INTELLIGENT CONTROL IN THE SIMULATION OF MANUFACTURING SYSTEM

International audienceA particular characteristic of a manufacturing system concerns the complexity and the presence of uncertainties along with the difficulties in building analytical models that capture the system in all its important aspects. Hence, simulation remains one of the most widely used tools to fill this need. The objective of this article is related to the potential improvement of computer simulation as applied to the control of manufacturing system by introducing a two-level fuzzy-logic based control structure. On the lower level of the hierarchy, there is an adaptive fuzzy controller for each specific production module which can automatically sythesize itself to regulate the flow of the material into a system, and in the upper level, a supervisor has the task of coordinating and tuning the local controllers by using the performance measurements characterizing the overall system's current behavior to achieve better performance and restrict the system in admissible domain

Hierarchical Control of Production Flow based on Capacity Allocation for Real-Time Scheduling of Manufacturing System

8International audienceThis paper considers the modelling and simulation of a hierarchical production-flow control system. It uses a continuous control approach for machine capacity allocation at the design level and real time scheduling at the shop-floor level. Particularly, at the design level, the control of machine throughput has been addressed by a set of distributed and supervised fuzzy controllers. The objective is to adjust the machine's production rates in such a way that satisfies the demand while maintaining the overall performances within acceptable limits. At the shop-floor level, the problem of scheduling of jobs is considered. In this case, the priority of jobs (actual dispatching times) is determined from the continuous production rates through a discretization procedure. A case study demonstrates the efficiency of the proposed methodology through a simulation case study

Pilotage Flou Distribué et Supervisé pour la Régulation des Flux de Production

National audienceDans cet article, une structure de pilotage distribuée et supervisée pour la régulation des flux de production est proposée. Partant de la décomposition d'un système de production en un ensemble de modules élémentaires, une structure de pilotage distribuée de type multi-contrôleurs est déployée au niveau " local ". A ce niveau, chaque module de production est piloté par un contrôleur flou afin de satisfaire la demande et d'éviter les phénomènes de rupture et de blocage. Afin d'améliorer les performances de cette structure, un niveau de supervision est intégré. Ce dernier a pour rôle de coordonner les actions locales et de réaliser des compromis entre les objectifs globaux. La conception du superviseur s'appuie sur l'exploitation des opérateurs d'agrégation et la quantification des objectifs par des intervalles flous. Un exemple de simulation est considéré pour illustrer les performances de la méthodologie proposée

Application of a continuous supervisory fuzzy control on a discrete scheduling of manufacturing systems.

10 pagesInternational audienceThis paper considers the modelling and simulation of a hierarchical production-flow control system. Particularly, the system capacity allocation has been addressed by a set of distributed and supervised fuzzy controllers. The objective is to adjust the machine's production rates in such a way that satisfies the demand while maintaining the overall performances within acceptable limits. Given the adjusted production rates, the problem of scheduling of jobs is considered at the shop-floor level. In this case, the actual dispatching times are determined from the continuous production rates through a sampling procedure. To deal with conflicts between jobs at a shared machine, a decision for the actual part to be processed is taken using some criteria which represent a measure of the job's priority. A case study demonstrates the efficiency of the proposed control approach

Supervisory Control based Fuzzy Interval Arithmetic Applied for Discrete Scheduling of Manufacturing Systems

6 pagesInternational audienceThis paper considers the modelling and designing of a production-flow scheduler based on fuzzy interval system. Particularly, the supervisory control is built according to the satisfaction degree of conflicting objectives which are quantified by fuzzy intervals. The control system aims at adjusting the machine's production rates in such a way that satisfies the demand while maintaining the overall performances within acceptable limits. At the shop-floor level, the actual dispatching times are determined from the continuous production rates through a sampling procedure. A decision for the actual part to be processed is taken using some criterions which represent a measure of the job's priority. A case study demonstrates the efficiency of the proposed control approach

Intelligent distributed and supervised flow control methodology for production systems.

13International audienceThis paper deals with the development of an intelligent distributed and supervised control approach for high-volume production systems in which the flow of parts can be approximated by a continuous (fluid) model. The proposed approach is based on the decomposition of the production system into elementary modules in order to reduce the control design computational complexity. In this context, a two levels control structure is proposed. At the local level, a surplus-based principle is adopted to regulate the production flow for each module according to the distributed structure. The proposed control methodology decides how to adjust the production rate in order to avoid system overloading and eliminate machine starvation or blocking. In this context, the local control law is synthesized by using the Takagi-Sugeno fuzzy systems. At the high level, a supervisory controller is designed to improve the overall system performances. A supervisor provides an additive component for each local controller when the overall system performances deviate from their acceptable domains (degraded mode). This is done by combining both local and global information into a unified formalism by using aggregation operators and according to fuzzy interval representation of the desired objectives. Finally, the feasibility of the proposed methodology is validated with simulation examples

Approche de Pilotage par Allocation de Capacité Utilisant un Modèle de Simulation à Flux Continu

International audienceL'intégration d'une méthodologie de pilotage dans la simulation a motivé plusieurs travaux de recherche afin de rendre cette dernière " active " (Habchi et Berchet, 2003). Dans cet article, nous proposons une approche de simulation contrôlée à flux continu où le flux de production dans le système est régulé. En effet, en s'appuyant sur une modélisation fluide du système manufacturier, une architecture de pilotage hiérarchique à deux niveaux (niveau bas : commande locale et niveau haut : supervision) est développée. Sachant que le système de production est vue comme une collections de sous-systèmes élémentaires (machines, stocks), la commande dite " bas niveau ", fondée sur la théorie du contrôle flou, vise à réguler le flux de production au niveau de chaque ressource élémentaire. Dans ce contexte, afin de coordonner les actions de contrôle locales et améliorer les performances globales, une stratégie de supervision est proposée. Les principes de modélisation et de pilotage pour la simulation sont présentés et illustrés par une application

Développement d'une méthodologie de pilotage intelligent par régulation de flux adaptée aux systèmes de production

Les travaux présentés dans cette thèse portent sur la conception d'une méthodologie de pilotage intelligent pour les systèmes de production à forte densité de flux. Les caractéristiques de ces systèmes nous permettent d'appréhender la représentation des flux y circulant par un modèle continu. Ainsi, a partir du modèle obtenu, la méthodologie de pilotage proposée vise à améliorer les performances du système de production en présence de diverses perturbations. Dans ce contexte, en considérant une décomposition du système en modules de production élémentaires, nous avons proposé une structure de pilotage distribuée et supervisée a deux niveaux : un niveau de commande locale ayant pour objectif de réguler les flux traversant chaque module de production sur la base des informations locales (surplus, niveaux des stocks), un niveau de supervision dédié à la coordination des contrôleurs locaux afin de suivre les objectifs globaux. Au niveau de la commande locale, nous avons opté pour une structure distribuée et adopté une approche de pilotage fondée sur Ie principe du surplus. Ce principe consiste à allouer de la capacité en ajustant le taux de production de chaque module afin de satisfaire les demandes tout en évitant les ruptures et les blocages. Compte tenu des difficultés liées aux formalismes analytiques et aux incertitudes du système et son environnement, nous avons utilisé des techniques à base d'expertise en exploitant les systèmes flous de Takagi-Sugeno. Au niveau de la commande globale, la supervision est introduite afin d'améliorer la réactivité de la commande locale ainsi que les performances du système en intégrant les objectifs globaux via un mécanisme capable de réaliser des compromis entre des objectifs antagonistes. Lorsqu'une dérive est constatée, l'action de supervision est déployée sous forme d'une composante additive. La fonction de supervision est formalisée en exploitant des mécanismes d'agrégation à base de règles floues et d'opérateurs d'agrégation. Les superviseurs développés se distinguent par : la représentation des objectifs par des intervalles conventionnels et flous, Ie formalisme d'agrégation utilisé et les informations agrégées. Enfin, la méthodologie proposée a été validée, par simulation continue, sur des systèmes de production complexes et à gros volume.This thesis deals with development of an intelligent flow control approach applied to the field of high-volume production systems. In this context, the flow of parts is approximated by a continuous-flow (fluid) model. Thus, based on the obtained model, the proposed methodology aims at improving the performance of the overall system in presence of disturbances. In this context, based on the decomposition of a production system into basic modules, a two-level control architecture is proposed : a local control level for regulating the material flows at each basic production module on the basis of local information (surplus and buffer levels). A supervisory control level for coordinating the lower level distributed controllers and tracking the global objectives. Firstly, at the local control level, the surplus-based approach is adopted to regulate the flow into each production module. The control policy allocates the needed capacity by adjusting the processing rates in order to satisfy the demand and eliminate machine starvation or blocking. In this case, the local control structure is distributed. Due to the limitation of the existing analytical surplus-based approaches and the presence of uncertainties, the local controller is designed on the basis of expert knowledge according to the Takagi-Sugeno fuzzy formalisms. Next, the supervision level is introduced in order to enhance the reactivity of the local control and improve the overall production-system performances by integrating the global objectives through a decisional mechanism able to deal with conflicting situations. The supervisory control action is deployed as an additive component when a degraded operating mode is detected. In this context, the function of the supervisor is formalized by using aggregation mechanisms based on the fuzzy rules and the aggregation operators.The developed supervisors differ by : the interval representation of the objectives (conventional and fuzzy), the aggregation mechanisms and the aggregated information. Lastly, simulation results through a continuous-flow simulator on some complex production systems of high-volume are presented to illustrate the feasibility of the proposed methodology.CHAMBERY -BU Bourget (730512101) / SudocSudocFranceF

High Level Petri Nets Based Approach for Analysing Conceptual Objects for Production Systems Simulation

International audienceIn the field of design and analysis of manufacturing systems, models are sometimes built with the help of analytical methods. However, the verification of these models is often addressed by simulation. To check the performance of a manufacturing system, formal methods of design are needed. In this work, the selected modelling and verification tool is a high level Petri net. Based on properties of the generic concept called the Production Processing System (PPS) and developed for modelling and simulation of production resources, this article deals with analysing the PPS by high-level Petri nets (HLPN) formalisms

Multi-objective supervisory flow control based on fuzzy interval arithmetic: Application for scheduling of manufacturing systems.

13 pagesInternational audienceComplex production systems can produce more than one part type under multiple and possibly conflicting objectives. This paper considers the design of the multiple objective real-time scheduling problem of a multiple-part-type production system. Based on fuzzy control theory and fuzzy arithmetic intervals, distributed and supervised continuous-flow control architecture has been proposed. The objective is to balance the production process by adjusting the continuous production rates of the machines on the basis of the average behaviour. The supervisory control aims to maintain the overall performance within acceptable limits. In the proposed approach, the problem of a real-time scheduling of jobs is considered at the shop-floor level. In this case, the actual dispatching times are determined from the continuous production rates through a discretisation procedure. To deal with conflicts between jobs at a shared machine, a decision for the actual part to be processed is taken using some criterions which represent a measure of the job's priority. A case study demonstrates the efficiency of the proposed control approach