Logistics

Experiencing Digital Twins in Production and Logistics

Experiencing Digital Twins in Production and Logistics

The fischertechnik® Learning Factory 4.0 as a development platform for possible expansion stages
Jan Schickram, Tareq Albeesh, Deike Gliem ORCID Icon, Sigrid Wenzel ORCID Icon
The fischertechnik® Learning Factory 4.0 has proven to be a suitable experimental environment for testing digital twins. Depending on the targeted maturity stage, the functions of a digital twin range from status monitoring and forecasting to the operational control of production and logistics systems. To systematically classify these functions, this article presents a maturity model that serves as a framework for the development of a digital twin. Building on this, selected use cases are implemented in a test and development environment based on a system architecture with multi-layered logic structure. These initial implementations serve to highlight application purposes, relevant methods, and typical challenges and potentials in the transfer to real factory environments.
Industry 4.0 Science | Volume 42 | Edition 2 | Pages 30-37 | DOI 10.30844/I4SE.26.2.30
Adaptive In-Orbit Servicing of Altered Satellite Components

Adaptive In-Orbit Servicing of Altered Satellite Components

Adaptive gripper placement on altered components for servicing in-orbit satellites
Justus Rein ORCID Icon, Christian Plesker ORCID Icon, Adrian Reuther ORCID Icon, Hanyu Liu ORCID Icon, Benjamin Schleich ORCID Icon
In-orbit servicing of satellites presents several challenges as the satellite hardware is exposed to external influences throughout its life cycle. These factors wear down the components and cause changes to their physical structure. In such cases, the limits of simple dis- and reassembly steps may be reached, as the gripping surfaces are no longer present or suitable. This paper proposes an approach of an adaptive grip position estimation in a CubeSat disassembly process. The relevant components are identified using CAD models and a 3D camera. The gripping positions are determined based on the geometry of the gripper and the point cloud of the component.
Industry 4.0 Science | Volume 41 | Edition 6 | Pages 10-21 | DOI 10.30844/I4SE.25.6.10
“Entrepreneurial courage is the key ingredient”

“Entrepreneurial courage is the key ingredient”

Interview with Prof. Jan Wörner, Director of the Frankfurt Institute for Advanced Studies (FIAS)
Production is leaving Earth. As access to space becomes increasingly affordable and reliable, the idea of manufacturing in space is evolving from science fiction to a real industrial strategy. In this interview, Jan Wörner, who has headed not only the German Aerospace Center (DLR) but also the European Space Agency (ESA) for many years, talks about strategic opportunities and regulatory challenges.
Increasing Resilience in Logistics with IT

Increasing Resilience in Logistics with IT

Investigating supply chain risk management information systems
Alexander Baur, Jasmin Hauser, Dieter Uckelmann ORCID Icon
The blockage of the Suez Canal in 2021, caused by the accident involving the container ship Ever Given, clearly illustrates the need to design global supply chains in such a way that they can respond quickly to disruptions. In a volatile, uncertain, complex, and ambiguous (VUCA) environment, conventional logistics processes that focus on efficiency, and supply chain management methods in particular, are increasingly reaching their limits. Resilience, achieved through a combination of robustness and agility, is essential to ensure responsiveness. This article analyzes how risk management information systems (RMIS) can increase resilience. The analysis covers data availability, data transparency, modeling and simulation of risk scenarios, and the development of appropriate emergency action plans. Despite existing challenges in designing IT infrastructure, the measures mentioned have the potential to increase resilience in logistics.
Industry 4.0 Science | Volume 41 | Edition 4 | Pages 36-42
Requirements Analysis for Predictive Analytics in SCM

Requirements Analysis for Predictive Analytics in SCM

Decision support for research and practice
Iris Hausladen ORCID Icon, ABM Ali Hasanat
Predictive analytics opens up opportunities to improve decision-making in manifold areas, including in supply chain management (SCM). Yet, the complete realization of its potential requires the identification of the corresponding needs upfront. This paper provides a structured concept that guides through the complex and interdisciplinary endeavor of requirements analysis for predictive analytics in SCM. Due to the generic nature of this approach, it can be applied for any use case and be adapted or enhanced in case of need.
Industry 4.0 Science | Volume 41 | Edition 4 | Pages 86-92
Technologies for Assisting Manual Order Picking

Technologies for Assisting Manual Order Picking

From conventional pick-by systems to AI-driven manual picking assistance
Md Khalid Siddiqui ORCID Icon, Jonathan Kressel ORCID Icon, Jürgen Grinninger
Manual picking remains common due to the high initial cost of support systems. This paper reviews existing technologies, presents an exploratory vision-based prototype, and examines existing literature that explores how combining object detection with language systems could enhance manual workflows. The findings suggest a promising, low-cost direction for worker support in logistics.
Industry 4.0 Science | Volume 41 | Edition 4 | Pages 6-19 | DOI 10.30844/I4SE.25.4.6
Digital Twins for Production and Logistics Systems

Digital Twins for Production and Logistics Systems

Challenges and focus areas in implementation and use
Deike Gliem ORCID Icon, Nicolas Wittine ORCID Icon, Sigrid Wenzel ORCID Icon
For a successful implementation as well as sustainable use and maintenance of digital twins for production and logistics systems, it is necessary to identify relevant use cases and master the associated challenges. This paper analyzes scientific literature on common applications and challenges in the implementation of digital twins for the planning and operation of production and logistics systems. To confirm the practical relevance of the results, the results of an empirical survey have also been included. The findings are used to derive key focus areas for the successful implementation and long-term use of digital twins in production and logistics.
Industry 4.0 Science | Volume 41 | 2025 | Edition 3 | Pages 42-49 | DOI 10.30844/I4SE.25.3.42
Enabling the Future of Manufacturing with Digital Twins

Enabling the Future of Manufacturing with Digital Twins

Opportunities and obstacles
Javad Ghofrani, Darian Lemke, Tassilo Söldner
Digital twins connect physical and digital systems, furthering efficiency, enabling predictive maintenance, and allowing the production of more customized products. Despite these advantages, challenges such as high costs, data synchronization, and security risks hinder widespread adoption. This article explores the potential of digital twins and examines key barriers to integration and implementation, also considering some industrial applications including additive manufacturing as a relevant use case.
Industry 4.0 Science | Volume 41 | Edition 3 | Pages 72-81
Intelligent Load Carrier Management

Intelligent Load Carrier Management

AI-supported monitoring and reduction of losses in logistics
Dominik Augenstein, Lea Basler
Load carriers are essential for transporting manufactured parts in manufacturing companies. Despite their ‘simplicity’, they are usually expensive to purchase as they are manufactured expressly to fit purpose. While tracking methods such as GPS tracking can be used to prevent the loss of load carriers, this is associated with monitoring costs and presents challenges with regard to data protection as soon as the work performance of intralogistics employees is monitored. Assigning load carriers to designated clusters and monitoring these clusters provides an effective solution—without drawing conclusions about employee performance. Furthermore, artificial intelligence can optimize this approach whilst also deterring the theft of load carriers.
Industry 4.0 Science | Volume 41 | 2025 | Edition 2 | Pages 78-84
Boosting Competitiveness in Small Batch Production

Boosting Competitiveness in Small Batch Production

Scalable and flexible body-in-white production line with collaborative mobile robots
Walid Elleuch, Tadele Belay Tuli ORCID Icon, Martin Manns ORCID Icon
Due to the higher customization of products to customer groups and needs, body-in-white manufacturing industries are facing higher variant assembly at the later stages of the production line, thus increasing production costs per unit. Flexible production processes that involve flexible material flows, non-rigid manufacturing sequences, and the automatic reconfiguration of tools are regarded as the pillars of a resilient production system. This article presents a conceptual solution for flexible Body-in-White sheet metal production with autonomous collaborative robotic systems to make product costs affordable for a higher competitive advantage.
Industry 4.0 Science | Volume 41 | Edition 2 | Pages 60-67
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