390015 DK PhD-BALOR: Advanced Topics in Operations Management (2023S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 13.02.2023 09:00 to We 22.02.2023 12:00
- Deregistration possible until Fr 17.03.2023 23:59
Details
max. 24 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 13.06. 09:45 - 13:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Wednesday 14.06. 09:45 - 13:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Thursday 15.06. 09:45 - 13:00 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 04.07. 09:45 - 13:15 Digital
Information
Aims, contents and method of the course
Assessment and permitted materials
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.
Minimum requirements and assessment criteria
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)
Examination topics
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
Reading list
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.
Association in the course directory
Last modified: Th 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