330.169 Maintenance and Reliability Management
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2022W, VO, 2.0h, 3.0EC, to be held in blocked form
TUWEL

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VO Lecture
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to...

  • Defining and recognizing “Smart and Knowledge-Based Maintenance” concepts and strategies as well as associated data-driven processes, methods and tools in the context of Cyber Physical Production Systems and Smart Factories.  
  • Applying an appropriate and industry-oriented methodology toward selecting methods and/or tools (platforms) of “Artificial Intelligence” and “Data Science”, including machine learning and predictive data analytics, knowledge engineering and semantic technology for modeling and analyzing (unstructured) data, learning new patterns, and reasoning (including prediction) in maintenance management.
  • Identifying and Characterizing future-oriented maintenance approaches beyond the age of Industry 4.0 (Out-of-the-box thinking in maintenance management)

Subject of course

Basics of/ requirements for modern maintenance, maintenance strategies, internal or external maintenance? IT in maintenance, use and application of key figures in controlling, lean production and total productive management, basics and statistical methods of reliability engineering, methods of planning and predetermination as well as reliability tests, organizational anchoring of the reliability program in the company. Basics of Cyber Physical Production Systems (CPPS) related concepts and terminologies including Digitalization, Industry 4.0, Digital Transformation in Manufacturing Enterprises, IoT, Digital Twin, etc.., Industrial Artificial Intelligence, Basic of Knowledge-Based Maintenance (KBM), including terminologies, concepts and models of Predictive and Prescriptive Maintenance, Big Data, CRISP-DM and Data Science Applications in Various Industrial Domains, Text-Mining Applications in KBM, Industrial Maintenance Use-cases, Future-oriented Maintenance Approaches (Self-healing and self-management, collaborative robotics and assistant systems in maintenance, Digital Twin in maintenance, etc.)


Teaching methods

Qualitative modeling and analysis (PriMa Model and Maintenance Cube)

CRISP-DM, Machine Learning and Text Mining

Mode of examination

Written

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Thu09:00 - 17:0015.12.2022Seminarraum EBEG-3 - RPL Instandhaltungsmanagement - MATYAS
Fri09:00 - 18:0016.12.2022Theresianumgasse HS 2 Instandhaltungsmanagement - ANSARI - Hinweis: Vorlesung in Englisch!
Mon09:00 - 17:0016.01.2023 https://teams.microsoft.com/l/meetup-join/19%3ameeting_ODg1ZTY3ZGItMjZlMC00Mzk1LWFmOTgtZTRiNmVjNTY5MDI4%40thread.v2/0?context=%7b%22Tid%22%3a%22e7c56bf9-e9d8-48d1-a7a2-d3d4127341e0%22%2c%22Oid%22%3a%22a1c5a4c3-d046-40df-9e11-263a4297ab91%22%7dZuverlässigkeitsmanagement - HASELGRUBER
Tue09:00 - 17:0017.01.2023 https://teams.microsoft.com/l/meetup-join/19%3ameeting_MmVmNGNlODgtYzk0Ny00MmYwLWI2NTEtMjU1OTRhYzYxNTEx%40thread.v2/0?context=%7b%22Tid%22%3a%22e7c56bf9-e9d8-48d1-a7a2-d3d4127341e0%22%2c%22Oid%22%3a%22a1c5a4c3-d046-40df-9e11-263a4297ab91%22%7dZuverlässigkeitsmanagement - HASELGRUBER
Course is held blocked

Examination modalities

The proof of achievements will be evaluated by a written exam. The written examination consists of 3 parts (lecture part Prof. Matyas = 1/3, lecture part Dr. Ansari = 1/3, lecture part Dr. Haselgruber = 1/3). All 3 parts have to be completed positively in order to pass the VO.

In order to take part in an examination, it is necessary to register in time (for the respective examination date) in TISS. Students who do not meet the registration deadline cannot take part in the exam! Enquiries in this regard will not be answered!

Examination Barriers

In accordance with the study regulations (Mitteilungsblatt 2014, 3. Stück; Nr.22), the following rules apply to the cancellation of examinations.

§ 18a. (1)) The students are entitled to cancel their examinations orally, in writing or electronically with the examiner or dean of studies at the latest two working days before the day of the examination.

(2) If students do not appear for an examination without having cancelled their registration in accordance with paragraph 1, the Dean of Studies is entitled to exclude these students from the registration for this examination for a period of eight weeks at the suggestion of the examiner. This period begins on the examination day on which the student, despite having registered correctly, did not appear without having cancelled his/her registration beforehand. The affected students must be informed of the suspension in an appropriate manner.

(3) If the student can prove that he/she has been prevented from deregistering in due time in accordance with paragraph 1 by a valid reason (e.g. accident) or another reason worthy of special consideration, the suspension must be lifted.

It should be noted that use is made of the option set out in paragraph (2) for students who do not appear at the examination without prior deregistration.

Examinations: Registration by e-mail to lehreBTSP@tuwien.ac.at.

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Fri16:00 - 17:3019.04.2024 https://tuwel.tuwien.ac.at/course/view.php?id=58322written19.03.2024 09:00 - 17.04.2024 09:00TISSOnline-Prüfung
Thu16:00 - 17:3027.06.2024 https://tuwel.tuwien.ac.at/course/view.php?id=58322written28.05.2024 09:00 - 25.06.2024 09:00TISSOnline-Prüfung

Course registration

Begin End Deregistration end
04.09.2022 00:00 03.02.2023 00:00 03.02.2023 00:00

Curricula

Study CodeObligationSemesterPrecon.Info
066 482 Mechanical Engineering - Management Mandatory electiveSTEOP
Course requires the completion of the introductory and orientation phase

Literature

Zur weiteren Vertiefung empfohlen: K. Matyas: Instandhaltungslogistik - Qualität und Produktivität steigern, Hanser Verlag München, 6. Auflage, 2016

Previous knowledge

Basic knowledge in production, logistics, quality, process and project management

Language

German