Using Functional Blocks for Rolling Stock Troubleshooting: Sequential Augmented Reality Assistant (SARA)

Maintenance 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...

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Main Authors: Sara Scheffer, Alberto Martinetti, Roy Damgrave, Leo van Dongen
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10990276/
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author Sara Scheffer
Alberto Martinetti
Roy Damgrave
Leo van Dongen
author_facet Sara Scheffer
Alberto Martinetti
Roy Damgrave
Leo van Dongen
author_sort Sara Scheffer
collection DOAJ
description Maintenance 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.
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spelling doaj-art-4e8407d68d584dc1b6a5f9c675a79cdc2025-08-20T03:48:27ZengIEEEIEEE Access2169-35362025-01-0113873698738510.1109/ACCESS.2025.356767410990276Using Functional Blocks for Rolling Stock Troubleshooting: Sequential Augmented Reality Assistant (SARA)Sara Scheffer0https://orcid.org/0000-0002-2580-5732Alberto Martinetti1https://orcid.org/0000-0002-9633-1431Roy Damgrave2https://orcid.org/0000-0002-4053-1012Leo van Dongen3Research Unit of Production and Maintenance Management, Institute of Management Sciences, TU Wien, Vienna, AustriaDepartment of Design, Production and Management, University of Twente, Enschede, The NetherlandsDepartment of Design, Production and Management, University of Twente, Enschede, The NetherlandsDepartment of Design, Production and Management, University of Twente, Enschede, The NetherlandsMaintenance 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.https://ieeexplore.ieee.org/document/10990276/Augmented realityfunctional blocksmaintenancerolling stocktroubleshooting
spellingShingle Sara Scheffer
Alberto Martinetti
Roy Damgrave
Leo van Dongen
Using Functional Blocks for Rolling Stock Troubleshooting: Sequential Augmented Reality Assistant (SARA)
IEEE Access
Augmented reality
functional blocks
maintenance
rolling stock
troubleshooting
title Using Functional Blocks for Rolling Stock Troubleshooting: Sequential Augmented Reality Assistant (SARA)
title_full Using Functional Blocks for Rolling Stock Troubleshooting: Sequential Augmented Reality Assistant (SARA)
title_fullStr Using Functional Blocks for Rolling Stock Troubleshooting: Sequential Augmented Reality Assistant (SARA)
title_full_unstemmed Using Functional Blocks for Rolling Stock Troubleshooting: Sequential Augmented Reality Assistant (SARA)
title_short Using Functional Blocks for Rolling Stock Troubleshooting: Sequential Augmented Reality Assistant (SARA)
title_sort using functional blocks for rolling stock troubleshooting sequential augmented reality assistant sara
topic Augmented reality
functional blocks
maintenance
rolling stock
troubleshooting
url https://ieeexplore.ieee.org/document/10990276/
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