Soporte para la generación de maquetas virtuales de automatización industrial

[Resumen] Está demostrada la importancia que tienen la realización de prácticas de laboratorio en la educación universitaria relacionada con las ciencias, tecnologías, ingenierías y matemáticas. En el caso de las ingenierías y en particular en conceptos de automatización se hace aún más notorio. Lamentablemente, situaciones como las vividas en estos dos últimos cursos académicos, en los que la docencia presencial no ha sido posible, ha puesto a prueba tanto a docentes como a alumnos. Este trabajo presenta unas directrices y una herramienta de soporte para que el profesorado de este tipo de asignaturas pueda generar maquetas virtuales y por tanto realizar las prácticas de forma online de la misma manera que presencialmente

Digital Twin in the IoT context: a survey on technical features, scenarios and architectural models

Digital Twin is an emerging concept that is gaining attention in various industries. It refers to the ability to clone a physical object into a software counterpart. The softwarized object, termed logical object, reflects all the important properties and characteristics of the original object within a specific application context. To fully determine the expected properties of the Digital Twin, this paper surveys the state of the art starting from the original definition within the manufacturing industry. It takes into account related proposals emerging in other fields, namely, Augmented and Virtual Reality (e.g., avatars), Multi-agent systems, and virtualization. This survey thereby allows for the identification of an extensive set of Digital Twin features that point to the “softwarization” of physical objects. To properly consolidate a shared Digital Twin definition, a set of foundational properties is identified and proposed as a common ground outlining the essential characteristics (must-haves) of a Digital Twin. Once the Digital Twin definition has been consolidated, its technical and business value is discussed in terms of applicability and opportunities. Four application scenarios illustrate how the Digital Twin concept can be used and how some industries are applying it. The scenarios also lead to a generic DT architectural Model. This analysis is then complemented by the identification of software architecture models and guidelines in order to present a general functional framework for the Digital Twin. The paper, eventually, analyses a set of possible evolution paths for the Digital Twin considering its possible usage as a major enabler for the softwarization process

Digital twin-enabled smart industrial systems: a bibliometric review

The aim of this study is to investigate the body of literature on digital twins, exploring, in particular, their role in enabling smart industrial systems. This review adopts a dynamic and quantitative bibliometric method including works citations, keywords co-occurrence networks and keywords burst detection with the aim of clarifying the main contributions to this research area and highlighting prevalent topics and trends over time. The analysis performed on citations traces the backbone of contributions to the topic, visible within the main path. Keywords co-occurrence networks depict the prevalent issues addressed, tools implemented and application areas. The burst detection completes the analysis identifying the trends and most recent research areas characterizing research on the digital twin topic. Decision-making, process design and life cycle as well as the enabling role in the adoption of the latest industrial paradigms emerge as the prevalent issues addressed by the body of literature on digital twins. In particular, the up-to-date issues of real-time systems and industry 4.0 technologies, closely related to the concept of smart industrial systems, characterize the latest research trajectories identified in the literature on digital twins. In this context, the digital twin can find new opportunities for application in manufacturing, control and services

Sistemas de informação na indústria 4.0 : mecanismos de apoio à transferência de dados para conhecimento em ambientes Lean

The paradigm that presently emerges in the organizational context, known as Industry 4.0 (I4.0) or Fourth Industrial Revolution, promises to bring principles of connectivity and flexibility to the companies that embrace it. Industry 4.0 enhances the efficiency in adapting in real time to the customers’ requirements, through the establishment of an intelligent shop floor capable of answering in a flexible and customized way to market changes. However, during the last three decades, it is known that the adoption of the Lean philosophy was absorbed by the industrial environment, with results that proved to be exuberant, considering the simplicity of the tools. In this way, the I4.0 implementation must be prepared to preserve the existing manufacturing systems, proceeding, whenever possible, to upgrade them on a Lean excellence basis. It is said that information systems will be decisive in the foundation of the I4.0 paradigm. Of these, MES systems, with greater connection to the shop floor, will tend to be aligned with existing practices, contributing, through their connectivity, to the introduction of knowledge management practices and data visualization mechanisms. In the specification and architecture phase of these systems, understanding the processes will be crucial. Thus, their documentation is an organizational pillar, with BPMN and UML being able to guide it. However, and in addition to its usefulness in the processes’ mapping, BPMN is also likely to be applied in capturing tacit knowledge, which can be a foundation for the constitution of knowledge repositories, impacting organizational excellence. It is in this context that the present work is implanted, aiming at the creation of guidelines and mechanisms that facilitate the implementation of I4.0 strategies in Lean industrial environments. The adopted methodology first went through an exhaustive literature review, in order to find possible bilateral effects between I4.0 technologies and lean tools. Then, the development of some applications aligned with the I4.0 paradigm, as a technological engine, and the Lean philosophy, as a tool for eliminating waste and / or creating value, was contemplated. From the various development experiences in an industrial context and considering the evidence reported in the literature, this study proposes a Lean 4.0 framework oriented to the shop floor.O paradigma que atualmente emerge no contexto organizacional, conhecido como Indústria 4.0 (I4.0) ou Quarta Revolução Industrial, promete trazer princípios de conectividade e flexibilidade às empresas que a adotam. A Indústria 4.0 potencia a eficácia no ajuste em tempo real aos requisitos dos clientes, através da constituição de um chão de fábrica inteligente e capaz de responder de forma flexível e customizada às mudanças do mercado. Contudo, durante as últimas três décadas, sabe-se que a adoção da filosofia Lean foi absorvida pelo meio industrial, com resultados que se demonstraram exuberantes, tendo em conta a simplicidade das ferramentas. Deste modo, a implementação I4.0 deve ser feita no sentido da preservação dos sistemas de manufatura já existentes, procedendo, desde que possível, ao seu upgrade numa base de excelência Lean. Conta-se que os sistemas de informação serão decisivos na fundação do paradigma I4.0. Destes, os sistemas MES, com maior conexão ao chão de fábrica, tenderão a ser alinhados com as práticas já existentes, contribuindo, através da sua conectividade, para a introdução de práticas de gestão do conhecimento e mecanismos de visualização de dados. Na fase de especificação e arquitetura destes sistemas, o entendimento dos processos será crucial. Assim, a documentação dos mesmos é um pilar organizacional, estando o BPMN e a UML capazes de a orientar. Porém, e a somar à sua utilidade na ilustração de processos, o BPMN está igualmente passível de ser aplicado na captação de conhecimento tácito, o que por si pode ser uma base para a constituição de repositórios de conhecimento, contribuindo para a excelência organizacional. É neste contexto que o presente trabalho se insere, tendo como objetivo a criação de linhas orientadoras e mecanismos que facilitem a implementação de estratégias I4.0 em ambientes industriais Lean. A metodologia adotada passou, primeiramente, por uma exaustiva revisão da literatura, por forma a encontrar possíveis efeitos bilaterais entre tecnologias I4.0 e ferramentas lean. De seguida, contemplou-se o desenvolvimento de alguns aplicativos alinhados ao paradigma I4.0, enquanto motor tecnológico, e à filosofia Lean, enquanto ferramenta de eliminação de desperdícios e/ou criação de valor. Das diversas experiências de desenvolvimento em contexto industrial e considerando as evidências reportadas na literatura o presente estudo propõe uma framework Lean 4.0 orientado ao chão de fábrica.Mestrado em Engenharia e Gestão Industria

Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC

Industry 4.0 has made it possible for emerging technologies to revolutionize how organizations operate. New applications, supported by the Internet of things, cyber physical systems, and cloud computing, take advantage of large data exchange networks that capture data from the real and virtual world, to generate valuable insights for product development. This, together with the growing digitalization of product lifecycle information, has made information the most valuable asset of an organization, as it can be applied to improve product design, reduce lead time and decrease monetary costs. However, the growing volume, formats, and purposes of the information an organization captures, also brings challenges for information management, and consequently, appropriate IM and KM instruments and strategies must be adopted to successfully take advantage of organizational knowledge. The adoption of Knowledge-based Engineering can accomplish these goals. KBE refers to the knowledge management tasks of capturing, storing, modeling, coding, and sharing of organizational knowledge, both in explicit form, such as documents, and tacit form, present in the minds of employees. Ultimately, this results in systems that can automate design tasks. Also in the context of technological advances, a new concept called Digital Twin has emerged, which employs bidirectional data transmission to mirror the lifecycle of a physical product, in the virtual realm. Proposed DT functionalities actively use organizational knowledge to improve and automate product design, and as such, this technology can be an adequate vessel for KBE. This dissertation focuses on the implementation of the Digital Twin in power transformer development processes. Using the case of Efacec, a portuguese firm of the energy sector, the DT concept was developed, and this involved defining functionalities that are driven by organizational knowledge to automate, optimize, and streamline PT design tasks, thus accomplishing the goal of KBE. Some of the proposed DT features are the generation of design templates, the identification of design non-conformities, and the capture of engineer feedback. Furthermore, the DT information architecture that is required for these functionalities to successfully be implemented, was envisioned, by defining all captured and generated information in each PT lifecycle phase. Finally, a faceted classification scheme that classifies DT information and enables queries within the DT platform, was developed

A unified framework for digital twin development in manufacturing

The concept of digital twin (DT) is undergoing rapid transformation and attracting increased attention across industries. It is recognised as an innovative technology offering real-time monitoring, simulation, optimisation, accurate forecasting and bi-directional feedback between physical and digital objects. Despite extensive academic and industrial research, DT has not yet been properly understood and implemented by many industries, due to challenges identified during its development. Existing literature shows that there is a lack of a unified framework to build DT, a lack of standardisation in the development, and challenges related to coherent goals of DT in a multi-disciplinary team engaged in the design, development and implementation of DT to a larger scale system. To address these challenges, this study introduces a unified framework for DT development, emphasising reusability and scalability. The framework harmonises existing DT frameworks by unifying concepts and process development. It facilitates the integration of heterogeneous data types and ensures a continuous flow of information among data sources, simulation models and visualisation platforms. Scalability is achieved through ontology implementation, while employing an agent-based approach, it monitors physical asset performance, automatically detects faults, checks repair status and offers operators feedback on asset demand, availability and health conditions. The effectiveness of the proposed DT framework is validated through its application to a real-world case study involving five interconnected air compressors located at the Connected Facility at Devonport Royal Dockyard, UK. The DT automatically and remotely monitors the performance and health status of compressors, providing guidance to humans on fault repair. This guidance dynamically adapts based on feedback from the DT. Analyses of the results demonstrate that the proposed DT increases the facility’s operation availability and enhances decision-making by promptly and accurately detecting faults.This research was funded by the supported by the EPSRC, UK as part of the ‘Digital Toolkit for optimisation of operators and technology in manufacturing partnerships’ project (DigiTOP; https://digitop.ac.uk; EP/R032718/1), the Centre for Digital Engineering and Manufacturing at Cranfield University and Babcock International

COMPARAÇÃO DE MÉTODOS DE APRENDIZAGEM POR REFORÇO EM PROCESSOS INDUSTRIAIS DISCRETOS SEQUENCIAIS

O processo de comissionamento de equipamentos durante a implementação de um novo sistema, ou na reconfiguração de um já existente, é uma etapa em que as empresas gastam dinheiro e tempo antes da entrada em operação. Baseando-se nesse problema, este trabalho analisa a utilização de Gémeos Digitais, que simulem o ambiente fabril, em conjunto com a utilização de técnicas de Aprendizagem por Reforço para permitir que o sistema se reconfigure e se programe de forma automática. Diferentemente das técnicas tradicionais de controlo, a Aprendizagem por Reforço encara o sistema como uma caixa negra, em que a interação entre o agente e o ambiente promove a sintonização dos parâmetros necessários para o funcionamento correto do processo industrial. Isso resulta na economia de dinheiro, na diminuição de tempo de produção e na busca de inúmeras possibilidades de operação até que se encontre a mais eficiente. Acrescenta-se a tudo isso a diminuição do tempo de exposição de pessoas ao processo de implementação inicial e consequente diminuição de acidentes, uma vez que o comissionamento ocorre no ambiente virtual. Dessa forma, este trabalho desenvolve e aplica alguns dos diferentes algoritmos de Deep Reinforcement Learning a um sistema de empacotamente de latas. O principal objetivo é avaliar a viabilidade e o desempenho de utilizar estes tipos de algoritmos na aprendizagem e otimização automática das sequências de controlo em processos industriais de natureza sequencial e discreta. Dada a natureza sequencial dos processos, com necessidade inerente de efeito de memória, foram experimentadas diferentes arquiteturas de redes neuronais, realizando um estudo comparativo sobre a performance das redes neuronais LSTM (Long Short-Term Memory) frente à utilização de buffers de memória de estados anteriores de diferentes tamanhos. Por fim, os modelos com melhores resultados e maior estabilidade foram aplicados aos Gémeos Digitais, mostrando a capacidade que estes tipos de algoritmos de aprendizagem automática têm para ser aplicados no controlo de sistemas industriais

XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja)

[Resumen] Las Jornadas de Automática (JA) son el evento más importante del Comité Español de Automática (CEA), entidad científico-técnica con más de cincuenta años de vida y destinada a la difusión e implantación de la Automática en la sociedad. Este año se celebra la cuadragésima tercera edición de las JA, que constituyen el punto de encuentro de la comunidad de Automática de nuestro país. La presente edición permitirá dar visibilidad a los nuevos retos y resultados del ámbito, y su uso en un gran número de aplicaciones, entre otras, las energías renovables, la bioingeniería o la robótica asistencial. Además de la componente científica, que se ve reflejada en este libro de actas, las JA son un punto de encuentro de las diferentes generaciones de profesores, investigadores y profesionales, incluyendo la componente social que es de vital importancia. Esta edición 2022 de las JA se celebra en Logroño, capital de La Rioja, región mundialmente conocida por la calidad de sus vinos de Denominación de Origen y que ha asumido el desafío de poder ganar competitividad a través de la transformación verde y digital. Pero también por ser la cuna del castellano e impulsar el Valle de la Lengua con la ayuda de las nuevas tecnologías, entre ellas la Automática Inteligente. Los organizadores de estas JA, pertenecientes al Área de Ingeniería de Sistemas y Automática del Departamento de Ingeniería Eléctrica de la Universidad de La Rioja (UR), constituyen un pilar fundamental en el apoyo a la región para el estudio, implementación y difusión de estos retos. Esta edición, la primera en formato íntegramente presencial después de la pandemia de la covid-19, cuenta con más de 200 asistentes y se celebra a caballo entre el Edificio Politécnico de la Escuela Técnica Superior de Ingeniería Industrial y el Monasterio de Yuso situado en San Millán de la Cogolla, dos marcos excepcionales para la realización de las JA. Como parte del programa científico, dos sesiones plenarias harán hincapié, respectivamente, sobre soluciones de control para afrontar los nuevos retos energéticos, y sobre la calidad de los datos para una inteligencia artificial (IA) imparcial y confiable. También, dos mesas redondas debatirán aplicaciones de la IA y la implantación de la tecnología digital en la actividad profesional. Adicionalmente, destacaremos dos clases magistrales alineadas con tecnología de última generación que serán impartidas por profesionales de la empresa. Las JA también van a albergar dos competiciones: CEABOT, con robots humanoides, y el Concurso de Ingeniería de Control, enfocado a UAVs. A todas estas actividades hay que añadir las reuniones de los grupos temáticos de CEA, las exhibiciones de pósteres con las comunicaciones presentadas a las JA y los expositores de las empresas. Por último, durante el evento se va a proceder a la entrega del “Premio Nacional de Automática” (edición 2022) y del “Premio CEA al Talento Femenino en Automática”, patrocinado por el Gobierno de La Rioja (en su primera edición), además de diversos galardones enmarcados dentro de las actividades de los grupos temáticos de CEA. Las actas de las XLIII Jornadas de Automática están formadas por un total de 143 comunicaciones, organizadas en torno a los nueve Grupos Temáticos y a las dos Líneas Estratégicas de CEA. Los trabajos seleccionados han sido sometidos a un proceso de revisión por pares