Sara Scheffer

Ph.D.

Post Doctoral Researcher

Research Group for Logistics and Quality Management | Research Unit of Production and Maintenance Management | Institute of Management Science | Faculty of Mechanical and Industrial Engineering

TU Wien

Email: sara.scheffer@tuwien.ac.at

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Education

Post Doctoral Researcher for Research Unit of Production and Maintenance Management, Institute of Management Science, Faculty of Mechanical and Industrial Engineering, TU Wien, Austria
Ph.D. in Engineering Technology, Department of Design, Production, and Management, Chair of Asset Management and Maintenance Engineering, University of Twente, the Netherlands, 2024
M.Sc., Industrial Engineering & Management, University of Groningen, The Netherlands, 2020
B.Sc., Naval Architecture, NHL, Leeuwarden, The Netherlands, 2016

Research topics

Augmented Reality
Information Technology
Maintenance Operation
Fault Detection
Human-Computer Interaction
Decision-support systems

Students under (co-)supervision

PhD student(s)

Wanting Mao: Enhancing Knowledge Management Processes through Augmented Reality in Railway Maintenance

MSc student(s)

Kastriot Kajtazi: AR-Supported Knowledge Transfer Motion Tracking and Process Visualization for Tacit Knowledge Capturing

Elias Panner: Mixed Reality for Firefighting: Explainable AI for In-Situ Hazard Assessment

Sebastian Lux: Context-Aware Mixed Reality for Firefighter Navigation and Decision Support: System Development and Performance Evaluation.

Filipp Hafner: Mixed Reality as a Decision-Support Tool for End-of-Life Electric Vehicle Battery Disassembly

Karina Muriasova: Adaptable Interfaces for Augmented Reality Tailored to Workforce Skills (Troubleshooting in Manufacturing)

Stamatia Chachlaki: Augmented Reality for Perishable Inventory: Enhancing Quality Control and Reducing Food Waste in Food Banks

Nico Illich: A Framework for Operational Performance and Reliability in Freight Rail Arrival Time Prediction

Bachelor student(s)

Tegshbayar Batbayar: Augmented Reality-Driven Decision Support Systems: Applications in Maintenance and Manufacturing

Eve Valjevac: Smart Maintenance Strategies in Automotive Assembly: A Serious Game–Based Simulation Using Machine Learning Models

Lukas Besic: Advances in Predictive Maintenance and Troubleshooting for Industry 4.0: A Review of Neurosymbolic Artificial Intelligence, Augmented Reality, and Artificial Visual Intelligence.

Other work(s)

Michael Starzinger: AR-Enhanced Decision-Support-System for Fan Coil Unit at TU Wien

Results

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AR-COMPASS

For complete list of publications please visit Google Scholar, opens an external URL in a new window.

Scheffer, S. E. (2024). Let’s augment the future together! Augmented reality troubleshooting support for IT/OT rolling stock failures. University of Twente. https://doi.org/10.3990/1.9789036560184, opens an external URL in a new window

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SimpleSAMLAuthToken	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	Login TU Wien
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wd	Is needed to log the screen resolution.	1 week	HTTP	Meta
fr	Is needed to serve ads and measure and improve their relevance.	3 months	HTTP	Meta
act	Is needed to store logged in users (marketing/tracking).	90 days	HTTP	Meta
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datr	Is needed to identify the browser for security and website integrity purposes, including account recovery and identification of potentially compromised accounts.	2 years	HTTP	Meta
dpr	Is used for analysis purposes. Technical parameters are logged (e.g. aspect ratio and dimensions of the screen) so that Facebook apps can be displayed correctly.	1 week	HTTP	Meta
sb	Is needed to store browser details and security information of the Facebook account.	2 years	HTTP	Meta
dbln	Is needed to store browser details and security information of the Facebook account.	2 years	HTTP	Meta
spin	Is needed for promotional purposes and social campaign reporting.	session	HTTP	Meta
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cppo	Is needed for statistical purposes.	90 days	HTTP	Meta
locale	Is needed to save the language settings.	session	HTTP	Meta
pl	Required for Facebook Pixel.	2 years	HTTP	Meta
lu	Required for Facebook Pixel.	2 years	HTTP	Meta
c_user	Required for Facebook Pixel.	3 months	HTTP	Meta
bcookie	Is needed to store browser data (marketing/tracking).	2 years	HTTP	LinkedIn
li_oatml	Is needed to identify LinkedIn members outside of LinkedIn for advertising and analytics purposes.	1 month	HTTP	LinkedIn
BizographicsOptOut	Is needed to save privacy settings.	10 years	HTTP	LinkedIn
li_sugr	Is needed to store browser data (marketing/tracking).	3 months	HTTP	LinkedIn
UserMatchHistory	Is needed to provide advertising or retargeting (marketing/tracking).	30 days	HTTP	LinkedIn
linkedin_oauth_	Is needed to provide cross-page functionality.	session	HTTP	LinkedIn
lidc	Is needed to store performed actions on the website (marketing/tracking).	1 day	HTTP	LinkedIn
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li_fat_id	Required for indirect member identification used for conversion tracking, retargeting and analytics.	30 days	HTTP	LinkedIn
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