Typeset

Digital Platform Frameworks for Manufacturing Companies

Digital Platform Frameworks for Manufacturing Companies

A review
Marcel Rojahn ORCID Icon
In recent years, digital platforms have established themselves as a central concept in the IT field. Due to the wide variety of digital platforms available on the market, there is still a need for clear comparison with criteria to enable interested parties to select, change, operate and further develop these platforms. The following paper aims to contribute to the facilitation of this comparison by undertaking a systematic literature review of digital platform frameworks in the context of the Industrial Internet of Things (IIOT) for manufacturing companies and thus providing a basis for a number of potential ways to effectively compare current digital platforms and ecosystems.
Industry 4.0 Science | Volume 40 | 2024 | Edition 2 | Pages 8-15 | DOI 10.30844/I4SE.24.2.8
Spare Part Production of Vehicle Gearbox Bearings

Spare Part Production of Vehicle Gearbox Bearings

A method using additive manufacturing
Norbert Babel, Tobias Empl, Raimund Kreis ORCID Icon, Peter Roider
Spare parts for older products are often difficult to obtain or cannot be produced in an economically viable way using conventional manufacturing techniques. This article examines whether damping elements for gearbox bearings (in/for the automotive sector) can be manufactured from thermoplastic polyurethanes (TPU) with the same or compatible properties as the original part alternatively using additive manufacturing.
Industry 4.0 Science | Volume 40 | 2024 | Edition 2 | Pages 16-22
Energy Efficiency Through Intelligent Electricity Data Acquisition

Energy Efficiency Through Intelligent Electricity Data Acquisition

Wireless retrofit solution based on IoT technologies and open-source software for existing industrial buildings
Sergej Kreber, Kevin Kutzner, Dieter Uckelmann ORCID Icon
Facility managers for industrial properties are faced with the challenge of optimizing the energy efficiency of their facilities in the face of ever-increasing energy demand and rising energy costs. Digital processes that enable the comprehensive monitoring, analysis and control of energy demand offer an effective way to reduce costs, increase energy efficiency and make optimal use of resources. Based on IoT technologies and open-source software, a cost-effective, wireless and flexible retrofit solution for real-time energy data collection has been developed.
Industry 4.0 Science | Volume 40 | Edition 2 | Pages 87-93
Leveraging AI for Cost-Reduced Exhaust Gas Aftertreatment

Leveraging AI for Cost-Reduced Exhaust Gas Aftertreatment

Use of AI-based dosing systems to reduce nitrogen oxides in large diesel engines
Manuel Brehmer, Marc Schuler
The design of gear pumps causes gap flows, which counteract efforts to achieve exact dosing. However, due to the complex relationships between pressure, temperature, manufacturing tolerances and the material properties of the pumped medium, these gap flows cannot be reliably described in real time using physical equation systems. By using new algorithms and artificial neural networks, it was possible to solve this problem and replace a cost-intensive flow measurement method at the same time. This new approach has been tested on a pilot plant scale, and has already demonstrated that it can achieve the accuracy of a classic flow meter, while at the same time significantly decreasing the response time and increasing the application range of the dosing system.
Industry 4.0 Science | Volume 40 | 2024 | Edition 2 | Pages 72-79
Lean Empowerment in the Digital Ecosystem

Lean Empowerment in the Digital Ecosystem

Translating cultural values into technical requirements
Frank Bertagnolli ORCID Icon, Sabrina Karch ORCID Icon, Arndt Lüder ORCID Icon
With the advent of digitalization, prevailing paradigms – such as product centricity, face-to-face collaboration and hierarchical structures – are giving way to the vision of data-driven business models, digital, collaborative ecosystems and an agile, holacratic way of working in flat hierarchies and self-managing teams. Collaboration is made possible through the use of software solutions. In addition to adapted management concepts, the digital space also requires a digital cultural understanding on part of the companies involved. Lean empowerment is a pioneering approach to collaboration based on cultural values. In expert workshops, ideas were developed to explore how these values can be lived in a digital culture and thus in terms of global digital collaboration. This article presents concrete solutions from which requirements for digital collaboration and for implementation within IT structures and software solutions in particular can be derived.
Industry 4.0 Science | Volume 40 | 2024 | Edition 2 | Pages 32-39 | DOI 10.30844/I4SE.24.2.32
The Utopia of European Cybersecurity Certifications

The Utopia of European Cybersecurity Certifications

Alexander Lawall ORCID Icon, Jesus Luna Garcia
Interoperable automation can benefit cybersecurity certification processes that result from the EU Cybersecurity Act (e.g. EUCS) so that they represent less overhead for the stakeholders involved. The development of key standardization efforts involving relevant stakeholders (e.g. regulators) is needed to fully realize these benefits. EU projects like H2020 MEDINA, HEU COBALT and communities such as EUROSCAL are well on the way to achieving this goal. However, more practical experience is needed to make continuous certification with automation a reality.
Industry 4.0 Science | Volume 40 | 2024 | Edition 2 | Pages 48-55
secureAR – An AR Platform for Industrial Manufacturing

secureAR – An AR Platform for Industrial Manufacturing

Development and testing of an AR assistance system with consideration of cyber security
Frank-Peter Schiefelbein, Stefan Sigl
With its ability to integrate digital information into the real world, augmented reality (AR) is increasingly becoming a critical success factor when it comes to safe, efficient and human-centered manufacturing. However, the implementation of an AR project poses various challenges that can hinder its ability to succeed. A clear sequence of steps for implementing this technology is therefore essential.
Industry 4.0 Science | Volume 40 | 2024 | Edition 2 | Pages 64-71
Platform Business

Platform Business

Increasing sustainability with digital business models
Andrea Carolina Soto Ramirez ORCID Icon, Søren Salomo ORCID Icon
Platforms and business models based on them have been around for many years. However, the rapid development of information technology in recent years has greatly reduced the need for physical assets and infrastructure to enable value creation. Digitalization enables highly efficient interactions among platform participants. This lowers the barriers to accessing tangible and intangible goods, which in turn opens up opportunities to develop instruments that improve the sustainability of platform results.
Industry 4.0 Science | Volume 40 | 2024 | Edition 2 | Pages 80-86
Warehouse Inventory Detection with Airship Drones

Warehouse Inventory Detection with Airship Drones

(Semi-)autonomous aircraft for inventory and quality inspection of pallets in block storage facilities
Dmitrij Boger, Michael Freitag ORCID Icon, Britta Hilt, Michael Lütjen ORCID Icon, Benjamin Staar ORCID Icon
The complex dynamics of block warehouses pose major challenges to the manual stocktaking process. Frequent relocation of pallets, crates or pallet cages without fixed storage locations leads to a time-consuming and error-prone inventory process, wherein goods often have to be searched for and damages due to improper storage can occur. The use of (semi-)autonomous drones offers a promising solution to enable automated stocktaking, especially if these are appropriately equipped for optical goods detection.
Industry 4.0 Science | Volume 40 | 2024 | Edition 2 | Pages 56-63
Motion-Mining Compared to Traditional Lean Tools

Motion-Mining Compared to Traditional Lean Tools

Sensor-supported analysis of manual processes in manufacturing and logistics
Hendrik Appelhans, Christopher Borgmann, Carsten Feldmann
Motion-Mining® is a technology that uses motion sensors and pattern recognition to enable automated process mapping and analysis of manual work. This article evaluates the advantages and limitations of its use in manufacturing and logistics processes. To this end, Motion-Mining® is compared with traditional lean management tools used to analyze manual activities. Experiences derived from four use cases provide decision support for selecting the appropriate method for a specific use case.
Industry 4.0 Science | Volume 40 | Edition 2 | Pages 24-31
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