3,943 research outputs found

    Survey of dynamic scheduling in manufacturing systems

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    A nervousness regulator framework for dynamic hybrid control architectures

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    Dynamic hybrid control architectures are a powerful paradigm that addresses the challenges of achieving both performance optimality and operations reactivity in discrete systems. This approach presents a dynamic mechanism that changes the control solution subject to continuous environment changes. However, these changes might cause nervousness behaviour and the system might fail to reach a stabilized-state. This paper proposes a framework of a nervousness regulator that handles the nervousness behaviour based on the defined nervousness-state. An example of this regulator mechanism is applied to an emulation of a flexible manufacturing system located at the University of Valenciennes. The results show the need for a nervousness mechanism in dynamic hybrid control architectures and explore the idea of setting the regulator mechanism according to the nervousness behaviour state.info:eu-repo/semantics/publishedVersio

    Collective intelligence in self-organized industrial cyber-physical systems

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    Cyber-physical systems (CPS) play an important role in the implementation of new Industry 4.0 solutions, acting as the backbone infrastructure to host distributed intelligence capabilities and promote the collective intelligence that emerges from the interactions among individuals. This collective intelligence concept provides an alternative way to design complex systems with several benefits, such as modularity, flexibility, robustness, and reconfigurability to condition changes, but it also presents several challenges to be managed (e.g., non-linearity, self-organization, and myopia). With this in mind, this paper discusses the factors that characterize collective intelligence, particularly that associated with industrial CPS, analyzing the enabling concepts, technologies, and application sectors, and providing an illustrative example of its application in an automotive assembly line. The main contribution of the paper focuses on a comprehensive review and analysis of the main aspects, challenges, and research opportunities to be considered for implementing collective intelligence in industrial CPS. The identified challenges are clustered according to five different categories, namely decentralization, emergency, intelligent machines and products, infrastructures and methods, and human integration and ethics. Although the research indicates some potential benefits of using collective intelligence to achieve the desired levels of autonomy and dynamic adaptation of industrial CPS, such approaches are still in the early stages, with perspectives to increase in the coming years. Based on that, they need to be further developed considering some main aspects, for example, related to balancing the distribution of intelligence by the vertical and horizontal dimensions and controlling the nervousness in self-organized systems.info:eu-repo/semantics/publishedVersio

    Dynamic self-organization in holonic multi-agent manufacturing systems: The ADACOR evolution

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    Nowadays, systems are becoming increasingly complex, mainly due to an exponential increase in the number of entities and their interconnections. Examples of these complex systems can be found in manufacturing, smart-grids, traffic control, logistics, economics and biology, among others. Due to this complexity, particularly in manufacturing, a lack of responsiveness in coping with demand for higher quality products, the drastic reduction in product lifecycles and the increasing need for product customization are being observed. Traditional solutions, based on central monolithic control structures, are becoming obsolete as they are not suitable for reacting and adapting to these perturbations. The decentralization of the complexity problem through simple, intelligent and autonomous entities, such as those found in multi-agent systems, is seen as a suitable methodology for tackling this challenge in industrial scenarios. Additionally, the use of biologically inspired self-organization concepts has proved to be suitable for being embedded in these approaches enabling better performances to be achieved. According to these principals, several approaches have been proposed but none can be truly embedded and extract all the potential of self-organization mechanisms. This paper proposes an evolution to the ADACOR holonic control architecture inspired by biological and evolutionary theories. In particular, a two-dimension al self-organization mechanism was designed taking the behavioural and structural vectors into consideration, thus allowing truly evolutionary and reconfigurable systems to be achieved that can cope with emergent requirements. The approach proposed is validated with two simulation use cases.info:eu-repo/semantics/publishedVersio

    An agent-based approach for the dynamic and decentralized service reconfiguration in collaborative production scenarios

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    Future industrial systems endorse the implementation of innovative paradigms addressing the continuous flexibility, reconfiguration, and evolution to face the volatility of dynamic markets demanding complex and customized products. Smart manufacturing relies on the capability to adapt and evolve to face changes, particularly by identifying, on-the-fly, opportunities to reconfigure its behavior and functionalities and offer new and more adapted services. This paper introduces an agent-based approach for service reconfiguration that allows the identification of the opportunities for reconfiguration in a pro-active and dynamic manner, and the implementation on-the-fly of the best strategies for the service reconfiguration that will lead to a better production efficiency. The developed prototype for a flexible manufacturing system case study allowed to verify the feasibility of greedy local service reconfiguration for competitive and collaborative industrial automation situations.info:eu-repo/semantics/publishedVersio

    Dynamic Switching Mechanism to Support Self-organization in ADACOR Holonic Control System

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    Evolvable control systems face the demands for modularity, decentralization, reconfigurabil-ity and responsiveness pointed out by the Industrie 4.0 initiative. In these systems, the self-organization model assumes a critical issue to ensure the correct evolution of the system structure into different operating configurations. ADACOR holonic manufacturing control architecture introduces an adaptive production control mechanism that balances between two states, combining the optimization provided by hierarchical structures with agility and responsiveness to condition changes offered by decentralized structures. This paper describes the switching mechanism that supports this dynamic balance and particularly the local and global driving forces for the self-organization model. The proposed model was experimentally tested in a small scale production system.info:eu-repo/semantics/publishedVersio

    Design choices for agent-based control of AGVs in the dough making process

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    In this paper we consider a multi-agent system (MAS) for the logistics control of Automatic Guided Vehicles (AGVs) that are used in the dough making process at an industrial bakery. Here, logistics control refers to constructing robust schedules for all transportation jobs. The paper discusses how alternative MAS designs can be developed and compared using cost, frequency of messages between agents, and computation time for evaluating control rules as performance indicators. Qualitative design guidelines turn out to be insufficient to select the best agent architecture. Therefore, we also use simulation to support decision making, where we use real-life data from the bakery to evaluate several alternative designs. We find that architectures in which line agents initiate allocation of transportation jobs, and AGV agents schedule multiple jobs in advance, perform best. We conclude by discussing the benefits of our MAS systems design approach for real-life applications

    Specification of the PERFoRM architecture for the seamless production system reconfiguration

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    The world is assisting to the fourth industrial revolution, with several domains of science and technology being strongly developed and, specially, being integrated with each other, allowing to build evolvable complex systems. Data digitization, big-data analysis, distributed control, Industrial Internet of Things, Cyber-Physical Systems and self-organization, amongst others, are playing an important role in this journey. This paper considers the best practices from previous successful European projects addressing distributed control systems to develop an innovative architecture that can be industrially deployed. For this purpose, a particular design process has to be addressed in order to consider the requirements and functionalities from various use cases. To investigate the known practices, four use cases are enlighted in this paper, which cover a wide spectrum of the European industrial force, as well as industrial standards to support a smooth migration from traditional systems to the emergent distributed systems.info:eu-repo/semantics/publishedVersio

    Proposition d’une architecture holonique auto-organisée et évolutive pour le pilotage des systèmes de production

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    The manufacturing world is being deeply challenged with a set of ever demanding constraints where from one side, the costumers are requiring products to be more customizable, with higher quality at lower prices, and on other side, companies have to deal on a daily basis with internal disturbances that range from machine breakdown to worker absence and from demand fluctuation to frequent production changes. This dissertation proposes a manufacturing control architecture, following the holonic principles developed in the ADAptive holonic COntrol aRchitecture (ADACOR) and extending it taking inspiration in evolutionary theories and making use of self- organization mechanisms. The use of evolutionary theories enrich the proposed control architecture by allowing evolution in two distinct ways, responding accordingly to the type and degree of the disturbance that appears. The first component, named behavioural self- organization, allows each system’s entity to dynamically adapt its internal behaviour, addressing small disturbances. The second component, named structural self-organization, addresses bigger disturbances by allowing the system entities to re-arrange their rela- tionships, and consequently changing the system in a structural manner. The proposed self-organized holonic manufacturing control architecture was validated at a AIP-PRIMECA flexible manufacturing cell. The achieved experimental results have also shown an improvement of the key performance indicators over the hierarchical and heterarchical control architecture.Le monde des entreprises est profondément soumis à un ensemble de contraintes toujours plus exigeantes provenant d’une part des clients, exigeant des produits plus personnalisables, de qualité supérieure et à faible coût, et d’autre part des aléas internes auxentreprises, comprenant les pannes machines, les défaillances humaines, la fluctuation de la demande, les fréquentes variations de production. Cette thèse propose une architecture de contrôle de systèmes de production, basée sur les principes holoniques développées dans l’architecture ADACOR (ADAptive holonic COntrol aRchitecture), et l’étendant en s’inspirant des théories de l’évolution et en utilisant des mécanismes d’auto-organisation. L’utilisation des théories de l’évolution enrichit l’architecture de contrôle en permettant l’évolution de deux manières distinctes, en réponse au type et au degré de la perturbation apparue. Le premier mode d’adaptation, appelé auto-organisation comportementale, permet à chaque entité qui compose le système d’adapter dynamiquement leur comportement interne, gérant de cette façon de petites perturbations. Le second mode, nommé auto-organisation structurelle, traite de plus grandes perturbations, en permettant aux entités du système de ré-organiser leurs relations, et par conséquent modifier structurellement le système. L’architecture holonique auto-organisée de contrôle de systèmes de production proposée dans cette thèse a été validée sur une cellule de production flexible AIP-PRIMECA. Les résultats ont montré une amélioration des indicateurs clés de performance par rapport aux architectures de contrôle hiérarchiques et hétérarchiques
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