Media:

• black board, lecture notes, presentations

Learning Content:

• single server systems: M/M/1, M/G/1: priority rules, model of failures
• networks: open and closed approximations, exact solutions and approximations
• application to flexible manufacturing systems, AGV (automated guided vehicles) - systems
• modeling of control approaches like constant work in process (ConWIP) or kanban
• discrete-time modeling of queuing systems

Learning Goals:

Students are able to:

• Describe queueing systems with analytical solvable stochastic models,
• Derive approches for modeling and controlling material flow and production systems based on models of queueing theory,
• Use simulation and exakt methods.

Recommendations:

• Basic knowledge of statistic
• Recommended compusory optional subject: Stochastics
• Recommended lecture: Materials flow in logistic systems (also parallel)

Workload:

• regular attendance: 42 hours
• self-study: 198 hours

Ronald W. Wolff (1989) Stochastic Modeling and the Theory of Queues, Englewood Cliffs, NJ : Prentice-Hall.
John A. Buzacott, J. George Shanthikumar (1993) Stochastic Models of Manufacturing Systems, Upper Saddle River, NJ : Prentice Hall.

• In winter term 2022/2023, the lecture is limited to a maximum of 30 participants.
• The application for this course is possible from 01.09.2022 to 30.09.2022.
• You can apply by joining the corresponding ILIAS course and filling in the provided application form (required fields of ILIAS course registration).