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

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

Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

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

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

Enhancing service-oriented holonic multi-agent systems with self-organization

Multi-agents systems and holonic manufacturing systems are suitable approaches to design a new and alternative class of production control systems, based on the decentralization of control functions over distributed autonomous and cooperative entities. However, in spite of their enormous potential they lack some aspects related to interoperability, migration, optimisation in decentralised structures and truly self-adaptation. This paper discusses the advantages of combining these paradigms with complementary paradigms, such as service-oriented architectures, and enhancing them with biologically inspired algorithms and techniques, such as emergent behaviour and self-organization, to reach a truly robust, agile and adaptive control system. An example of applying a stigmergy-based algorithm to dynamically route pallets in a production system is also provided

A holonic approach to dynamic manufacturing scheduling

Indexado ISIManufacturing scheduling is a complex combinatorial problem, particularly in distributed and dynamic environments. This paper presents a holonic approach to manufacturing scheduling, which in opposite to traditional approaches, distributes the scheduling functions over several entities, combining their calculation power and local optimization. In this scheduling and control approach, the scheduling mechanism evolves dynamically to combine optimized scheduling, achieved by central entities, and distributed scheduling, improving its responsiveness and robustness

Industrial cyber physical systems supported by distributed advanced data analytics

The industry digitization is transforming its business models, organizational structures and operations, mainly promoted by the advances and the mass utilization of smart methods, devices and products, being leveraged by initiatives like Industrie 4.0. In this context, the data is a valuable asset that can support the smart factory features through the use of Big Data and advanced analytics approaches. In order to address such requirements and related challenges, Cyber Physical Systems (CPS) promote the development of more intelligent, adaptable and responsiveness supervisory and control systems capable to overcome the inherent complexity and dynamics of industrial environments. In this context, this work presents an agent-based industrial CPS, where agents are endowed with data analysis capabilities for distributed, collaborative and adaptive process supervision and control. Additionally, to address the different industrial levels’ requirements, this work combines two main data analysis scopes: at operational level, applying distributed data stream analysis for rapid response monitoring and control, and at supervisory level, applying big data analysis for decision-making, planning and optimization. Some experiments have been performed in the context of an electric micro grid where agents were able to perform distributed data analysis to predict the renewable energy production.info:eu-repo/semantics/publishedVersio

A holonic approach to dynamic manufacturing scheduling

Manufacturing scheduling is a complex combinatorial problem, particularly in distributed and dynamic environments. This paper presents a holonic approach to manufacturing scheduling, where the scheduling functions are distributed by several entities, combining their calculation power and local optimization capability. In this scheduling and control approach, the objective is to achieve fast and dynamic re-scheduling using a scheduling mechanism that evolves dynamically to combine centralized and distributed strategies, improving its responsiveness to emergence, instead of the complex and optimized scheduling algorithms found in traditional approaches

Adaptive scheduling based on self-organized holonic swarm of schedulers

Scheduling plays an important role in the companies’ competiveness, dealing with complex combinatorial problems subject to uncertainty and emergence. In particular, in the ramp-up phase of small lot-sizes of complex products, scheduling is more demanding, e.g. due to late requests and immature technology products and processes. This paper presents the principles of a distributed scheduling architecture based on holonic and swarm principles and implemented using multi-agent system technology. In particular, it is described the coordination among the network of the swarm of schedulers and analysed the impact of embedded self-organization mechanisms.The research leading to these results has received funding from the European Union Seventh Framework Programme FP7 ARUM project, under grant agreement n° 314056.info:eu-repo/semantics/publishedVersio

Background, Systematic Review, Challenges and Outlook

Publisher Copyright: © 2013 IEEE. This research is supported by the Digital Manufacturing and Design Training Network (DiManD) project funded by the European Union through the Marie Skłodowska-Curie Innovative Training Networks (H2020-MSCA-ITN-2018) under grant agreement no. 814078The concept of smart manufacturing has attracted huge attention in the last years as an answer to the increasing complexity, heterogeneity, and dynamism of manufacturing ecosystems. This vision embraces the notion of autonomous and self-organized elements, capable of self-management and self-decision-making under a context-aware and intelligent infrastructure. While dealing with dynamic and uncertain environments, these solutions are also contributing to generating social impact and introducing sustainability into the industrial equation thanks to the development of task-specific resources that can be easily adapted, re-used, and shared. A lot of research under the context of self-organization in smart manufacturing has been produced in the last decade considering different methodologies and developed under different contexts. Most of these works are still in the conceptual or experimental stage and have been developed under different application scenarios. Thus, it is necessary to evaluate their design principles and potentiate their results. The objective of this paper is threefold. First, to introduce the main ideas behind self-organization in smart manufacturing. Then, through a systematic literature review, describe the current status in terms of technological and implementation details, mechanisms used, and some of the potential future research directions. Finally, the presentation of an outlook that summarizes the main results of this work and their interrelation to facilitate the development of self-organized manufacturing solutions. By providing a holistic overview of the field, we expect that this work can be used by academics and practitioners as a guide to generate awareness of possible requirements, industrial challenges, and opportunities that future self-organizing solutions can have towards a smart manufacturing transition.publishersversionpublishe

Reconfigurable production control systems: beyond ADACOR

In the recent evolution of production control systems, the emergence of decentralized systems capable of dealing with the rapid changes in the production environment better than the traditional centralized architectures has been one of the most significant developments. The agent-based and holonic paradigms symbolize this approach, and ADACOR holonic control architecture is a successful example of such a system. In this paper, authors discusses the current challenges and the way to go in the direction of new, reconfigurable, evolvable and ubiquitous systems, able to respond to current production environment demands and variability