminated. Also, the effectiveness of the method is confirmed by computer simulation. © 2006 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 89(11): 35–45, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.20267 [ABSTRACT FROM AUTHOR]

This paper describes research in the area of hybrid control using simulation including a suitable architecture and a test-bed developed for experimenting with hybrid manufacturing systems -- that is, manufacturing systems containing both continuous and discrete processing activities. The paper builds on the RapidCIM control system developed at Penn State University and makes innovations in this work including, integrating continuous simulation and discrete event simulation into a message-based process control system. Simulation technology is extended to support real-time communication to access remote databases, and pass messages, which are used to control hardware equipment performing both continuous processes and discrete activities. This makes possible the development of a generic hybrid control capability. In RapidCIM, software is automatically generated to control and coordinate the physical system. This can substantially reduce the cost of developing and integrating such systems, and allows a detailed simulation to be used for both analysis as well as for control. An experimental research prototype of such a hybrid control system has been constructed for the Pennsylvania State University Creamery, in which unit processes and operational decisions are integrated. [ABSTRACT FROM AUTHOR]

Interval number theory has been applied to many fields; however, its applications to production scheduling are seldom investigated. In this paper, interval theory is used for its low cost in uncertainty modeling and novel interval job shop scheduling problem is proposed. To build the schedule of the problem, the addition and comparison of two interval numbers are first introduced and then a decoding procedure is constructed by using the chromosome of operation-based representation. It is proved that the possible actual objective values are contained in interval objective. An effective genetic algorithm (GA) is presented and tested by using some randomly generated instances. Computational results show the effectiveness of the GA. [ABSTRACT FROM AUTHOR]

This paper presents an integrated computer simulation, goal programming, and design of experiment (DOE) algorithm to solve the jobshop scheduling problem with multiple objectives. The proposed algorithm is applied to an actual textile dyeing, printing, and finishing workshop for minimization of tardiness and makespan. The simulation model enables managers to find schedule of jobs on machines given a defined combination of decision parameters which provide the smallest completion time of jobs. We then utilize DOE for determining the decision parameters to estimate the effect of both qualitative and qualitative factors through metamodeling. A goal programming model is used to find the optimum values of decision variables subject to a set of technical and managerial constraints. The proposed algorithm concentrates on two main managerial objectives simultaneously whereas previous studies are able to consider a single criterion. Finally, distinctive features of the proposed approach are compared with previous studies and models. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with the use of online simulation on Holonic manufacturing systems. Concepts needed for the use of online simulation in a classical hierarchical system were already defined, the observer being the central one. The behavior''s differences between both classes of systems are studied to determine the best way to adapt these concepts to this new environment. In the product resource order staff approach (PROSA) reference architecture, staff holons were chosen to welcome the simulation models and the observer. An application on an industrial sized Holonic manufacturing system is described to demonstrate the validity of the approach. [Copyright &y& Elsevier]

To meet the dynamically changing market requirements, production enterprises are collaborating in the form of production chains to share life cycle engineering data/knowledge as well as to improve production efficiency and product quality. This paper proposes a model-based control mechanism and intelligent control layer, which is used to control the operation of chained production enterprises. The control mechanism is achieved by defining control levels as mapped to production chain topology using the concept of operation isolation area. Production constraints and control rules are defined as attached to structure elements. The proposed control layer is used to decide the suitable operation of the selected production chain, in view of process constraints and operating conditions. A case study of a generic production chain with recycling is used to show the proposed control mechanism. [ABSTRACT FROM AUTHOR]