Sustainability

Enabling Digital Trust in Green Hydrogen Markets

Enabling Digital Trust in Green Hydrogen Markets

Trust-Building Information Systems and Mechanisms
Johanna Voß, Jens Pöppelbuß ORCID Icon
Building a global hydrogen economy requires more than technology and investment; it requires trust. As information systems (IS) increasingly mediate collaboration among unfamiliar, distributed actors, the question of how trust can be deliberately built becomes critical. This study systematically maps how IS enable different types of trust and reveals how these mechanisms can support trusting collaboration in emerging hydrogen value chains.
Industry 4.0 Science | Volume 42 | 2026 | Edition 4 | Pages 82-90 | DOI 10.30844/I4SE.26.4.9
Classification of Digital Supply Chain Management Platforms

Classification of Digital Supply Chain Management Platforms

Review of existing classification approaches from a circular economy perspective
Sophia Botsch ORCID Icon, Eva Mante ORCID Icon, Marcel Papert ORCID Icon, Alexander Pflaum ORCID Icon
Assessing the impact of digital industrial platforms on the dynamics and resilience of supply chains requires clear classification of such platforms. This article examines the extent to which a current classification proposal from the field of supply chain management must be further developed in the context of digital platforms for implementing the circular economy (CE). The authors conclude that a fundamental revision is not necessary, as the digital CE platforms under consideration fit well into the existing classification system. However, new research questions arise regarding the distinction between digital service platforms and digital data-oriented platforms, as well as the link between the circular economy and supply chain management—particularly in connection with supply chain control towers, which are becoming increasingly established in supply chain management practice.
Industry 4.0 Science | Volume 42 | 2026 | Edition 4 | Pages 62-70 | DOI 10.30844/I4SE.26.4.7
Digital Twins for Emission Reduction

Digital Twins for Emission Reduction

Ex-ante case study on a pump test bench in industrial production
Felix Bischoff, Ingela Tietze ORCID Icon, Peter Hertweck, Nina van Hasz
Digital twins are frequently referred to as a promising approach for reducing greenhouse gas (GHG) emissions in industrial production; however, robust empirical evidence of their benefits under real-world conditions is largely lacking. In this case study, the emission reduction potential of a digital twin—as a conceptually described target system—is quantified ex-ante via the example of a test bench for hydraulic pumps. To this end, the GHG emissions of the original test plan for the year 2025 are determined based on actual measured energy consumption of the tested pumps and time-resolved grid electricity emission intensities. This is followed by a rule-based rescheduling, in which energy-intensive test processes are shifted to time intervals with lower emissions. The rescheduling takes operational constraints into account so that processes and equipment remain unchanged. The savings potential is determined by comparing the GHG emissions of the reference and the optimized case.
Industry 4.0 Science | Volume 42 | 2026 | Edition 3 | Pages 16-24 | DOI 10.30844/I4SE.26.3.2
Has the Time Come for an Energy Revolution in Intralogistics?

Has the Time Come for an Energy Revolution in Intralogistics?

The current status of hydrogen fuel cell-powered MHE
Joseph W. Dörmann
Hydrogen fuel cells promise to be a sustainable alternative to fossil fuel or battery-electric material handling equipment (MHE) in various production or warehouse contexts. Short refuelling times, an absence of carbon emissions, and constant power input put fuel cell-powered MHE at an advantage in high-intensity work environments. However, various barriers to the adoption of fuel cells remain, including considerations surrounding cost and efficiency.
Industry 4.0 Science | Volume 41 | 2025 | Edition 6 | Pages 74-80
Loam Construction and Wooden Shelving

Loam Construction and Wooden Shelving

A contribution to sustainability in warehouse logistics
Viviano De Giacomo ORCID Icon, Nathalie Fritsch ORCID Icon, Jakob Kennert ORCID Icon, Dieter Uckelmann ORCID Icon
This study examines the contribution of natural building materials, in particular loam and wood, to the sustainable development of logistics infrastructure, assessing ecological, economic, and technical dimensions across the entire life cycle. Potentials, restrictions, and supportive framework conditions are identified based on literature analyses and expert interviews. Wood proves to be technically mature and ecologically advantageous, especially in high rack construction, while loam offers high potential for energy- and resource-efficient construction. The study concludes with recommendations for research, policy, and practice to establish circular construction methods in logistics.
Industry 4.0 Science | Volume 41 | Edition 6 | Pages 82-89
The Bias of “Instructional Systems for the Disabled”

The Bias of “Instructional Systems for the Disabled”

Ethnographic insights from deploying augmented reality in a sheltered workshop
David Kostolani ORCID Icon, Annemarie Ploss, Sebastian Schlund ORCID Icon
The rehumanization of industrial work has emerged as a key focus in Industry 4.0 research, emphasizing the empowerment of human workers amidst advancing automation. Within this re-search, supporting workers with disabilities through digital assistance technologies serves as a prime example of a human-centric approach to industrial engineering. These technologies often claim to enhance productivity, which aims to promote the integration of workers with disabili-ties in industrial roles. But can they genuinely improve their work experience? This ethnograph-ic study presents insights from two years of developing and deploying augmented reality in a sheltered woodworking workshop. Over this period, we engaged in conversations and facilitat-ed over 30 technology sessions with workers with diverse disabilities. Our experiences chal-lenge the narrative of industrial research, in particular with digital instructional systems serving as “enabler technology” to help them work “better.” ...
Industry 4.0 Science | Volume 41 | 2025 | Edition 5 | Pages 102-110 | DOI 10.30844/I4SE.25.5.102
Machine Learning to Promote Sustainability 

Machine Learning to Promote Sustainability 

Company analysis based on expert interviews
Matthias Weigold
This article outlines the results of ten expert interviews on the use of machine learning to promote corporate sustainability and then compares them with relevant literature. The study shows that economic factors drive the use of machine learning, the introduction of which is initiated by both top management and specialist departments. However, grounded strategies for implementing machine learning are rarely available and use cases are often based on supervised learning. The environmental impact (the reduction of emissions, for example) outweighs the social impact, though quantification is difficult. Additionally, a lack of trust, expertise, and communication hinders the adoption of machine learning, while some technical challenges regarding data requirements also pose problems.
Industry 4.0 Science | Volume 41 | Edition 4 | Pages 44-51
Real-Time Monitoring of the Carbon Footprint for SMEs

Real-Time Monitoring of the Carbon Footprint for SMEs

Sustainability in real time — from operation to finished products
Henning Strauß ORCID Icon, Julian Sasse ORCID Icon
Although SMEs are not directly affected by the statutory reporting obligations for carbon accounting, as suppliers they are obliged to meet the requirements of sustainability reporting. In addition to a holistic life cycle analysis, this requires a high-quality database within production in order to determine the specific CO₂ footprint. A central element is the implementation of a Machine Carbon Footprint (MCF). This article aims to develop and implement an MCF focusing on its applicability for SMEs. For this purpose, data is recorded and visualized in real time on a machine tool. The measurement data is then processed, stored and visualized using open-source low-code platforms. Real-time data flows enable the precise determination of the production-specific carbon footprint and, in conjunction with order data, the Product Carbon Footprint.
Industry 4.0 Science | Volume 41 | Edition 3 | Pages 102-109
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
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
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