Digitalisierung

Competence Needs for Hybridization

Competence Needs for Hybridization

An Approach to Identifying Competency Gaps and Need-Based Competency Development for Hybrid Business Models
Nicole Ottersböck, Sascha Stowasser, i
Digitalization and the possibility to use big data give companies the opportunity to establish hybrid business models. This enables them to offer customers smart services in addition to their physical products, create more value and strengthen their competitiveness. The hybridization goes along with new competence requirements, which need to be shaped. In the AnGeWaNt project, hybrid business models were developed and implemented in three companies. This article describes the approach to analyze new competence requirements and how to build up new skills for a successful hybridization
Industrie 4.0 Management | Volume 38 | 2022 | Edition 2 | Pages 49-52
Digitalized Industry and Sustainability

Digitalized Industry and Sustainability

Between Synergy and Dissonance
Frieder Schmelzle, Stefanie Kunkel, Marcel Matthess, Grischa Beier
A considerable part of global greenhouse gas emissions is caused in the industrial sector. Its digitialization is often seen as a means to increase sustainability. At the same time, ecological and social risks emerge. Their exploration is still in its infancy, however, previous findings point out multiple challenges. These must be conceptually taken into account in order to realize a sustainable industry 4.0. Building on a literature analysis, the following contribution presents current developments in research, industry, and policy. We shed light on a number of selected approaches, which aim at a sustainable industry 4.0. Finally, practical design options are outlined.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 1 | Pages 7-11 | DOI 10.30844/I40M_22-1_7-11
Requirements for the Use of Digitization and AI

Requirements for the Use of Digitization and AI

Applications for increasing energy efficiency
Dennis Bode, Henry Ekwaro-Osire, Klaus-Dieter Thoben ORCID Icon
Innovative digital and AI solutions for more energy-efficient production can decisively contribute to the environmental impact and competitiveness of companies, especially in the manufacturing industry. Requirements for the functionality and implementation of these solutions are complex and diverse; multiple stakeholders need to be addressed when eliciting requirements and various technology and business aspects have to be considered. This article presents a procedure for requirements elicitation for energy efficiency digitalization and AI projects.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 1 | Pages 17-22 | DOI 10.30844/I40M_22-1_17-22
Sustainable Recycling of EV Traction Batteries

Sustainable Recycling of EV Traction Batteries

Christoph Herrmann, Mark Mennenga, Alexander Kaluza, Bernd Friedrich, Elinor Rombach, Alexander Michaelis, Mareike Partsch, Constantin Wolf
In the course of the shift to electromobility, the use of battery cells as energy storage is facing exponential growth. The goal in research and industry is to design the entire life cycle of these battery cells in the light of global sustainability goals and to ensure the necessary supply of raw materials. In this context, the establishment of efficient recycling technologies plays a central role. In particular, there is a need for research into the further development of process routes according to technological, ecological, economic and social criteria. The competence cluster Recycling & Green Battery (greenBatt) addresses these challenges in 15 research projects. This article presents overarching solution approaches and project highlights.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 1 | Pages 12-16 | DOI 10.30844/I40M_22-1_12-16
Digital Sustainability Management in Companies

Digital Sustainability Management in Companies

A Service-Oriented Approach to Develop a Platform for Data-Driven Sustainability Management
Justus von Geibler ORCID Icon, Julia Brandt, Lara Waltersmann, Robert Miehe, Ralf Tesch
The digitalization in sustainability management and the creation of a consistent database for sustainability data can significantly support companies in meeting increasing sustainability requirements and transparency regarding the sustainability performance. This paper presents a service-oriented approach for the development of a platform for data-driven sustainability management in manufacturing companies.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 1 | Pages 45-47 | DOI 10.30844/I40M_22-1_45-47
Ready for Industrie 4.0?

Ready for Industrie 4.0?

Prerequisites for successful digitalization in production
Günther Schuh ORCID Icon, Andreas Gützlaff, Matthias Schmidhuber, Judith Fulterer, Max-Ferdinand Stroh, Jan Hicking
Despite a strong media presence and proven potential benefits, Industrie 4.0 is not yet established in many companies. Industry 4.0 projects often remain in a prototype status and do not deliver long-term added value. The solution is an integrated digital system landscape consisting of a connected, digital infrastructure and a business organization oriented towards Industrie 4.0. Through a four-step approach, this paper presents the foundations that need to be created to enable scalable solutions and realize long-term benefits.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 1 | Pages 61-65
Ready for Artificial Intelligence?

Ready for Artificial Intelligence?

Recommendations for the AI transformation for small and mid-sized enterprises
Ralf Klinkenberg, Philipp Schlunder
Artificial intelligence (AI) is the next stage in the digitalization of the economy. The technology also offers great potential for small and mediusized enterprises (SMEs). However, many SMEs are still reluctant to introduce AI and are only at the beginning of digitization: only around one fifth of all SMEs in Germany have thoroughly digitized their own processes and departments. What does this mean for the use of AI in companies? What steps should businesses take now to take advantage of the opportunities AI offers? And what stumbling blocks should be avoided? This article presents practical implementation concepts for companies with different levels of digital maturity and AI deployment capabilities and shows the range of potential benefits of AI applications in different industries and with different value creation architectures in medium-sized companies.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 6 | Pages 62-66
Sustainable Problem Solving in Digitized Processes

Sustainable Problem Solving in Digitized Processes

Lean-Management-Umsetzung in der Logistik mittels datengestützter Prozessabsicherung
Nico Hilgert, Frank Bertagnolli ORCID Icon
In lean management implementations, processes are improved and causes of problems are sustainably eliminated. However, in areas with a lot of data, such as logistics, root cause analysis on the shopfloor becomes confusing and complicated. Supporting application systems can help with analysis and shopfloor management. Using the example of supply logistics in the automotive industry, a simple digital solution is demonstrated that creates transparency, saves time and contributes to sustainable problem solving.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 5 | Pages 31-34 | DOI 10.30844/I40M_21-5_S31-34
Selection Criteria for IoT Platforms

Selection Criteria for IoT Platforms

Fundierte Auswahl einer passenden IoT-Plattform auf Basis häufig verwendeter Kriterien
Lukas Bruder, Dirk A. Neumayer, Richard Neumayer, Theo Lutz ORCID Icon
IoT-Platforms are a key element for interconnecting physical objects and providing data for digital twins which represent such objects. The market for IoT platforms has grown massively in recent years. With now more than 600 providers, selecting the “right” platform for a company is no longer an easy task. This article supports companies in the selection process by providing an overview on common functionalities of IoT platforms and criteria for evaluating IoT platforms.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 4 | Pages 55-58
Exchanging Data Between Industrial Companies − Smart Factories Use a Cloud-Based Common Data Environment as their Central Information Hub

Exchanging Data Between Industrial Companies − Smart Factories Use a Cloud-Based Common Data Environment as their Central Information Hub

Cloudbasiertes Common Data Environment als zentraler Informationshub in der Smart Factory
Andreas Dangl
Right now, there’s virtually no single issue impacting the mechanical and plant engineering sector as profoundly as that of the “smart factory.” In fact, according to an industry survey conducted in 2019 [1], as many as 68 percent of the respondents reported that they had already launched initial smart factory initiatives. According to the Capgemini study “Smart Factories @ Scale” [2], by the end of 2019, a third of the factories had already been transformed into intelligent factories. This article presents insight into how leveraging the advantages of a cloud-based solution can ensure that the flow of information within a network of smart factories can be managed effectively.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 4 | Pages 63-66
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