دانلود مقاله ISI انگلیسی شماره 3511
عنوان فارسی مقاله

مدلسازی و شبیه سازی چارچوب کنترل بر یک سیستم تولید انعطاف پذیر

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
3511 2000 9 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
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عنوان انگلیسی
Modeling and simulation of the control framework on a flexible manufacturing system
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : International Journal of Production Economics, Volume 64, Issues 1–3, 1 March 2000, Pages 285–293

کلمات کلیدی
سیستم تولید انعطاف پذیر - مدل شبیه سازی
پیش نمایش مقاله
پیش نمایش مقاله مدلسازی و شبیه سازی چارچوب کنترل بر یک سیستم تولید انعطاف پذیر

چکیده انگلیسی

A flexible manufacturing system (FMS) is designed to combine high productivity and production flexibility. But the design of a FMS requires high investment. Furthermore, this preliminary phase is strategic and the decisions at this stage have to be made very carefully in order to ensure that the manufacturing system will successfully satisfy the demands of an ever-changing market. Discrete-event simulation has been widely used to design production systems such as FMSs. More particularly, it has been used to design and size the hardware part of a FMS. On the other hand, simulation is more and more used to design and evaluate decision strategies. In this paper, we propose to integrate in a single simulation model a physical model which corresponds to the hardware elements of the FMS with their physical characteristics and interactions, and a logic model which corresponds to the modeling of the computer control system and its interaction with the material part (i.e., the control framework and the network). For this, we present a methodology which allows the integration in a single simulation model of logical layer representing the control framework and a physical layer representing the FMS elements (i.e., machines, vehicles, transportation network…) within a discrete-event simulation language. On a FMS, for example described in this paper, the results obtained show that with a high level shop congestion, the control layer does not increase the job flowtime.

مقدمه انگلیسی

A flexible manufacturing system (FMS) is an integrated system composed of automated workstations such as computer numerically controlled (CNC) machines with tool changing capability, a hardware handling and storage system and a computer control system which controls the operations of the whole system [1]. It is designed to combine high productivity and production flexibility. But the design of a FMS requires high investment. Furthermore, this preliminary phase is strategic and the decisions at this stage have to be made very carefully in order to ensure that the manufacturing system will successfully satisfy the demands of an ever-changing market. In a FMS, the flexibility depends, from one point of view on the technology used (e.g., machines with tool changing capability) and from another point of view, which is not the least important, on the computer control system. Moreover, the computer control system can hardly be tested without the FMS hardware part. Thus, the design of the computer control system has to be made so that the control will be flexible and easily adaptable to the configuration changes of the FMS. In fact, the computer control system is a strategic function for the optimal use of a FMS, as well as the hardware part of the FMS has to be carefully designed. Discrete-event simulation has been widely used to design production systems such as FMSs. More particularly, it has been used to design and size the hardware part of a FMS (e.g., capacity of the buffer storage, characteristics of the hardware handling, characteristics and numbers of workstations with regard to the expected production, robots,…) in order to optimize the parts flow or to maximize the utilization of the workstations for example. Simulation tools such as ARENA, Witness or Automod allow to model quite quickly the physical flow of parts in the FMS. On the other hand, simulation is more and more used to design and evaluate decision strategies (e.g., sequencing of parts, machine or AGV selection). But, decision strategies in FMSs are integrated into the computer control system and depend widely on the framework of this control system and also on the way that the control system interacts with the material elements. In this paper, we propose to integrate in a single simulation model a physical model which corresponds to the hardware elements of the FMS with their physical characteristics and interactions, and a logic model which corresponds to the modeling of the computer control system and its interaction with the material part (i.e., the control framework and the network). The first part of this paper is devoted to the presentation of different control frameworks used in FMSs. The second part will present the methodology used to integrate a logical model representing the control framework and a physical model representing the FMS elements (i.e., machines, vehicles, transportation network…) with discrete-event simulation tools. Then, in the third part we describe, as an example of FMS, an application of this methodology. And finally in the fourth part we present and analyze the results obtained from this example which integrates the control framework and the physical part.

نتیجه گیری انگلیسی

We have proposed a methodology which allows the integration in a single-simulation model, a physical model which corresponds to the material elements of the FMS with their physical characteristics and interactions, and a logical model which corresponds to the modeling of the computer control system and its interaction with the hardware part. This integration allows us to evaluate the incidence of the control framework on the performance of the production system. It also allows us to test different control frameworks on an existing manufacturing system and to select the one that is the more adapted with regard to the physical constraints and the production objectives. One of our perspectives is to model the allocation resources throughout the local supervisors and the logical entities. Other perspectives are: • to integrate the dynamic scheduling rules and to test the way these dynamic strategies can be implemented in a control framework, • to use this integrated model simulation to establish procedures in case of a degraded utilization of the elements of the shop.

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