Künstliche Intelligenz

Competence Assurance for the Verification and Validation of Simulation Models

Competence Assurance for the Verification and Validation of Simulation Models

Requirements for AI-supported assistance in production and logistics
Sigrid Wenzel ORCID Icon, Felix Özkul ORCID Icon, Robin Sutherland ORCID Icon
Can artificial intelligence be used to assess the validity and credibility of simulation models and data for production and logistics? And what requirements must AI assistance meet to effectively support experts in verification and validation while simultaneously safeguarding their competence? In an online survey, simulation experts were asked regarding their expectations and needs.
Industry 4.0 Science | Volume 42 | 2026 | Edition 5 | Pages 24-33 | DOI 10.30844/I4SE.26.5.3
Explaining AI in Industrial Production in an Accessible Way

Explaining AI in Industrial Production in an Accessible Way

Requirements for AI demonstrators to promote acceptance
Jennifer Link ORCID Icon, Markus Harlacher ORCID Icon, Colin Srebny, Sascha Stowasser ORCID Icon
Artificial intelligence (AI) offers a wide range of possibilities in industrial production, but it also presents challenges regarding employee acceptance. AI demonstrators are therefore of central importance, as they enable hands-on experience with AI. However, there has been a lack of systematically identified requirements for demonstrators that specifically promote acceptance and address negative emotions. Using a multi-stage research design, 69 requirements were identified, structured into functional requirements, quality requirements, and boundary conditions.
Industry 4.0 Science | Volume 42 | 2026 | Edition 5 | Pages 6-14 | DOI 10.30844/I4SE.26.5.1
Experiential Knowledge Powered by AI 

Experiential Knowledge Powered by AI 

Practical insights from industry
Martin Schmauder ORCID Icon, Gritt Ott ORCID Icon, Bianca Windisch
The use of experiential knowledge is a key success factor for companies. Based on four corporate case studies, this article analyzes the technical, organizational, and personnel challenges associated with the use of retrieval-augmented generation (RAG) systems. The results show that the success of such systems depends on the strategic development and maintenance of the knowledge base, as well as on employee engagement.
Industry 4.0 Science | Volume 42 | 2026 | Edition 5 | Pages 128-135 | DOI 10.30844/I4SE.26.5.15
Inclusive Work System Design

Inclusive Work System Design

Automation, standardization, and adaptability
Sebastian Schlund ORCID Icon
The design of inclusive work systems is gaining importance due to demographic change and the increasing digital penetration of value creation processes. While traditional ergonomic approaches are based primarily on percentile logic and thus address only a portion of the user population, the integration of digital technologies opens up new possibilities for the dynamic and individualized adaptation of work systems. This article presents a conceptual framework for inclusive work system design that integrates standardization, automation, and adaptability. Methodologically, the article is based on a conceptual analysis of existing approaches from ergonomics and human-centered design. The article makes a theoretical contribution to the systematization of inclusive work system design and identifies areas of focus for further research and industrial practice.
Industry 4.0 Science | Volume 42 | 2026 | Edition 5 | Pages 70-76 | DOI 10.30844/I4SE.26.5.8
Industry 4.0—Progress and Digitalization in Limbo

Industry 4.0—Progress and Digitalization in Limbo

Status of sustainable transformation and digitalization in production engineering
Christian Donhauser ORCID Icon, Daniel Riepl
Digitalization projects help users represent complex processes more simply and efficiently. However, there are many obstacles to implementation. Reluctance to implement these projects is palpable. This affects, among others, employers and employees, who may fall behind economically by waiting or avoiding change. These observations can be traced back to an overarching research question: What barriers and systemic challenges hinder sustainable transformation within the context of Industry 4.0, particularly when considering human labor in production engineering? What questions are the affected stakeholders asking? The primary goal of this long-term research project is to define these questions decisively and in detail in order to develop a conceptual foundation that integrates research, teaching, and technological development and thus combines the potential of digital technologies with the experiential and practical knowledge of production workers.
Industry 4.0 Science | Volume 42 | 2026 | Edition 3 | Pages 56-60
AI Colleagues?

AI Colleagues?

Competence requirements and training for AI use in industry
Swetlana Franken ORCID Icon
Artificial intelligence is fundamentally changing tasks, roles, and skills in (industrial) companies. Increasingly, it acts as a colleague, preparing decisions, supporting processes, and interacting with people. This article highlights key competence requirements for AI use in industry, presents an integrated competence model, and outlines practical strategies for the transfer of skills. The aim is to prepare companies and employees for humane, competence-oriented AI implementation that combines technological efficiency with human creativity and judgment.
Industry 4.0 Science | Volume 42 | 2026 | Edition 2 | Pages 78-86
Digital Competence Lab (DCL) for Speech Therapy

Digital Competence Lab (DCL) for Speech Therapy

Designing a learning platform to advance digital skills
Anika Thurmann ORCID Icon, Antonia Weirich ORCID Icon, Kerstin Bilda, Fiona Dörr ORCID Icon, Lars Tönges ORCID Icon
The digital transformation of healthcare results in lasting changes in speech therapy. Smart technologies and artificial intelligence (AI) are creating new opportunities to ensure therapy quality, address care bottlenecks, and actively involve patients in exercise processes. At the same time, these developments are expanding the role of speech therapists, who increasingly use digital systems as supportive tools in addition to their core therapeutic tasks. Based on a feasibility study of the AI-supported application ISi-Speech-Sprechen in a real-world setting of complex Parkinson's therapy (PKT), this article outlines the key challenges associated with implementing smart technologies.
Industry 4.0 Science | Volume 42 | 2026 | Edition 1 | Pages 110-118 | DOI 10.30844/I4SE.26.1.102
AI Implementation in Industrial Quality Control

AI Implementation in Industrial Quality Control

A design science approach bridging technical and human factors
Jens Pöppelbuß ORCID Icon, Kathrin Nauth ORCID Icon
Artificial intelligence (AI) offers significant potential to enhance industrial quality control, yet successful implementation requires careful consideration of ethical and human factors. This article examines how automated surface inspection systems can be deployed to augment human capabilities while ensuring ethical integration into workflows. Through design science research, twelve stakeholders from six organizations across three continents are interviewed and twelve sociotechnical design requirements are derived. These are organized into pre-implementation and implementation/operation phases, addressing human agency, employee participation, and responsible knowledge management. Key findings include the critical importance of meaningful employee participation during pre-implementation, and maintaining human agency through experiential learning, building on existing expertise. This research contributes to ethical AI workplace implementation by providing guidelines that preserve human ...
Industry 4.0 Science | Volume 42 | 2026 | Edition 1 | Pages 120-127 | DOI 10.30844/I4SE.26.1.112
Ideating Ethical AI Business Models

Ideating Ethical AI Business Models

A dual card approach for the ethical development of AI business models
Marie-Christin Barton ORCID Icon, Lisa Skrzyppek, Kathrin Nauth ORCID Icon, Jens Pöppelbuß ORCID Icon, Jürgen Mazarov
AI opens up entirely new forms of value creation, but most business model tools have not kept pace. They overlook both the strategic potential that AI holds and the ethical challenges that it introduces. This study introduces a dual-card toolkit that helps interdisciplinary teams design AI-enabled business models with built-in ethical reflection. The key insight: to harness AI responsibly, we must rethink how we innovate, starting from the business model itself.
Industry 4.0 Science | Volume 42 | Edition 1 | Pages 40-49 | DOI 10.30844/I4SE.26.1.38
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 | 2025 | Edition 6 | Pages 10-21 | DOI 10.30844/I4SE.25.6.10
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