Digital Pyramid: an approach to relate industrial automation and digital twin concepts

Cortés, Daniel; Ramírez, José; Villagómez, Luis E.; Batres, Rafael; Vásquez, Virgilio; Molina, Arturo

doi:10.1109/ice/itmc49519.2020.9198643

Cited by 10 publications

(6 citation statements)

References 14 publications

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“…Some research works that propose DTs for training purposes are presented as follows. Cortes et al [ 49 ] present a DT to teach industrial concepts such as the automation and programming of programmable logic controllers (PLC), industrial network traffic and modeling using system dynamics. Waat et al [ 50 ] propose a DT with AR capabilities using physical geometrical models.…”

Section: Digital Twin Designmentioning

confidence: 99%

Design, Modeling and Implementation of Digital Twins

Segovia

García-Alfaro

2022

Sensors

157

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A Digital Twin (DT) is a set of computer-generated models that map a physical object into a virtual space. Both physical and virtual elements exchange information to monitor, simulate, predict, diagnose and control the state and behavior of the physical object within the virtual space. DTs supply a system with information and operating status, providing capabilities to create new business models. In this paper, we focus on the construction of DTs. More specifically, we focus on determining (methodologically) how to design, create and connect physical objects with their virtual counterpart. We explore the problem into several phases: from functional requirement selection and architecture planning to integration and verification of the final (digital) models. We address as well how physical components exchange real-time information with DTs, as well as experimental platforms to build DTs (including protocols and standards). We conclude with a discussion and open challenges.

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Section: Digital Twin Designmentioning

confidence: 99%

Design, Modeling and Implementation of Digital Twins

Segovia

García-Alfaro

2022

Sensors

157

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“…Der Begriff «digitaler Zwilling» umfasst ein Konzept, unter dem die Reproduktion eines physischen Systems in der digitalen Welt verstanden wird (‹Twinning›) (Tao et al 2019b;Holler, Uebernickel, und Brenner 2016;Cortés et al 2020;Baumgartner et al 2022;Kritzigner et al 2018;Tao et al 2018). Die zentralen Aspekte von digitalen Zwillingen sind, manuelle, automatisierte oder in Echtzeit erfasste Daten des physischen Objekts in einem einheitlichen Format bereitzustellen, diese Datenstrukturen zu verarbeiten und unterschiedlich darzustellen.…”

Section: Digitaler Zwilling -Facetten Der Begriffsdefinitionenunclassified

Digitale Zwillinge in der naturwissenschaftlichen Bildung

Geuer,

Ulber

2024

MedienPädagogik

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Digitale Medien sind elementarer Bestandteil in Lehr-Lern-Prozessen und stehen im Einklang mit den physischen, medialen und virtuellen Lebensräumen der Schüler:innen indem sie Gegenwarts- und insbesondere auch eine Zukunftsbedeutung für die Heranwachsenden haben. Die didaktisch-methodische Reflektion und Bewertung von technologischen Innovationen aus dem Internet of Things (IoT) oder der Industrie 4.0 ermöglichen es, grundlegende Aussagen zu fächerspezifischen sowie fächerübergreifenden Potentialen zum Einsatz im schulischen Kontext zu formulieren. In diesem Beitrag werden die Potentiale für ein gelingendes Lehren und Lernen in der naturwissenschaftlichen Bildung von digitalen Zwillingen zusammenfassend betrachtet. Digitale Zwilling sind bereits in der industriellen Prozessentwicklung und -optimierung implementiert. Grundsätzlich nehmen die, in digitalen Zwillingen, repräsentierten Vernetzungsstrukturen zwischen digitaler und realer Welt und deren Potential in den Bereichen künstliche Intelligenz, maschinelles Lernen und Data-Mining-Prozessen einen wesentlichen Fokus ein. Um Bildungsperspektiven für den naturwissenschaftlichen Unterricht abzuleiten, werden die eingehenden und ausgehenden Datenstrukturen und deren Funktionsweisen in digitalen Zwillingen näher betrachtet. Der Beitrag thematisiert den Blick auf digitale Zwillinge als intelligente neue Bildungstechnologie in Lehr-Lern-Prozessen, welche auch im industriellen Sektor noch nicht an ihrem Entwicklungsendpunkt steht und vielfältige Anwendungspotentiale im Schulkontext, viele offene Forschungsfragen und Entwicklungspotentiale im Rahmen der Bildungsforschung bereithalten.

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“…In terms of educational technologies, Virtual Reality (VR) and Augmented Reality (AR) have been prominently discussed as pedagogical tools (Daniela, 2020;Sharifpour et al, 2022) underlining their usefulness in developing skills and immersive learning experiences, as well as the integration of such technologies into engineering education and manufacturing simulations Pizzuto et al, 2022). Of particular interest are the studies that adopt non-traditional or innovative approaches to Industry 4.0, seeking to integrate these new technologies with educational innovation (Cortes et al, 2020) as the incorporation of IoT devices in training medical (Al-Emran et al, 2020).…”

Section: Industry 40 and Educationmentioning

confidence: 99%

Exploring educational simulation platform features for addressing complexity in Industry 4.0: a qualitative analysis of insights from logistics experts

Pacheco-Velazquez,

Rodes-Paragarino,

Marquez-Uribe

2024

Front. Educ.

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IntroductionThis study explores the transformative impact of Industry 4.0 on industrial operations, emphasizing the integration of advanced technologies like AI, IoT, and Big Data Analytics to enhance process optimization, automation, and connectivity. Despite its potential for efficiency, Industry 4.0 introduces significant complexities, challenging existing operational and decision-making frameworks. Addressing these challenges, the research investigates the role of simulation platforms in logistics, seeking to identify their critical attributes for effective complexity management. It highlights the need for innovative tools in system evaluation, performance measurement, and skill development, aiming to equip the workforce with essential Industry 4.0 competencies. Through qualitative insights from logistics experts, the study aims to offer practical recommendations for educators and industry professionals, contributing to the design and implementation of educational simulations that align with the intricate demands of Industry 4.0 logistics.MethodsThis study employs a qualitative content analysis approach to develop an Industry 4.0-adapted logistics simulator, leveraging the Asteraceae framework for digital game co-design and pedagogical reflection. Data were collected from six industry and academia experts through semi-structured interviews, designed around the framework’s key steps to explore simulator design, decision-making, impact, and skill development. Utilizing convenience sampling, the research engaged participants with experience in educational logistics platforms and simulators. Interviews were conducted online, with ethical considerations including informed consent. Transcription used OpenAI’s API for accuracy, followed by manual review. The analysis combined qualitative content with frequency analysis, employing Atlas.ti software to identify and code key simulation features as informed by expert insights. This methodology underscores a comprehensive approach to understanding and innovating logistics education for Industry 4.0, aiming to equip learners with necessary competencies through targeted simulation tools.ResultsThe study’s findings emphasize the critical role of simulation tools in Industry 4.0 logistics for risk mitigation, operational planning, and decision-making. Experts pointed out the significant benefits of simulations in providing safe spaces for experimentation, especially valuable for SMEs with limited access to advanced technologies. They advocated for simulators to incorporate current technological and e-commerce trends, suggesting a customizable business model based on diverse logistics requirements. Key insights included the necessity for adaptable simulation architectures to handle various operational variables, the importance of integrating multidisciplinary competencies like data analytics and strategic management, and the role of performance metrics in evaluating simulations and logistics operations. The analysis revealed essential features for an educational logistics simulator, highlighting the importance of operational knowledge, predictive analytics, and the need for a comprehensive tool that integrates technology, strategy, operations, and data analysis. This approach aims to equip users with the skills necessary for navigating the complexities of modern logistics, promoting a deep understanding of systems thinking and complex reasoning skills.DiscussionThe discussion centers on the essential requirement for a multidisciplinary approach in creating an educational logistics simulator for Industry 4.0, emphasizing the need for technological adaptability and operational efficiency. It highlights the importance of integrating advanced technologies and collaborative paradigms to enhance logistics operations and improve decision-making processes. The utility of simulation-based learning as a pedagogical tool is acknowledged, with an emphasis on its role in developing complex thinking and practical skills relevant to the digital transformation of the logistics sector. The discussion suggests that educational simulations are poised to play a pivotal role in preparing the workforce for Industry 4.0 challenges by bridging technological advancements and pedagogical strategies. However, it also points to the limitations of the current study, such as its sampling method and regional focus, and calls for future research to explore broader applications and the integration of comprehensive strategies to ensure the educational simulator’s effectiveness and relevance in a global context.

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Digital Pyramid: an approach to relate industrial automation and digital twin concepts

Cited by 10 publications

References 14 publications

Design, Modeling and Implementation of Digital Twins

Design, Modeling and Implementation of Digital Twins

Digitale Zwillinge in der naturwissenschaftlichen Bildung

Exploring educational simulation platform features for addressing complexity in Industry 4.0: a qualitative analysis of insights from logistics experts

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