390015 DK PhD-BALOR: Advanced Topics in Operations Management (2023S)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 13.02.2023 09:00 bis Mi 22.02.2023 12:00
- Abmeldung bis Fr 17.03.2023 23:59
Details
max. 24 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Dienstag 13.06. 09:45 - 13:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Mittwoch 14.06. 09:45 - 13:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Donnerstag 15.06. 09:45 - 13:00 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
- Dienstag 04.07. 09:45 - 13:15 Digital
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
To successfully attend this course, the students should have general understanding of the following concepts and topics:
Integer and linear programming
Mathematical modelling of a targeted and defined problem
Basic competences in programming, with whatsoever coding language
Heuristic algorithms, constructive and local search are preferrable
Each student has to bring his/her own laptop at every lecture.
Technical notes of the lectures will be provided to students.
Integer and linear programming
Mathematical modelling of a targeted and defined problem
Basic competences in programming, with whatsoever coding language
Heuristic algorithms, constructive and local search are preferrable
Each student has to bring his/her own laptop at every lecture.
Technical notes of the lectures will be provided to students.
Mindestanforderungen und Beurteilungsmaßstab
After attending this course students will be able to:
- Identify the characteristics of modern assembly lines.
- Evaluate the impact of these features on line design and management.
- Develop analytical models for designing and operating assembly lines.
- Solve the defined optimization problems through proper solvers and/or heuristic algorithms
- Choosing the best configuration by simultaneously considering different performance criteria (KPIs)
- Identify the characteristics of modern assembly lines.
- Evaluate the impact of these features on line design and management.
- Develop analytical models for designing and operating assembly lines.
- Solve the defined optimization problems through proper solvers and/or heuristic algorithms
- Choosing the best configuration by simultaneously considering different performance criteria (KPIs)
Prüfungsstoff
The examination is going to take place accordingly to the following activities:
Definition of teams of 2 or 3 students each.
Assignment to each team of a specific ALBP to tackle.
Each team has a defined number of weeks to develop the related mathematical model and solve it through a co-defined heuristic algorithm.
Presentation of the activities developed and results obtained
Definition of teams of 2 or 3 students each.
Assignment to each team of a specific ALBP to tackle.
Each team has a defined number of weeks to develop the related mathematical model and solve it through a co-defined heuristic algorithm.
Presentation of the activities developed and results obtained
Literatur
Reading list
Scholl, A., & Scholl, A. (1999). Balancing and sequencing of assembly lines (pp. 34-351). Heidelberg: Physica-Verlag.
Scholl, A., & Scholl, A. (1999). Balancing and sequencing of assembly lines (pp. 34-351). Heidelberg: Physica-Verlag.
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Do 21.09.2023 15:08
The content of the course deals with the following topics:
- Analysis of popular methodologies for designing and operating assembly lines
- The design of assembly lines to minimize the number of stations and cycle time
- Quantitative performance indices to measure the efficiency of assembly lines
- Single, multi and mixed model assembly lines
- Material flow in the assembly process: synchronous and asynchronous assembly lines
- Assembly time variability: deterministic, stochastic and dynamic
- Emerging characteristics of assembly lines and the current manufacturing environment
- Quantitative methodologies for integrating emerging characteristics into the design and management of assembly lines
- Practical solving tools for defining efficient assembly line configurations
- Heuristic solving algorithms for designing assembly lines by minimizing the number of stations or cycle time
- Use of commercial solvers for the optimization of assembly lines
- Real-world case studies of industrial derivation: the assembly process of the automotive and large products.The lecture types and organizations will include all the following approaches:
Frontal lectures for theoretical content presentation
Discussion with students for in-depth topics understanding
In-class teamwork for developing of mathematical models and heuristic algorithms
In-class hands-on for coding and programming examples and applications