Damien Trentesaux

Distributed control of production systems

This editorial introduces the special issue of the Elsevier journal, Engineering Application of Artificial Intelligence, on Distributed control of production systems. The current technology in communication and embedded systems allows products and production resources to play a more active role in the production process. This new active capacity will generate major changes in organizations and information systems (e.g., Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES)). New approaches are now required for modelling, testing and assessing the features made possible by the decisional and informational capabilities of these new active entities. One among the many possibilities is to use agents and holons, since agent and holon-based approaches assume interaction between intelligent entities to facilitate the emergence of a global behavior. This special issue thus focuses on the possible applications of distributed approaches for the design, evaluation and implementation of new control architectures for production systems. Both fundamental and applied research papers are presented.

Bio-inspired multi-agent systems for reconfigurable manufacturing systems

The current markets demand for customization and responsiveness is a major challenge for producing intelligent, adaptive manufacturing systems. The Multi-Agent System (MAS) paradigm offers an alternative way to design this kind of system based on decentralized control using distributed, autonomous agents, thus replacing the traditional centralized control approach. The MAS solutions provide modularity, flexibility and robustness, thus addressing the responsiveness property, but usually do not consider true adaptation and re-configuration. Understanding how, in nature, complex things are performed in a simple and effective way allows us to mimic natures insights and develop powerful adaptive systems that able to evolve, thus dealing with the current challenges imposed on manufacturing systems. The paper provides an overview of some of the principles found in nature and biology and analyses the effectiveness of bio-inspired methods, which are used to enhance multi-agent systems to solve complex engineering problems, especially in the manufacturing field. An industrial automation case study is used to illustrate a bio-inspired method based on potential fields to dynamically route pallets.

Dynamic self-organization in holonic multi-agent manufacturing systems

Holonic multi-agent system evolution of the well-known ADACOR architecture.Behavioural and structural self-organization proposed.Nervousness control mechanism.Results show an improvement of the previous version of ADACOR. 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-dimensional 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.

A stigmergic approach for dynamic routing of active products in FMS

This paper illustrates the capacity of a stigmergic routing control model to automatically find efficient routing paths for active products in flexible manufacturing systems (FMSs) undergoing perturbations. The proposed model is based upon a functional architecture with two levels: a virtual level in which virtual active products (VAPs) evolve stochastically in accelerated time, and a physical level in which physical active products (PAPs) evolve deterministically in real-time. The physical active products follow the best paths that have been detected on the virtual level, with a virtual level exploration being triggered when a perturbation is diagnosed in the transportation system. The data used for the simulation on the virtual level is then updated to reflect the real state of the transportation system. The models adaptive capabilities are illustrated with several simulation scenarios using NetLogo software, and an on-going real implementation is presented.

Dynamic scheduling of maintenance tasks in the petroleum industry: A reinforcement approach

Petroleum industry production systems are highly automatized. Maintenance of such systems is vital, not only to maintain production efficiency but also to insure minimal safety levels. Maintenance task scheduling is difficult since some tasks are already identified because they must be done repeatedly, and other tasks need to be identified dynamically. In this paper, we present a multi-agent approach for the dynamic maintenance task scheduling for a petroleum industry production system. Agents simultaneously insure effective maintenance scheduling and the continuous improvement of the solution quality by means of reinforcement learning, using the SARSA algorithm. Reinforcement learning allows the agents to adapt, learning the best behaviors for their various roles without reducing the performance or reactivity. To demonstrate the innovation of our approach, we include a computer simulation of our model and the results of experimentation applying our model to an Algerian petroleum refinery.

The lifecycle of active and intelligent products: The augmentation concept

This paper aims to demonstrate the consistency of extending the active or intelligent product concept to the whole product lifecycle. The first two sections describe the state of the art in the field of closed-loop PLM and the repercussions of introducing active products in the different phases of the product lifecycle: design, manufacturing, distribution, use and recycling. A functional generic model is then introduced. This model is based upon the ‘augmentation’ concept, which is available throughout the whole product lifecycle. To illustrate our proposal, we provide examples in the design and distribution phases. To validate our proposal, we focus on the manufacturing phase, describing a real implementation on a flexible assembly cell at Valenciennes AIP Primeca pole. Our ongoing research works to apply the ‘augmentation’ concept to the operating phase of a complex system in order to improve performance, especially in terms of availability.

ORCA-FMS: a dynamic architecture for the optimized and reactive control of flexible manufacturing scheduling

Abstract Reactive and effective hybrid manufacturing control architectures, combining hierarchy and heterarchy adapted to the current constraints of the industrial market and its environment were created. In this article, a new generic hybrid control architecture called ORCA (dynamic Architecture for an Optimized and Reactive Control) is first proposed. This hybrid architecture is able to dynamically and partially switch between a hierarchical predictive architecture and a heterarchical reactive architecture, if an event forbidding the planned behavior to be followed occurs. In this article, this architecture was applied to a Flexible Manufacturing System (FMS) problem and denoted ORCA-FMS. ORCA-FMS was tested on an existing manufacturing cell with simulations and real experiments to prove the applicability and the effectiveness of this kind of hybrid architecture in an industrial environment.

Self-organization in distributed manufacturing control: state-of-the-art and future trends

Facing new and varied customers needs, strategies of production have radically changed during these list three decades leading to a need for agile and, as a consequence, self-organized manufacturing control systems. One possible way to integrate self-organization capability is to move from rigid centralized architectures towards distributed architectures. In this paper, we present a state-of-the-art of self-organization models in distributed manufacturing control, according to the bionic, holonic, multi-agent and heterarchical design approaches. We show the potential capabilities offered by these approaches to integrate self-organization mechanisms. Meanwhile, we also point out the insufficiencies of existing contributions, which lead us to highlight some future trends in the design of effective self-organized manufacturing control systems.

Service Orientation in Holonic and Multi-Agent Manufacturing and Robotics

This volume gathers the peer reviewed papers which were presented at the third edition of the International Workshop Service Orientation in Holonic and Multi-agent Manufacturing and Robotics SOHOMA13 organized on June 20-22, 2013 by the Centre of Research in Computer Integrated Manufacturing and Robotics CIMR Bucharest, and hosted by the University of Valenciennes, France. The book is structured in five parts, each one covering a specific research domain which represents a trend for modern manufacturing control: Distributed Intelligence for Sustainable Manufacturing, Holonic and Multi-Agent Technologies for Manufacturing Planning and Control; Service Orientation in Manufacturing Management and Control, Intelligent Products and Product-driven Automation and Robotics for Manufacturing and Services. These five evolution lines have in common concepts related to service orientation in a distributed planning and control agent-based industrial environment; today it is generally recognized that the Service Oriented Enterprise Architecture paradigm has been looked upon as a suitable and effective approach for industrial automation and management of manufacturing enterprises.

Reactive and energy-aware scheduling of flexible manufacturing systems using potential fields

This paper presents a reactive scheduling approach for flexible manufacturing systems, which integrates the overall energy consumption of the production. This work is justified by the growing needs of manufacturers for energy-aware control, due to new important environmental criteria, which holds true in the context of high reactivity. It makes production hard to predict. The proposed reactive scheduling model is based on potential fields. In this model, resources that sense the intentions from products are able to switch to standby mode to avoid useless energy consumption and emit fields to attract products. Simulations are provided, featuring three indicators: makespan, overall energy consumption and the number of resource switches. Real experiments were carried out to illustrate the feasibility of the approach on a real system and validate the simulation results.