کنترل مبتنی بر عامل FMS
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|16111||2009||11 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Robotics and Computer-Integrated Manufacturing, Volume 25, Issue 2, April 2009, Pages 470–480
Future manufacturing systems will be integrated into the networks of distributed resources, and at the same time, such systems will be capable of processing both knowledge and material. It will probably be required that manufacturing systems be agile, flexible, and fault-tolerant. Petri nets (PN) and object-oriented design (OOD) are used together in order to develop the integrated agent-based FMS control system. The flexible manufacturing system (FMS) consists of machines, workstations, and automated material handling system, distributed buffer storage sites and computer-based supervisory control, all which can be modeled as an agent in OOD with PN. This paper introduces the design of an agent-based FMS control system through PNs and evaluates the performance using timed placed Petri nets (TPPN). In order to do so, the agent control design, FMS structure has been evaluated in detail and the agent definitions have been submitted. The system includes the sharing and distribution of tasks among agents and the mentioned structure has been simulated by TPPN. The simulation procedure has been realized through Petri Net 2.0—MATLAB Demo Program [Mahulea CF, Motcovschi MH, Pastravanu O. Department of Automatic Control Industrial Informatics, Technical University “Gh. Asachi” of Iasi, Blvd., Mangeron 53A, 6600 Iasi, Romania, 〈http://www.ac.tuiasi.ro/pntool,email@example.com〉, 2004.]. Each case is modeled, and then the agent's machine processing time is considered in this program. As for the evaluation of the study, the system performance is assessed through the waiting time of the parts in queue and the task distributions.
Agent-based flexible manufacturing system (FMS) control system is a mechanism in which status analysis and control of the system is performed by the agents. This control is performed by the Supervisor Agent. This is a mechanism, which continually monitors the system status and conditions and makes the production related decisions. It is a mechanism where knowledge about the system status, and about which part will be processed in and how much time by use of which robot or AGV and in which frame is received and evaluated. The Supervisor Agent also makes decisions about which process plan is going to be implemented with which operation sequence, taking into consideration the system status. Supervisor Agent is a mechanism which endeavors to answer the questions such as what and how for the production of a part. It has been aimed at reaching the more rapid and flexible control system that has a complex structure with factor-based FMS control model. For this procedure, firstly, the data and rule base are determined by taking into consideration in detail. The unified modeling language (UML) structure was used in modeling the factors. The UML structure was chosen because this structure shows the message stages particularly and clearly. The Petri net (PN) is preferred in the working style of the system as metaphor simulation. This paper represents the design of an agent-based FMS (ABFMS) control system through PNs and evaluates the performance with timed placed PNs (TPPN). In this study, PN model is designed by taking into account the event-state diagram and database; this program has been run, and its performance figures have been submitted as a conclusion.
نتیجه گیری انگلیسی
This paper proposed various decision-making rules for the ABFMS control. These results could be used to develop and improve decision-making and self-learning systems through the integrating of agent systems. The scheduling activities that have been obtained according to the sequencing of the parts have been evaluated in terms of time durations. The agent system can be reviewed for the following factors. These factors can be grouped in two categories: • Capacity constraints o Number of part and types o Tool magazine capacity o Capacity of material handling system o Type and size of buffers o Number of pallets o Number and design of the fixtures o Allocation of pallets and fixtures to part types • Operational constraints o Input sequence and number of parts into the system o Scheduling parts to machines based upon alternative routings o Sequencing parts on machine o Scheduling material-handling devices such as AGV