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

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

Scheduling and Control Modelling of HVLV Systems Using Max-Plus Algebra

International audienceThe High-Variety, Low-Volume (HVLV) scheduling problem is one of the most arduous and combinatorial optimization problems. This paper presents an analytical scheduling model using a tropical algebra called (max,+) algebra. The aim is to find an allocation for each operation and to define the sequence of operations on each machine, so that the resulting schedule has a minimal completion time and the due dates of the different jobs (products) are met such that a Just-In-Time (JIT) production will be satisfied. To generate feasible schedules, decision variables are introduced in the model. The algebraic model developed in this work describes the discontinuous operations aspect of HVLV systems as Discrete Event Dynamic Systems (DEDS). It is non-linear in the sense of (max,+) algebra. The focus of this research concerns the development of a static scheduling approach for deterministic and not-decision-free HVLV manufacturing systems. Firstly, using (max, +) algebra, a direct generation of event-timing equations for deterministic and not-decision free HVLV systems is obtained. Then, a non-linear optimization problem in (max, +) algebra is solved. Finally, the validity of the proposed approach is illustrated by simulation examples

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

A propos de la modélisation et le pilotage des systèmes manufacturiers de type HVLV

International audienceIl s'agit dans ce papier de développer un modèle d'ordonnancement basé sur des méthodes analytiques permettant la simulation à évènements discrets des systèmes de production assez complexes de type HVLV (High Variety, Low Volume), dont la date de besoin client est un paramètre important, afin de converger plus rapidement vers des solutions quasi-optimales ou optimales

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

Fuzzy Piecewise Linear Regression

International audienceFuzzy regression using possibilistic concepts allows the identification of models from uncertain data sets. However, some limitations still exist about the possible evolution of the output spread with respect to inputs. We present here a modified form of fuzzy linear model whose output can have any kind of output spread tendency. The formulation of the linear program used to identify the model introduces a modified criterion that assesses the model fuzziness independently of the collected data. These concepts are used in a global identification process in charge of building a piecewise model able to represent every kind of output evolution

A Mathematical Model for HVLV Systems Scheduling and Optimization With Periodic Preventive Maintenance Using (max, +) Algebra

International audienceThe High-Variety, Low-Volume (HVLV) scheduling problem is one of the most arduous combinatorial optimization problems. This paper considers an interesting formulation of the HVLV scheduling problem using (max, +) algebra while periodic Preventive Maintenance (PM) is considered. Maintenance is time based since activities are periodically fixed: maintenance is required after a periodic time interval (all periods are equals on each machine). In this paper, the maintenance tasks of machines are controllable.The jobs and the maintenance operations are scheduled simultaneously. Also, the maintenance operations are scheduled between each other, so that a regular criterion is optimized. To generate feasible schedules, constrained decision variables are incorporated into the (max, +) model. The validity of the proposed approach is illustrated by simulation examples

Max-plus-linear model-based predictive control for constrained HVLV manufacturing systems

International audienceIn this paper, a max-plus-linear model predictive con- trol strategy is proposed for High-Variety, Low-Volume (HVLV) systems. Firstly, using the (max,+) algebra, a di- rect generation of event-timing equations for determinis- tic and decision-free HVLV manufacturing systems is ob- tained. Then, a linear optimization method is presented. It is based on canonical forms for Max-Min-Plus-Scaling (MMPS) functions with linear constraints on the inputs. The approach aims at solving several linear programming problems and its validity is illustrated by a simulation ex- ample. Finally, a discussion of results, conclusions and perspectives are given

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