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

Adaptation of Manufacturing Systems in Dynamic Environment Based on Capability Description Method

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Worker-robot cooperation and integration into the manufacturing workcell via the holonic control architecture

Cooperative manufacturing is a new field of research, which addresses new challenges beyond the physical safety of the worker. Those new challenges appear due to the need to connect the worker and the cobot from the informatics point of view in one cooperative workcell. This requires developing an appropriate manufacturing control system, which fits the nature of both the worker and the cobot. Furthermore, the manufacturing control system must be able to understand the production variations, to guide the cooperation between worker and the cobot and adapt with the production variations.Die kooperative Fertigung ist ein neues Forschungsgebiet, das sich neuen Herausforderungen stellt. Diese neuen Herausforderungen ergeben sich aus der Notwendigkeit, den Arbeiter und den Cobot aus der Sicht der Informatik in einem kooperativen Arbeitsplatz zu verbinden. Dies erfordert die Entwicklung eines geeigneten Produktionskontrollsystems, das sowohl der Natur des Arbeiters als auch der des Cobots entspricht. Darüber hinaus muss die Fertigungssteuerung in der Lage sein, die Produktionsschwankungen zu verstehen, um die Zusammenarbeit zwischen Arbeiter und Cobot zu steuern

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

Analysis and evaluation of multi-agent systems for digital production planning and control

Industrial manufacturing companies have different IT control functions that can be represented with a so-called hierarchical automation pyramid. While these conventional software systems especially support the mass production with consistent demand, the future project “Industry 4.0” focuses on customer-oriented and adaptable production processes. In order to move from conventional production systems to a factory of the future, the control levels must be redistributed. With the help of cyber-physical production systems, an interoperable architecture must be, implemented which removes the hierarchical connection of the former control levels. The accompanied digitalisation of industrial companies makes the transition to modular production possible. At the same time, the requirements for production planning and control are increasing, which can be solved with approaches such as multi-agent systems (MASs). These software solutions are autonomous and intelligent objects with a distinct collaborative ability. There are different modelling methods, communication and interaction structures, as well as different development frameworks for these new systems. Since multi-agent systems have not yet been established as an industrial standard due to their high complexity, they are usually only tested in simulations. In this bachelor thesis, a detailed literature review on the topic of MASs in the field of production planning and control is presented. In addition, selected multi-agent approaches are evaluated and compared using specific classification criteria. In addition, the applicability of using these systems in digital and modular production is assessed

A Capacity Planning Simulation Model for Reconfigurable Manufacturing Systems

Important objectives and challenges in today’s manufacturing environment include the introduction of new products and the designing and developing of reconfigurable manufacturing systems. The objective of this research is to investigate and support the reconfigurability of a manufacturing system in terms of scalability by applying a discrete-event simulation modelling technique integrated with flexible capacity control functions and communication rules for re-scaling process. Moreover, the possible extension of integrating the discrete-event simulation with an agent-based model is presented as a framework. The benefits of this framework are collaborative decision making using agents for flexible reaction to system changes and system performance improvement. AnyLogic multi-method simulation modelling platform is utilized to design and create different simulation modelling scenarios. The developed capacity planning simulation model results are demonstrated in terms of a case study using the configurable assembly Learning Factory (iFactory) in the Intelligent Manufacturing Systems (IMS) Center at the University of Windsor. The main benefit of developed capacity planning simulation in comparison to traditional discrete-event simulation is, with a single simulation run, the recommended capacity for manufacturing system will be determined instead of running several discrete-event simulation models to find the needed capacity

Agent-based Hierarchical Planning and Scheduling Control in Dynamically Integrated Manufacturing System

It has been broadly recognised that today’s manufacturing organisations face increasing pressures from continuous and unexpected changes in the business environment such as changes in product types, changes in demand pattern, changes in manufacturing technologies etc. To enable manufacturing organisations to rapidly and timely deal with these changes, operational decisions (e.g., process planning and production scheduling) have to be integrated with dynamic system restructure or reconfiguration so that manufacturing organisations do not only use the flexible resource utilisations to deal with these changes, but also can dynamically reconfigure their existing system structures in response these changes. A manufacturing system concept and implementation methodology is proposed by the Exeter Manufacturing Enterprise Centre (XMEC), which is called the Dynamically Integrated Manufacturing System (DIMS). The overall aim of DIMS is to provide a systematic modelling and control framework in which operational decisions can be integrated with the dynamic system restructuring decisions so as to help manufacturing systems to dynamically deal with changes in the business environment. This PhD research is a part of DIMS research, which focuses on the investigation on operational control in DIMS. Based on the established agent-based modelling architecture in DIMS, this research develops two agent bidding mechanisms for the hierarchical control of production planning and scheduling. These two mechanisms work together to assist manufacturing systems in making optimal and flexible operational decisions in response to changes in the business environment. The first mechanism is the iterative agent bidding mechanism based on a Genetic Algorithm (GA) which facilitates the determination of the optimal or near optimal allocation of a production job containing a set of sub-jobs to a pool of heterarchical resources. The second mechanism is the hierarchical agent bidding mechanism which enables product orders to be cost-efficiently and flexibly planned and scheduled to meet the orders’ due dates. The novelty of this mechanism is that it enables orders to be fulfilled within structural constraints of manufacturing systems as far as possible and however enables resources to be regrouped flexibly across system boundaries when orders cannot be fulfilled within structural constraints of manufacturing systems

A model-based approach for supporting flexible automation production systems and an agent-based implementaction

158 p.En esta Tesis Doctoral se plantea una arquitectura de gestión genérica y personalizable, capaz de asegurar el cumplimiento de los requisitos de calidad de servicio (QoS) de un sistema de control industrial. Esta arquitectura permite la modificación de los mecanismos de detección y recuperación de los requisitos de QoS en función de diversos tipos de ésta. Como prueba de concepto, la arquitectura de gestión ha sido implementada mediante un middleware basado en sistemas multi-agente. Este middleware proporciona una serie de agentes distribuidos, los cuales se encargan de la monitorización y recuperación de las QoS en caso de su perdida.La incorporación de los mecanismos de reconfiguración incrementa la complejidad de los sistemas de control. Con el fin de facilitar el diseño de estos sistemas, se ha presentado un framework basado en modelos que guía y facilita el diseño de los sistemas de control reconfigurables. Este framework proporciona una serie de herramientas basadas en modelos que permiten la generación automática del código de control del sistema, así como de los mecanismos de monitorización y reconfiguración de los agentes del middleware.La implementación de la arquitectura ha sido validada mediante una serie de escenarios basados en una célula de montaje real