knowledge management

Potentials, Premises, Perspectives

Potentials, Premises, Perspectives

Using LLMs to reinterpret corporate knowledge management
Vanessa Kuks ORCID Icon, Pius Finkel ORCID Icon, Peter Wurster ORCID Icon
Demographic change is exacerbating the shortage of labor and skilled workers in the manufacturing industry, making knowledge management an increasingly important issue in many companies. Collecting and preserving tacit knowledge poses a particular challenge. This study examines the extent to which large language models (LLMs) can provide meaningful support in knowledge gathering through expert interviews. Three experts test and evaluate a personalized chatbot that has been developed using ChatGPT-5. The results of the interview are promising, but the summary shows room for improvement.
Industry 4.0 Science | Volume 41 | Edition 6 | Pages 48-56 | DOI 10.30844/I4SE.25.6.48
Bridging Knowledge Gaps with GenAI in Industrial Maintenance

Bridging Knowledge Gaps with GenAI in Industrial Maintenance

Specific needs and contextualized solutions
Uta Wilkens ORCID Icon, Julian Polte ORCID Icon, Philipp Lelidis, Eckart Uhlmann ORCID Icon
The paper specifies the genAI support needs for industrial maintenance against the background of a sociotechnical systems perspective. Emphasizing two needs, accessing implicit operator knowledge and prioritizing complex regulatory knowledge, a multi-layer architecture is outlined for an AI-based context-sensitive maintenance assistance system (MAS). The main purpose is to bridge knowledge gaps with genAI if human expertise and human implicit knowledge are not available and to cope with sub-process-specific challenges of multiple regulations. The MAS facilitates access to technical knowledge, distributes expertise, and shares implicit knowledge of experienced operators across different layers of information processing. The approach goes beyond standardization and has a high potential to enhance organizational as well as individual resilience.
Industry 4.0 Science | Volume 41 | 2025 | Edition 5 | Pages 50-57 | DOI 10.30844/I4SE.25.5.50
I4S 4/2024: Learning Factories

I4S 4/2024: Learning Factories

Learning locations for SMEs, more resilience through knowledge transfer
The shortage of skilled labor is putting pressure on many manufacturing companies worldwide. While skilled labor is becoming scarcer in traditional industrialized economies, proper training is urgently needed in countries with high unemployment. But how to solve this challenge? Find out what makes learning factories so successful in this issue.
Optimizing Production Processes with AI-based Knowledge Transfer

Optimizing Production Processes with AI-based Knowledge Transfer

How AI can secure human-oriented, experiential knowledge in the KI-eeper project
Nicole Ottersböck, Holger Dander ORCID Icon, Christian Prange ORCID Icon
Implicit experiential knowledge will be lost through the retirement of the babyboomer generation. This know-how is difficult to capture and transfer. The KI_eeper project aims to develop an efficient AI-based system that automatically identifies and stores knowledge in the work process. The resulting knowledge base will provide assistance to all employees. The system will be designed in cooperation with employees according to their needs to gain high user acceptance.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 6 | Pages 51-54
Use Artificial Intelligence for Internal Videos

Use Artificial Intelligence for Internal Videos

Michael Kummer
Huge amounts of information are stored in the memory of every employee. How a product works, best practices in departments, customer-specific information, general market and competitive knowledge, etc. This expertise is a blind spot in most companies. So how do you make in-house know-how available? And in a time when many employees work remotely, in home offices, even across countries or continents?
Industrie 4.0 Management | Volume 38 | 2022 | Edition 5 | Pages 61-63
Digital Lifecycle Record – Building Block of Smart Maintenance

Digital Lifecycle Record - Building Block of Smart Maintenance

David Kiklhorn, Michael Wolny, Daniel Hefft, Jonas Eichholz, Alexander Kreyenborg
The digital transformation, especially the shift of maintenance to smart maintenance, contains a number of challenges. The management of data plays a significant role in this [1]. The use of sensor technology and devices for mobile data acquisition offers a variety of possibilities for quickly capturing large amounts of data, even in real time. In this context, however, there is also a need for tools that enable efficient data exchange and, at the same time, structured storage of large amounts of data. One of these tools is the digital lifecycle record, which has enormous potential for data-driven services thanks to its special features.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 5 | Pages 26-30
Smart Factory

Smart Factory

Reducing lead time in toolmaking by 90%
Christian Ludwig, Hilmar Gensert, Thomas Farrenkopf, Thomas Panske
Smart Factory is the vision of a production environment in which manufacturing plants and logistics systems organize themselves as far as possible without human intervention. The article describes a project, at the start of which none of the participants created a relation to “Smart Factory” or “Industry 4.0”. Rather, the objective was to drastically reduce the current delivery time of 6-8 weeks. The result is a completely digitized business process from order creation, product development, design, manufacturing as well as processing for “batch size 1” with a reduction in lead time to less than 10 %.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 4 | Pages 29-33 | DOI 10.30844/I40M_21-4_S29-33
Knowledge Management for Industry 4.0

Knowledge Management for Industry 4.0

Herausforderungen und Lösungsansätze
Klaus North, Ronald Maier
The digital interactions along the value chain pose new challenges for managing information and knowledge. The objectives of this article are to describe the changes in knowledge-based value creation induced by digitalisation and to derive fields of action for knowledge management for Industry 4.0. The “knowledge ladder 4.0” shows how digital technologies can transform strategic and operative knowledge management. Subsequently, we offer a framework for the knowledge-oriented design of dynamic digital organisations that consists of three layers of activities for the operation, reflection and design of knowledge management illustrated with leading questions and case examples in order to promote the productive, responsible and sustainable usage of digital technologies.
Industrie 4.0 Management | Volume 35 | 2019 | Edition 2 | Pages 7-12
Like Facebook on Steroids? Challenges and Good Practice Examples for a Successful Implementation of Enterprise Social Networks

Like Facebook on Steroids? Challenges and Good Practice Examples for a Successful Implementation of Enterprise Social Networks

Herausforderungen und Anwendungsempfehlungen zur betrieblichen Nutzung von sozialen Netzwerken
Jonathan Niehaus, Alfredo Virgillito
With the industrial internet the digitization of communication processes receives a new impulse. By application of social networks within firms, the collaboration of and knowledge transfer between workers can be supported and rationalized. This paper focuses on Enterprise Social Networks and discusses the challenges and opportunities when implementing these digital communication tools. On basis of a real world case study we illustrate some good practices.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 4 | Pages 21-24
Enabling Employees in “Industry 4.0”

Enabling Employees in “Industry 4.0”

Holistic Approach for the Acquisition and Management of Knowledge Concerning Employees and Processes
Niklas Kreggenfeld, Christopher Prinz ORCID Icon, Bernd Kuhlenkötter ORCID Icon
The increase of complexity in the field of production due to “Industrie 4.0” causes also a rapid increase of the complexity of tasks on the shopfloor level. Thus, efficient methods for the systematic identification of the competence deficits of the employees as well as new forms of knowledge management for an adequate administration of knowledge have to be established.
Industrie 4.0 Management | Volume 32 | 2016 | Edition 3 | Pages 31-34
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