97 research outputs found
Using Functional Blocks for Rolling Stock Troubleshooting: Sequential Augmented Reality Assistant (SARA)
No full textMaintenance and troubleshooting contribute to the overall economic efficiency of rolling stock throughout its lifecycle, yet these activities are resource-intensive and incur significant costs. In the era of Industry 4.0 implementation, the escalating complexity of rolling stock poses challenges in troubleshooting and maintenance decision-making. Recognizing this, there is a pressing need for a structured solution that empowers maintenance operators with tools for effective organization, analysis, and real-time presentation of rolling stock system failures, facilitating streamlined troubleshooting and maintenance guidance. Functional blocks, providing systematic structuring of processes, and Augmented Reality (AR), offering enhanced visualization and decision support, emerge as solutions to navigate and streamline these challenges in the evolving industrial landscape. The intricacies of existing fault-diagnosing systems, particularly interconnected transmission of functional blocks for troubleshooting and AR integration, lack detailed explanation, hindering effective solutions. To address these challenges, this work leverages AR for troubleshooting rolling stock failures, introducing functional blocks to 1) collect maintenance and fault data, 2) integrate maintenance information based on failure diagnostics and maintenance patterns, and 3) deliver this information to maintenance operators through AR. The developed Sequential Augmented Reality Assist (SARA) method, demonstrates the sequential implementation of AR troubleshooting functional blocks in an industrial context, providing a systematic solution to the complexities involved
Let’s augment the future together!:Augmented reality troubleshooting support for IT/OT rolling stock failures
Full text linkThe railway industry is moving to a socio-technological system that relies on computer-controlled and human-machine interfaces. Opportunities arise for creating new services and commercial business cases by using technological innovations and traffic management systems. The convergence of Information Technology (IT) with Operational Technology (OT) is critical for cost-effective and reliable railway operations. However, this convergence introduces complexities, leading to more intricate rolling stock system failures. Hence, operators necessitate assistance in their troubleshooting and maintenance strategy to simplify the decision-making and action-taking processes. Augmented Reality (AR) emerges as a pivotal tool for troubleshooting within this context. AR enhances the operator’s ability to visualize, contextualize, and understand complex data by overlaying real-time and virtual information onto physical objects. AR supports the identification of IT/OT rolling stock system failures, offers troubleshooting directions, and streamlines maintenance procedures, ultimately enhancing decision-making and action-taking processes. This thesis investigates how AR can support operators in navigating troubleshooting and maintenance challenges posed by IT/OT rolling stock system failures in the railway industry
AR-Supported Knowledge Transfer: Motion Tracking and Process Visualization for Tacit Knowledge Capturing
Full text linkImplizites Wissen spielt in der industriellen Instandhaltung eine zentrale Rolle: Erfahrungswissen bleibt oft undokumentiert und lässt sich mit klassischen Schulungsmethoden nur schwer weitergeben. Diese Arbeit untersucht, wie AR die Externalisierung impliziten Wissens in Instandhaltungsaufgaben unterstützen kann, um Wissenskontinuität, -transfer und -erhalt zu verbessern.Ausgehend von einem Design-Science-Research-Ansatz identifiziert eine systematische Literaturrecherche zentrale Hürden der Wissenserfassung. Eine integrative Literaturübersicht bündelt und ordnet sechs für die Instandhaltung relevante Typen impliziten Wissens: (1) motorische Fertigkeiten und Werkzeugführung, (2) Troubleshooting-Know-how, (3) kollaborative Routinen, (4) kontextabhängige Anpassung, (5) pragmatische Abkürzungen und (6) Sicherheitsbewusstsein sowie Risikobeurteilung. Die Einordnung erfolgt entlang von Collins’ Taxonomie (somatisch, relational, kollektiv) und nach Wissensebene (individuell vs. Gruppe).Darauf aufbauend wird ein kompaktes konzeptionelles Modell vorgestellt, das die AR-gestützte Erfassung und Weitergabe über diese Kategorien hinweg operationalisiert. Zur Evaluierung entstand eine AR-basierte PoC Demo auf Basis eines BPMN-Prozessmodells in einem Wasserfallvorgehen, der Bewegungserfassung, Videoaufzeichnung und Entscheidungsabfragen in den Erfassungsablauf integriert.In einer praxisnahen Fallstudie wechselte ein erfahrener Fahrradmechaniker den Schlauch eines Reifens. Dabei wurden elf bislang undokumentierte implizite Hinweise erfasst, die sich auf acht der neun Prozessschritte verteilen. Das bestehende Handbuch ließ sich dadurch um konkrete, handlungsnahe Einsichten ergänzen, ohne die ursprüngliche Abfolge zu verändern. Ein kontrollierter A/B-Test mit zehn unerfahrenen Probanden zeigte, dass die AR-basierte Anleitung die papiergebundene Instruktionen deutlich übertrifft: schnellere Aufgabenerledigung, keine Fehler, signifikant höhere Bewertungen in Kategorien wie Benutzerfreundlichkeit, Selbstvertrauen und Zufriedenheit sowie geringere kognitive Belastung. Halbstrukturierte Interviews stützten diese Ergebnisse und belegten eine klare Präferenz für AR-Unterstützung.In Summe verdeutlichen die Resultate, wie AR implizites Instandhaltungswissen in explizite, schrittverankerte Handlungsanleitungen überführt und das mit messbaren Verbesserungen beim Wissenstransfer, geringeren Fehlern und effizienterer Ausführung.Tacit knowledge plays a critical role in industrial maintenance, where experiential expertise often remains undocumented and difficult to transfer through traditional training methods. This thesis investigates how AR can mediate the externalization of tacit knowledge in industrial maintenance tasks to enhance knowledge continuity, transfer, and retention.Following a Design Science Research approach, a systematic literature review identified key challenges in tacit knowledge capture, while an integrative literature review identified and categorized six maintenance-relevant tacit knowledge types: (1) motor skills and tool handling, (2) troubleshooting know-how, (3) collaborative routines, (4) contextual adaptation, (5) practical shortcuts, and (6) safety awareness and risk assessment. These types are categorized according to Collins's taxonomy (somatic, relational, collective) and knowledge level (individual vs. group). On this basis, a concise conceptual model is introduced that operationalizes AR-mediated capture and transfer across these tacit knowledge categories, leveraging motion tracking, video documentation, and decision prompts. To validate the conceptual model, a case study was conducted in which an AR-based PoC Demo was developed based on a BPMN process design using a Waterfall approach, integrating motion tracking, video recording, and decision prompts into the capture workflow. In a maintenance-focused case study, an expert bicycle mechanic performed an inner-tube replacement, during which 11 previously undocumented tacit cues were captured across eight of nine procedural steps. This enriched the existing maintenance manual by embedding actionable insights without altering the original sequence. Controlled A/B testing with ten novices demonstrated that AR-delivered maintenance guidance outperformed traditional paper-based instructions, leading to faster task completion, elimination of errors, and significantly higher usability, confidence, and satisfaction ratings, while reducing cognitive workload. Semi-structured interviews reinforced these findings, with consistent user preference for AR support. The results highlight how AR can externalize tacit maintenance expertise, transforming it into explicit, step-anchored guidance that enhances skill transfer, reduces errors, and supports more efficient maintenance execution
An ontological framework for AR-enhanced maintenance management
No full textThis paper presents an ontology design framework that integrates opportunistic maintenance (OM) strategies, Stackelberg game theory models, Nash equilibrium concepts, and augmented reality (AR) to enhance decision-making, information visualization and contextualization in industrial settings. Traditional OM approaches often lack real-time, context-aware decision support, efficient resource allocation, and multi-agent collaboration, essential for dynamic optimization strategies. Integrating Stackelberg game theory models into OM enhances resource allocation and scheduling through hierarchical decision-making, allowing a leader-follower to optimally distribute resources while providing data-rich visualization and supporting adaptive, strategic planning in maintenance management. In dynamic multi-agent environments with multiple stakeholders, achieving Nash equilibrium leads to stable and efficient resource allocation, as no participant can unilaterally improve their outcome without impacting others. By incorporating Stackelberg game dynamics, Nash equilibrium concepts, and AR, the conceptual framework facilitates structured strategic planning, balancing leadership-driven optimization with equilibrium-based stability in decision-making and visualization. Evaluation of this ontology is proposed through a case study in a laboratory setting. The proposed ontology serves as a knowledge base for improving decision-making and provides a replicable framework for future advancements in industrial maintenance management by enabling the integration of emerging technologies, such as foundation models and large language models (LLMs), to refine maintenance strategies
Gender literary analysis of novel Němci by Czech author Jakuba Katalpa focusing on the concepts motherhood and parenthood
No full textIn the diploma thesis Gender Literary Analysis of the novel Němci by Jakuba Katalpa focusing on the motherhood and the parenthood is a gender literary analysis of the novel Němci by the Czech writer Jakuba Katalpa. The thesis focuses on the motherhood, fatherhood, respectively parenthood and how are these phenomenon established within the concrete society: as essentialist, that means biologically, versus the constructivist, therefore socially constructed paradigm. In my thesis I use qualitative interpretative analysis with aspects of discourse analysis and feminist literary theory. Using gender as a analytical cathegory as a methodological category, I try to find and uncover new interpretations and meanings of the book Němci and try to find alternative interpretations of plot and characters. Methodological-theoretical part on the basis of literature introduces the basic terms in use (gender, patriarchy, literary canon, feminism, feminist literary theory), with the help of several writers and authors (Terry Eagleton, Pam Morris, Elaine Showalter). The next part of the thesis pays attention to the concepts of motherhood (Zuzana Kiczková, Sara Ruddick, Elisabeth Badinter, Hana Hašková) and fatherhood (R. W. Connell, Ann Oakley, Elisabeth Badinter). I use the method of so- called resistant reading..
Augmented reality-enabled knowledge management in industrial maintenance: the DILEAF framework
No full textEffective maintenance in industrial operations relies on efficient management of task-critical knowledge, particularly in dynamic and unpredictable environments. Traditional knowledge management (KM) approaches face challenges in handling fragmented data, delivering procedural guidance, and adapting to evolving operational demands. To address these limitations, this study introduces the Data, Information, Learning, Engagement, Application, Feedback (DILEAF) framework, a structured KM model that integrates augmented reality (AR) as a digital enabler for improving knowledge capture, transfer, and application in industrial maintenance. By leveraging AR's capabilities in real-time visualisation, interactive procedural guidance, and dynamic feedback, the DILEAF framework enhances user engagement and operational adaptability. The effectiveness of the framework is validated through a case study within a rolling stock organisation, where iterative experiments in both laboratory and field environments demonstrated improvements in task accuracy, real-time decision-making, and system adaptability. It was shown that AR overlays play a crucial role in enabling early error detection and correction, directly supporting the overall task success rate. Furthermore, 91 % of participants in the case study expressed satisfaction with the clarity and usefulness of the information presented via AR, underscoring the framework's effectiveness in delivering task-relevant knowledge and supporting robust performance in maintenance scenarios. These findings illustrate that the DILEAF framework provides a system-informed and operationally structured approach to industrial KM, bridging theoretical KM principles with practical AR-driven implementations. This study establishes a scalable and adaptable foundation for integrating AR into industrial workflows, contributing to the advancement of digitalised maintenance strategies in industrial engineering
Mixed reality meets circular economy: The case of battery lifecycle management
No full textDespite recent digitalization efforts across European industries, research gaps persist in applying mixed reality (MR) within circular economy (CE) frameworks. Specifically, there is limited exploration of data integration, an unclear value proposition for digital tools, and minimal engagement from business perspectives. Despite growing interest, a structured framework mapping MR applications to CE processes remains underexplored. This paper addresses this gap by mapping MR modules to CE practices across lifecycle phases, illustrating specific use cases in design, manufacturing, use, and end-of-life stages. The paper also exploits MR applications for sustainable battery manufacturing, using real-time data to monitor and guide disassembly and recycling processes. This work contributes to advancing sustainable practices and facilitating the transition to circular business models by demonstrating the role of MR in promoting efficient resource use, disassembly, and recycling within a closed-loop system
Cinderella, Marie Antoinette, and Sara: Roles and Role Models in A Little Princess
Full text linkRole-model criticism, the easiest and often most logical form of criticism for children’s literature, has fallen out of favor in our more theoretically sophisticated times. Toril Moi, surveying the state of feminist criticism in 1985, devoted a chapter to “Images of Women” criticism, finding it overly prescriptive and frequently self-contradictory in its calls for a “realistic” or accurate depiction of women’s lives simultaneously with the desire for “strong, impressive female characters” (47). Since many real women (and men!) are neither strong nor impressive, the effort is doomed from the start. And the specific call for “role models” is problematic in itself, for literature is an exchange between writer and readers: readers separated widely by historical circumstance, out of the control of the author and yet affected by him/her in incalculable ways. My role model is your anti-heroine, even in the same text. Yet as a politically-charged reading strategy, Moi goes on to say, “Images of Women” criticism broke new ground: its “will to take historical and sociological factors into account must [in the mid-seventies, coming out of the New Criticism] have seemed both fresh and exciting” (49). She doesn’t suggest, however, how we might revive the best efforts of such work without lapsing into a naïve ahistoricism or a vulgar model of textual reflectionism
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