Intelligent Simulation Modeling of a Flexible Manufacturing System with Automated Guided Vehicles

Although simulation is a very flexible and cost effective problem solving technique, it has been traditionally limited to building models which are merely descriptive of the system under study. Relatively new approaches combine improvement heuristics and artificial intelligence with simulation to provide prescriptive power in simulation modeling. This study demonstrates the synergy obtained by bringing together the "learning automata theory" and simulation analysis. Intelligent objects are embedded in the simulation model of a Flexible Manufacturing System (FMS), in which Automated Guided Vehicles (AGVs) serve as the material handling system between four unique workcenters. The objective of the study is to find satisfactory AGV routing patterns along available paths to minimize the mean time spent by different kinds of parts in the system. System parameters such as different part routing and processing time requirements, arrivals distribution, number of palettes, available paths between workcenters, number and speed of AGVs can be defined by the user. The network of learning automata acts as the decision maker driving the simulation, and the FMS model acts as the training environment for the automata network; providing realistic, yet cost-effective and risk-free feedback. Object oriented design and implementation of the simulation model with a process oriented world view, graphical animation and visually interactive simulation (using GUI objects such as windows, menus, dialog boxes; mouse sensitive dynamic automaton trace charts and dynamic graphical statistical monitoring) are other issues dealt with in the study

Using statistical-model-checking-based simulation for evaluating the robustness of a production schedule

Published in Service Orientation in Holonic and Multi-Agent Manufacturing, Borangiu T., Trentesaux D., Thomas A., Cardin O. (eds). Studies in Computational Intelligence, vol 762, pp. 345-357, Springer, ChamInternational audienceIndustry 4.0 implies new scheduling problems linked to the optimal using of flexible resources and to mass customisation of products. In this context, first research results show that Discrete Event Systems models and tools are a relevant alternative to the classical approaches for modelling scheduling problems and for solving them. Moreover, the challenges of the industry 4.0 mean taking into account the uncertainties linked to the mass customisation (volume and mix of the demand) but also to the states of the resources (failures, operation durations,. . .). The goal of this paper is to show how it is possible to use the simulation based on statistical model checking for taking into account these uncertainties and for evaluating the robustness of a given schedule

Compositional verification of industrial control systems : methods and case studies

The main obstacles in the formal verification of industrial control systems are the lack of precise semantics for its programming languages, and the complexity problems which arise during the verification process. This work addresses both issues by defining an operational semantics for Sequential Function Charts, a widely-used language for Programmable Logic Controllers (PLCs), and by presenting modular and compositional methods to reduce the complexity arising from parallel structures in the system. These methods are illustrated by the verification of two PLC-controlled chemical batch plants

Computer-aided HAZOP of batch processes

The modern batch chemical processing plants have a tendency of increasing technological complexity and flexibility which make it difficult to control the occurrence of accidents. Social and legal pressures have increased the demands for verifying the safety of chemical plants during their design and operation. Complete identification and accurate assessment of the hazard potential in the early design stages is therefore very important so that preventative or protective measures can be integrated into future design without adversely affecting processing and control complexity or capital and operational costs. Hazard and Operability Study (HAZOP) is a method of systematically identifying every conceivable process deviation, its abnormal causes and adverse hazardous consequences in the chemical plants. [Continues.

Analyse pire cas exact du réseau AFDX

L'objectif principal de cette thèse est de proposer les méthodes permettant d'obtenir le délai de transmission de bout en bout pire cas exact d'un réseau AFDX. Actuellement, seules des bornes supérieures pessimistes peuvent être calculées en utilisant les approches de type Calcul Réseau ou par Trajectoires. Pour cet objectif, différentes approches et outils existent et ont été analysées dans le contexte de cette thèse. Cette analyse a mis en évidence le besoin de nouvelles approches. Dans un premier temps, la vérification de modèle a été explorée. Les automates temporisés et les outils de verification ayant fait leur preuve dans le domaine temps réel ont été utilisés. Ensuite, une technique de simulation exhaustive a été utilisée pour obtenir les délais de communication pire cas exacts. Pour ce faire, des méthodes de réduction de séquences ont été définies et un outil a été développé. Ces méthodes ont été appliquées à une configuration réelle du réseau AFDX, nous permettant ainsi de valider notre travail sur une configuration de taille industrielle du réseau AFDX telle que celle embarquée à bord des avions Airbus A380. The main objective of this thesis is to provide methodologies for finding exact worst case end to end communication delays of AFDX network. Presently, only pessimistic upper bounds of these delays can be calculated by using Network Calculus and Trajectory approach. To achieve this goal, different existing tools and approaches have been analyzed in the context of this thesis. Based on this analysis, it is deemed necessary to develop new approaches and algorithms. First, Model checking with existing well established real time model checking tools are explored, using timed automata. Then, exhaustive simulation technique is used with newly developed algorithms and their software implementation in order to find exact worst case communication delays of AFDX network. All this research work has been applied on real life implementation of AFDX network, allowing us to validate our research work on industrial scale configuration of AFDX network such as used on Airbus A380 aircraft. ABSTRACT : The main objective of this thesis is to provide methodologies for finding exact worst case end to end communication delays of AFDX network. Presently, only pessimistic upper bounds of these delays can be calculated by using Network Calculus and Trajectory approach. To achieve this goal, different existing tools and approaches have been analyzed in the context of this thesis. Based on this analysis, it is deemed necessary to develop new approaches and algorithms. First, Model checking with existing well established real time model checking tools are explored, using timed automata. Then, exhaustive simulation technique is used with newly developed algorithms and their software implementation in order to find exact worst case communication delays of AFDX network. All this research work has been applied on real life implementation of AFDX network, allowing us to validate our research work on industrial scale configuration of AFDX network such as used on Airbus A380 aircraft