digitaler Zwilling

Open-Source and Cost-Effective Digital Twin

Open-Source and Cost-Effective Digital Twin

A case study with two weeks to succeed
Shantall Cisneros Saldana ORCID Icon, Sonali Pratap, Parth Punekar, Sampat Acharya, Heike Markus ORCID Icon
Digital Twin (DT) adoption remains a challenge due to high costs, complexity and lack of skills. This study proposes a cost-effective, TRL 5-validated DT model that can be built using open-source and office suite tools within just two weeks. Integrating real-time sensor data, predictive analytics, anomaly detection and notification, the model improves efficiency and sustainability in agriculture. Even with cloud service constraints, the system delivers a 7.76% average relative error and rapid, automated notifications. The findings show how open-source in combination with common commercial tools technologies can make advanced digital tools accessible to all, creating scalable, human-centered, and affordable solutions in line with Industry 5.0 principles.
Industry 4.0 Science | Volume 41 | Edition 3 | Pages 62-68 | DOI 10.30844/I4SE.25.3.62
I4S 2/2025: The Future of Production with AI, Cobots and Virtual Worlds

I4S 2/2025: The Future of Production with AI, Cobots and Virtual Worlds

Technology needs innovative, value-adding business models
Artificial intelligence, collaborative robotics, and virtual worlds, such as the metaverse, are fueling visions for new forms of industrial value creation. However, innovation alone is not enough—given that these technologies only develop their full potential through intelligent business models. How can companies efficiently integrate AI-supported automation, cobots and digital twins into their processes?
Digital Twins Using Semantic Modeling and AI

Digital Twins Using Semantic Modeling and AI

Self-learning development and simulation of industrial production facilities
Wolfram Höpken ORCID Icon, Ralf Stetter ORCID Icon, Markus Pfeil ORCID Icon, Thomas Bayer ORCID Icon, Bernd Michelberger, Markus Till, Timo Schuchter, Alexander Lohr
The AI-driven, self-learning digital twin continuously adapts to real system behavior, ensuring an optimal representation of the production process. A comprehensive semantic model serves as the foundation for advanced artificial intelligence (AI) approaches. Insights derived from AI methods are integrated into this model, enhancing the interpretability and explainability of AI systems. Techniques from the field of eXplainable AI (XAI) facilitate the automated description of AI models and their findings, as well as the development of self-explanatory models.
Industry 4.0 Science | Volume 41 | Edition 2 | Pages 30-36
Assembly in Transition

Assembly in Transition

Empirical results of digitalization
Mathias König ORCID Icon, Herwig Winkler ORCID Icon
Assembly is an important part of industrial production and is also characterized by a high proportion of manual work. Manufacturing companies have an intrinsic interest in increasing personnel productivity and preventing unit labor costs from rising. Many thus hope to gain economic benefits by implementing digitalization projects. The potential of digitalization in assembly must be exploited to achieve these goals.
Industry 4.0 Science | Volume 41 | 2025 | Edition 1 | Pages 42-49
The Key to Successful Digitalization

The Key to Successful Digitalization

Development, implementation and benefits of digital twins in Industry 4.0
Andreas Bayha ORCID Icon, Sönke Knoch ORCID Icon, Dirk Schöttke ORCID Icon
The success of technologies depends not only on their innovative strength and acceptance, but also on their management. Decision-makers evaluate factors like technical framework conditions and organizational requirements, with the demand for flexibility adding to the complexity. Industry 4.0 addresses this with networking, transparency and decentralized decisions. Digital twins, which can be implemented with open source software, play a key role.
Industry 4.0 Science | Volume 40 | Edition 4 | Pages 42-49
Digital Twin and Vertical Integration

Digital Twin and Vertical Integration

Support for sustainability concepts in production processes
Ute Dietrich
Establishing “smart” production processes that are focused on sustainability and based on aggregated data requires a great deal of exchange at various levels. The vertical integration of different production components provides companies with an important basis for achieving their sustainability goals. Digital twins can play a decisive role in driving this process forward.
Industry 4.0 Science | Volume 40 | 2024 | Edition 3 | Pages 67-72
Potentials and Application of the Industrial Metaverse

Potentials and Application of the Industrial Metaverse

Convergence from simulation to reality
Oliver Petrovic, Yannick Dassen, Christian Brecher
This paper deals with the concept of the Industrial Metaverse and its potential impact on the manufacturing industry. First, the possibilities of the Industrial Metaverse are explained in general and then possible resulting functionalities for production technology along the life cycle are presented. For the two topics "Synthetic Data Generation" and "Virtual Qualification" the implications of the Industrial Metaverse are considered more concretely.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 27-32 | DOI 10.30844/IM_23-5_27-32
Vom Energiedatenmanagement zum Digitalen Zwilling

Vom Energiedatenmanagement zum Digitalen Zwilling

Vereinfachte Modellierung eines Digitalen Zwillings mithilfe von Energiedaten
Alexander Blinn, Henrik te Heesen, Joachim Brinkmann, Julius Herzog
Bedingt durch globale Entwicklungen hinsichtlich der Preise und Versorgungssicherheit im Energiesektor stehen besonders energieintensive Unternehmen vor großen Herausforderungen. Zusätzlich fordern Kunden mehr Informationen über Energiekennzahlen und CO₂-Emissionen sowie ressourcenschonendere Prozesse. Mit einer energiedatenbasierten Simulationsmethode werden die Ressourceninformationen direkt aus dem Energiedatenmanagementsystem (EDMS) extrahiert und weiterverarbeitet. Hierbei werden sowohl aktuelle als auch stetig aktualisierte historische Daten verwendet, die automatisiert abgeglichen werden. Die digitale Abbildung der vorhandenen Prozesse ist lediglich auf Seiten der Energiedaten notwendig, ohne die technischen Prozesse in ihrer Gänze analysieren zu müssen. Mit dem so erstellten energetischen digitalen Schatten lassen sich Energiebedarfe für bevorstehende Produktionen und Produkte simulieren und können durch automatisierte Vorschläge in der Produktionsplanung positiv ...
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 33-36 | DOI 10.30844/IM_23-5_33-36
Bakery 4.0

Bakery 4.0

Development of an IoT framework for the automatic collection of machine, process data in medium-sized bakery operations
Abderrahim Ait Alla ORCID Icon, Frida Köning, Heiner Alsen, Joshua Coordes, Michael Freitag ORCID Icon
While the digital world has already made its way into many other production areas, the bakery industry has so far benefited little from these technological developments. This is because many baking processes are manually controlled and rely on expert knowledge. In addition, the process data from the machines is still not automatically captured via sensors. This paper describes a procedure for digitizing baking processes by developing an IoT framework consisting of an IoT device including measurement methods, an edge gateway, and a simulation-based solution for process optimization.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 3 | Pages 36-40
Digital Twins for Circular Economy

Digital Twins for Circular Economy

Enabling Decision Support for R-Strategies
Janine Mügge, Inka Rebekka Hahn, Theresa Riedelsheimer ORCID Icon, Johannes Chatzis
Digital twins (DT) for circular economy (CE) offer a promising approach as part of digital data ecosystems for more sustainable value creation. By mapping and analyzing product, component and material specific data along the li- fecycle, it is possible to address current challenges such as climate change and resource scarcity. Within Catena-X, specific solutions based on this cross-company exchanged data and information are developed. Here, the “R-Strategy Assistant” is presented. It is an application, which identifies the best CE-Strategy based on DT data at the end of a vehicle's life.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 6 | Pages 42-46 | DOI 10.30844/IM_22-6_33-36
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