Eco‐Holonic 4.0 Circular Business Model to Conceptualize Sustainable Value Chain Towards Digital Transition

The purpose of this paper is to conceptualize a circular business model based on an Eco-Holonic Architecture, through the integration of circular economy and holonic principles. A conceptual model is developed to manage the complexity of integrating circular economy principles, digital transformation, and tools and frameworks for sustainability into business models. The proposed architecture is multilevel and multiscale in order to achieve the instantiation of the sustainable value chain in any territory. The architecture promotes the incorporation of circular economy and holonic principles into new circular business models. This integrated perspective of business model can support the design and upgrade of the manufacturing companies in their respective industrial sectors. The conceptual model proposed is based on activity theory that considers the interactions between technical and social systems and allows the mitigation of the metabolic rift that exists between natural and social metabolism. This study contributes to the existing literature on circular economy, circular business models and activity theory by considering holonic paradigm concerns, which have not been explored yet. This research also offers a unique holonic architecture of circular business model by considering different levels, relationships, dynamism and contextualization (territory) aspects

Special Session on Industry 4.0

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Agent-based asset administration shell approach for digitizing industrial assets

Modern manufacturing systems are facing new challenges related to the fast-changing market conditions, increased global competition and rapid technological developments, imposing strong requirements in terms of flexibility, robustness and reconfigurability. In this context, the Industry 4.0 (I4.0) paradigm relies on digitizing industrial assets to fulfil these requirements. The implementation of this digitization process is being promoted by the so-called Asset Administration Shell (AAS), a digital representation of an asset that complies with standardization and interoperability strategies. At this moment, a significant part of the AAS developments is more focused on the information management of the asset along its lifecycle and not concerned with aspects of intelligence and collaboration, which are fundamental aspects to develop I4.0 compliant solutions. In this sense, this paper presents an agent-based AAS approach for enhancing the digitization process of assets, considering agents to embed distributed intelligence and collaborative functions, service orientation to support interoperability, and holonic principles to provide the system organization. The proposed agent-based AAS was implemented in an industrial automation system aiming to analyze its applicability.info:eu-repo/semantics/publishedVersio

Towards the next generation of smart grids: semantic and holonic multi-agent management of distributed energy resources

The energy landscape is experiencing accelerating change; centralized energy systems are being decarbonized, and transitioning towards distributed energy systems, facilitated by advances in power system management and information and communication technologies. This paper elaborates on these generations of energy systems by critically reviewing relevant authoritative literature. This includes a discussion of modern concepts such as ‘smart grid’, ‘microgrid’, ‘virtual power plant’ and ‘multi-energy system’, and the relationships between them, as well as the trends towards distributed intelligence and interoperability. Each of these emerging urban energy concepts holds merit when applied within a centralized grid paradigm, but very little research applies these approaches within the emerging energy landscape typified by a high penetration of distributed energy resources, prosumers (consumers and producers), interoperability, and big data. Given the ongoing boom in these fields, this will lead to new challenges and opportunities as the status-quo of energy systems changes dramatically. We argue that a new generation of holonic energy systems is required to orchestrate the interplay between these dense, diverse and distributed energy components. The paper therefore contributes a description of holonic energy systems and the implicit research required towards sustainability and resilience in the imminent energy landscape. This promotes the systemic features of autonomy, belonging, connectivity, diversity and emergence, and balances global and local system objectives, through adaptive control topologies and demand responsive energy management. Future research avenues are identified to support this transition regarding interoperability, secure distributed control and a system of systems approach

Agents enabling cyber-physical production systems

In order to be prepared for future challenges facing the industrial production domain, Cyber-Physical Production Systems (CPPS) consisting of intelligent entities which collaborate and exchange information globally are being proclaimed recently as part of Industrie 4.0. In this article the requirements of CPPS and abilities of agents as enabling technology are discussed. The applicability of agents for realizing CPPS is exemplarily shown based on three selected use cases with different requirements regarding real-time and dependability. The paper finally concludes with opportunities and open research issues that need to be faced in order to achieve agent-based CPPSs.info:eu-repo/semantics/publishedVersio

Soft computing agents for e-health applied to the research and control of unknown diseases

This paper presents an Ontology-based Holonic Diagnostic System (OHDS) that combines the advantages of the holonic paradigm with multi-agent system technology and ontology design, for the organization of unstructured biomedical research into structured disease information. We use ontologies as 'brain' for the holonic diagnostic system to enhance its ability to structure information in a meaningful way and share information fast. To integrate dispersed heterogeneous knowledge available on the web we use a fuzzy mechanism ruled by intelligent agents, which automatically structures the information in the adequate ontology template. Our vision of how this system implementation should be backed by a solid security shield that ensures the privacy and safety of medical information concludes the paper

Skill-based reconfiguration of industrial mobile robots

Caused by a rising mass customisation and the high variety of equipment versions, the exibility of manufacturing systems in car productions has to be increased. In addition to a exible handling of production load changes or hardware breakdowns that are established research areas in literature, this thesis presents a skill-based recon guration mechanism for industrial mobile robots to enhance functional recon gurability. The proposed holonic multi-agent system is able to react to functional process changes while missing functionalities are created by self-organisation. Applied to a mobile commissioning system that is provided by AUDI AG, the suggested mechanism is validated in a real-world environment including the on-line veri cation of the recon gured robot functionality in a Validity Check. The present thesis includes an original contribution in three aspects: First, a recon - guration mechanism is presented that reacts in a self-organised way to functional process changes. The application layer of a hardware system converts a semantic description into functional requirements for a new robot skill. The result of this mechanism is the on-line integration of a new functionality into the running process. Second, the proposed system allows maintaining the productivity of the running process and exibly changing the robot hardware through provision of a hardware-abstraction layer. An encapsulated Recon guration Holon dynamically includes the actual con guration each time a recon guration is started. This allows reacting to changed environment settings. As the resulting agent that contains the new functionality, is identical in shape and behaviour to the existing skills, its integration into the running process is conducted without a considerable loss of productivity. Third, the suggested mechanism is composed of a novel agent design that allows implementing self-organisation during the encapsulated recon guration and dependability for standard process executions. The selective assignment of behaviour-based and cognitive agents is the basis for the exibility and e ectiveness of the proposed recon guration mechanism

A generic holonic control architecture for heterogeneous multi-scale and multi-objective smart microgrids

Designing the control infrastructure of future “smart” power grids is a challenging task. Future grids will integrate a wide variety of heterogeneous producers and consumers that are unpredictable and operate at various scales. Information and Communication Technology (ICT) solutions will have to control these in order to attain global objectives at the macrolevel, while also considering private interests at the microlevel. This article proposes a generic holonic architecture to help the development of ICT control systems that meet these requirements. We show how this architecture can integrate heterogeneous control designs, including state-of-the-art smart grid solutions. To illustrate the applicability and utility of this generic architecture, we exemplify its use via a concrete proof-of-concept implementation for a holonic controller, which integrates two types of control solutions and manages a multiscale, multiobjective grid simulator in several scenarios. We believe that the proposed contribution is essential for helping to understand, to reason about, and to develop the “smart” side of future power grids

Holonic Learning: A Flexible Agent-based Distributed Machine Learning Framework

Ever-increasing ubiquity of data and computational resources in the last decade have propelled a notable transition in the machine learning paradigm towards more distributed approaches. Such a transition seeks to not only tackle the scalability and resource distribution challenges but also to address pressing privacy and security concerns. To contribute to the ongoing discourse, this paper introduces Holonic Learning (HoL), a collaborative and privacy-focused learning framework designed for training deep learning models. By leveraging holonic concepts, the HoL framework establishes a structured self-similar hierarchy in the learning process, enabling more nuanced control over collaborations through the individual model aggregation approach of each holon, along with their intra-holon commitment and communication patterns. HoL, in its general form, provides extensive design and flexibility potentials. For empirical analysis and to demonstrate its effectiveness, this paper implements HoloAvg, a special variant of HoL that employs weighted averaging for model aggregation across all holons. The convergence of the proposed method is validated through experiments on both IID and Non-IID settings of the standard MNISt dataset. Furthermore, the performance behaviors of HoL are investigated under various holarchical designs and data distribution scenarios. The presented results affirm HoL's prowess in delivering competitive performance particularly, in the context of the Non-IID data distribution