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

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

Agent-based distributed manufacturing control: a state-of-the-art survey

Manufacturing has faced significant changes during the last years, namely the move from a local economy towards a global and competitive economy, with markets demanding for highly customized products of high quality at lower costs, and with short life cycles. In this environment, manufacturing enterprises, to remain competitive, must respond closely to customer demands by improving their flexibility and agility, while maintaining their productivity and quality. Dynamic response to emergence is becoming a key issue in manufacturing field because traditional manufacturing control systems are built upon rigid control architectures, which cannot respond efficiently and effectively to dynamic change. In these circumstances, the current challenge is to develop manufacturing control systems that exhibit intelligence, robustness and adaptation to the environment changes and disturbances. The introduction of multi-agent systems and holonic manufacturing systems paradigms addresses these requirements, bringing the advantages of modularity, decentralization, autonomy, scalability and re- usability. This paper surveys the literature in manufacturing control systems using distributed artificial intelligence techniques, namely multi-agent systems and holonic manufacturing systems principles. The paper also discusses the reasons for the weak adoption of these approaches by industry and points out the challenges and research opportunities for the future

Special Session on Industry 4.0

No abstract available

A holonic manufacturing architecture for line-less mobile assembly systems operations planning and control

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2022.O Line-Less Mobile Assembly Systems (LMAS) é um paradigma de fabricação que visa maximizar a resposta às tendências do mercado através de configurações adaptáveis de fábrica utilizando recursos de montagem móvel. Tais sistemas podem ser caracterizados como holonic manufacturing systems (HMS), cujas chamadas holonic control architecture (HCA) são recentemente retratadas como abordagens habilitadoras da Indústria 4.0 devido a suas relações de entidades temporárias (hierárquicas e/ou heterárquicas). Embora as estruturas de referência HCA como PROSA ou ADACOR/ADACOR² tenham sido muito discutidas na literatura, nenhuma delas pode ser aplicada diretamente ao contexto LMAS. Assim, esta dissertação visa responder à pergunta \"Como uma arquitetura de produção e sistema de controle LMAS precisa ser projetada?\" apresentando os modelos de projeto de arquitetura desenvolvidos de acordo com as etapas da metodologia para desenvolvimento de sistemas holônicos multi-agentes ANEMONA. A fase de análise da ANEMONA resulta em uma especificação do caso de uso, requisitos, objetivos do sistema, simplificações e suposições. A fase de projeto resulta nos modelos de organização, interação e agentes, seguido de uma breve análise de sua cobertura comportamental. O resultado da fase de implementação é um protótipo (realizado com o Robot Operation System) que implementa os modelos ANEMONA e uma ontologia LMAS, que reutiliza elementos de ontologias de referência do domínio de manufatura. A fim de testar o protótipo, um algoritmo para geração de dados para teste baseado na complexidade dos produtos e na flexibilidade do chão de fábrica é apresentado. A validação qualitativa dos modelos HCA é baseada em como o HCA proposto atende a critérios específicos para avaliar sistemas HCA. A validação é complementada por uma análise quantitativa considerando o comportamento dos modelos implementados durante a execução normal e a execução interrompida (e.g. equipamento defeituoso) em um ambiente simulado. A validação da execução normal concentra-se no desvio de tempo entre as agendas planejadas e executadas, o que provou ser em média irrelevante dentro do caso simulado considerando a ordem de magnitude das operações típicas demandadas. Posteriormente, durante a execução do caso interrompido, o sistema é testado sob a simulação de uma falha, onde duas estratégias são aplicadas, LOCAL\_FIX e REORGANIZATION, e seu resultado é comparado para decidir qual é a opção apropriada quando o objetivo é reduzir o tempo total de execução. Finalmente, é apresentada uma análise sobre a cobertura desta dissertação culminando em diretrizes que podem ser vistas como uma resposta possível (entre muitas outras) para a questão de pesquisa apresentada. Além disso, são apresentados pontos fortes e fracos dos modelos desenvolvidos, e possíveis melhorias e idéias para futuras contribuições para a implementação de sistemas de controle holônico para LMAS.Abstract: The Line-Less Mobile Assembly Systems (LMAS) is a manufacturing paradigm aiming to maximize responsiveness to market trends (product-individualization and ever-shortening product lifecycles) by adaptive factory configurations utilizing mobile assembly resources. Such responsive systems can be characterized as holonic manufacturing systems (HMS), whose so-called holonic control architectures (HCA) are recently portrayed as Industry 4.0-enabling approaches due to their mixed-hierarchical and -heterarchical temporary entity relationships. They are particularly suitable for distributed and flexible systems as the Line-Less Mobile Assembly or Matrix-Production, as they meet reconfigurability capabilities. Though HCA reference structures as PROSA or ADACOR/ADACOR² have been heavily discussed in the literature, neither can directly be applied to the LMAS context. Methodologies such as ANEMONA provide guidelines and best practices for the development of holonic multi-agent systems. Accordingly, this dissertation aims to answer the question \"How does an LMAS production and control system architecture need to be designed?\" presenting the architecture design models developed according to the steps of the ANEMONA methodology. The ANEMONA analysis phase results in a use case specification, requirements, system goals, simplifications, and assumptions. The design phase results in an LMAS architecture design consisting of the organization, interaction, and agent models followed by a brief analysis of its behavioral coverage. The implementation phase result is an LMAS ontology, which reuses elements from the widespread manufacturing domain ontologies MAnufacturing's Semantics Ontology (MASON) and Manufacturing Resource Capability Ontology (MaRCO) enriched with essential holonic concepts. The architecture approach and ontology are implemented using the Robot Operating System (ROS) robotic framework. In order to create test data sets validation, an algorithm for test generation based on the complexity of products and the shopfloor flexibility is presented considering a maximum number of operations per work station and the maximum number of simultaneous stations. The validation phase presents a two-folded validation: qualitative and quantitative. The qualitative validation of the HCA models is based on how the proposed HCA attends specific criteria for evaluating HCA systems (e.g., modularity, integrability, diagnosability, fault tolerance, distributability, developer training requirements). The validation is complemented by a quantitative analysis considering the behavior of the implemented models during the normal execution and disrupted execution (e.g.; defective equipment) in a simulated environment (in the form of a software prototype). The normal execution validation focuses on the time drift between the planned and executed schedules, which has proved to be irrelevant within the simulated case considering the order of magnitude of the typical demanded operations. Subsequently, during the disrupted case execution, the system is tested under the simulation of a failure, where two strategies are applied, LOCAL\_FIX and REORGANIZATION, and their outcome is compared to decide which one is the appropriate option when the goal is to reduce the overall execution time. Ultimately, it is presented an analysis about the coverage of this dissertation culminating into guidelines that can be seen as one possible answer (among many others) for the presented research question. Furthermore, strong and weak points of the developed models are presented, and possible improvements and ideas for future contributions towards the implementation of holonic control systems for LMAS

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 framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

An agile and adaptive holonic architecture for manufacturing control

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2004. Faculdade de Engenharia. Universidade do Port

A holonic multi-agent methodology to design sustainable intelligent manufacturing control systems

[EN] The urgent need for sustainable development is imposing radical changes in the way manufacturing systems are designed and implemented. The overall sustainability in industrial activities of manufacturing companies must be achieved at the same time that they face unprecedented levels of global competition. Therefore, there is a well-known need for tools and methods that can support the design and implementation of these systems in an effective way. This paper proposes an engineering method that helps researchers to design sustainable intelligent manufacturing systems. The approach is focused on the identification of the manufacturing components and the design and integration of sustainability-oriented mechanisms in the system specification, providing specific development guidelines and tools with built-in support for sustainable features. Besides, a set of case studies is presented in order to assess the proposed method.This research was supported by research projects TIN2015-65515-C4-1-R and TIN2016-80856-R from the Spanish government. The authors would like to acknowledge T. Bonte for her contribution to the NetLogo simulator of the AIP PRIMECA cell.Giret Boggino, AS.; Trentesaux, D.; Salido Gregorio, MÁ.; Garcia, E.; Adam, E. (2017). A holonic multi-agent methodology to design sustainable intelligent manufacturing control systems. Journal of Cleaner Production. 167(1):1370-1386. https://doi.org/10.1016/j.jclepro.2017.03.079S13701386167

New Shop Floor Control Approaches for Virtual Enterprises

The virtual enterprise paradigm seems a fit response to face market instability and the volatile nature of business opportunities increasing enterprise’s interest in similar forms of networked organisations. The dynamic environment of a virtual enterprise requires that partners in the consortium own reconfigurable shop floors. This paper presents new approaches to shop floor control that meet the requirements of the new industrial paradigms and argues on work re-organization at shop floor level.virtual enterprise; networked organisations