PIM
Projects
Student Research Projects

Student Research Projects

Different topics in maintenance 4.0 focusing on human-centered and data-driven approaches are supervised by PIM team. etencies of the group.

SS2023

Explainability of transformer models
Long Title: Explainability of transformer models for event extraction applications in industrial maintenance
Large lange models for chatbos
Long Title: Large language model based chatbots in industrial maintenance applications

WS 2022

Assistance Systems in Maintenance
Long Title: An Analysis of the Utilization ofAssistance Systems in Maintenance Strategies
Opportunistic maintenance strategies
Long Title: Optimization of opportunistic maintenance strategies using von birtual reality technologies

SS 2022

Sustainable Digital Twin
Long Title: The use of Digital Twin Morphology towards a more Sustainable Maintenance
Artificial Intelligence in Ressilient Supply Chains
Long Title: Development of an Artificial Intelligence Road Map on the Resilience of Supply Chains at the Example of Industrial Maintenance
Hyperautomation for Learning Optimization
Long Title: Design and Implementation of an Integrated Data Pipeline for Combining Process- and Text-Mining towards Optimizing Human Learning in Business Processes

WS 2021

Predictive Maintenance Morhology
Long Title: A Classification of Predictive Maintenance Applications in Industry 4.0

SS2021

Predictive Maintenance Morphology
Full Title: A Classification of Predictive Maintenance Applications in Industry 4.0

WS2020

Analysis of Job Profiles for Competency Evaluation
Full Title: Textual Analysis of Job Descriptions to Asses the Competency Evolution within the Industrial Maintenance
Maintenance Text Data for Cost Factors
Full Title: Design and Development of a Prototype for Transforming Maintenance Text Data to Cost Factors

SS2020

Process Analysis with Process Mining
Full Title: Analysing Process Mining Methods and Related Applications Supported by Machine Learning
Gamification in Maintenance
Full Title: Design of a Procedural Model for Extracting and Specifying Requirements of Gamification Tools and Features in Industrial Maintenance

WS 2019

Artificial Intelligence and Enterprise Resource Planning (ERP) in cooperation with BRP Rotax
Full Title: Possible fields of application of AI methods and technologies in the field of supplier quality at an international engine manufacturer
Blockchain for Smart Manufacturing
Full Title: Enterprises Blockchain for Smart Manufacturing Enterprises
Maintenance Knowledge Management in Metal Industries in cooperation with Primetals
Full Title: Maintenance Knowledge Management in the metals industry
Knowledge Discovery from Text in Industry 4.0
Full Title: Knowledge Discovery from Textual Data in the Context of Smart Factories for Industry 4.0
Learning Scorecard Model for Smart Factories
Full Title: Design of a Learning Scorecard Model for Assessing Human and Machine Productivity in Cyber Physical Social Production Systems
Root Cause Analysis in Predictive Maintenance in cooperation with Infineon
Full Title: The way to a root cause prediction with an existing predictive maintenance model and its impact on maintenance and production KPI´s

SS 2018

Extracting Knowledge from Maintenance Reports
Full Title: A Procedural Model for Extracting Knowledge from Industrial Maintenance Reports
Bayesian Networks in Maintenance
Full Title: Dynamic Bayesian Network for Predictive Maintenance
Non-stationary Bayesian Networks for Predictive Maintenance
Full Title: Non-stationary Dynamic Bayesian Networks for Predictive Maintenance: Theoretical Foundation and Application Scenarios

Name	Purpose	Lifetime	Type	Provider
CookieConsent	Saves your settings for the use of cookies on this website.	1 year	HTML	Homepage TU Wien
SimpleSAML	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	Login TU Wien
SimpleSAMLAuthToken	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	Login TU Wien
fe_typo_user	Is needed so that in case of a Typo3 frontend login the session ID is recognized to grant access to protected areas.	session	HTTP	Homepage TU Wien
staticfilecache	Is needed to optimize the delivery time of the website.	session	HTTP	Homepage TU Wien
JESSIONSID	Is needed so that in case of a LectureTube the session ID is recognized to grant access to protected areas.	session	HTTP	LectureTube TU Wien
_shibsession_lecturetube	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	LectureTube TU Wien

Name	Purpose	Lifetime	Type	Provider
_pk_id	Used to store a few details about the user such as the unique visitor ID.	13 months	HTML	Matomo TU Wien
_pk_ref	Is used to store the information of the users home website.	6 months	HTML	Matomo TU Wien
_pk_ses	Is needed to store temporary data of the visit.	30 minutes	HTML	Matomo TU Wien

Name	Purpose	Lifetime	Type	Provider
facebook	Is used to Enable ad delivery or retargeting	90 days	HTTP	Meta
__fb_chat_plugin	Is needed to store and track interactions (marketing/tracking).	persistent	HTTP	Meta
_js_datr	Is needed to save user settings.	2 years	HTTP	Meta
_fbc	Is needed to save the last visit (marketing/tracking).	2 years	HTTP	Meta
fbm	Is needed to store account data (marketing/tracking).	1 year	HTTP	Meta
xs	Is needed to store a unique session ID (marketing/tracking).	1 year	HTTP	Meta
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
_fbp	Is needed to store and track visits to various websites (marketing/tracking).	3 months	HTTP	Meta
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
presence	Contains the "chat" status of logged in users.	1 month	HTTP	Meta
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
bscookie	Is needed to store performed actions on the website (marketing/tracking).	2 years	HTTP	LinkedIn
X-LI-IDC	Is needed to provide cross-page functionality (marketing/tracking).	session	HTTP	LinkedIn
AnalyticsSyncHistory	Stores the time when the user was synchronized with the "lms_analytics" cookie.	30 days	HTTP	LinkedIn
lms_ads	Is needed to identify LinkedIn members outside of LinkedIn.	30 days	HTTP	LinkedIn
lms_analytics	Is needed to identify LinkedIn members for analytics purposes.	30 days	HTTP	LinkedIn
li_fat_id	Required for indirect member identification used for conversion tracking, retargeting and analytics.	30 days	HTTP	LinkedIn
U	Is needed to identify the browser.	3 months	HTTP	LinkedIn
_guid	Is needed to identify a LinkedIn member for advertising via Google Ads.	90 days	HTTP	LinkedIn