Content
Decisions related to scheduling of a production system play an important role in all manufacturing
industries. Decisions like configuration of a layout and planning of material flow are all essential
for maximizing the profit of a company. In this course, the students learn how to support these
decisions by applying various quantitative methods in application areas such as assembly
systems, process industries, automotive industry and AGVs in flexible assembly layouts and
production centers.
Content:
• Layout types
• Introduction to scheduling
• Job shops
• Flexible assembly systems
• Economic lot scheduling, block planning
• Scheduling AGV‘s in centers (online vs. offline scheduling)
Learning outcomes
After the module the students will be able to:
• Give an overview of methods used in scheduling production systems.
• Give an overview of the scheduling objectives and requirements in manufacturing.
• Evaluate and apply different planning procedures (shifting bottleneck, scheduling of flexible
assembly systems,
economic lot scheduling, block planning and online vs. offline scheduling) to develop production
schedules for
different types of systems such as assembly lines, food processing systems and AGVs in flexible
assembly layouts
and production centers.
• Apply heuristics and formulate and solve mathematical models
Examination
The focus is on scheduling short term operations on the different manufacturing layout types.
The students have to show that for different production systems they are able to apply suitable
scheduling approaches taught in the lecture.
Furthermore, the students demonstrate that they are able to explain the fundamentals of the
different scheduling approaches and evaluate them.
3 assignments (50%) and a written test (50%). Each assignment consists of 4–5 questions, with
the points equally distributed among the assignments, i.e., each assignment is worth 30 points (90
points in total). Similarly, the written test is also worth 90 points.
Allowed aids for the test will be announced at the beginning of the semester.
Prerequisites
PLEASE NOTE:
This module cannot be attended if WI100967 Designing and Scheduling Manufacturing Systems
was attended previously.
Knowledge of quantitative approaches to production and supply chain management. The modules
"Management Science” and “Production and Logistics” or similar modules at other universities are
a prerequisite. Also, basic programming experience in Python is strongly recommended.
Teaching & learning methods
The module uses a blended learning approach with online on-demand lectures for the students to
study on their own
pace. Weekly in-class lectures are intended to re-cap the lecture material from the recorded
videos, clarify questions and discuss extensions. The assignments involve the modelling of the
scheduling problems discussed in class and the implementation of these mathematical models.
Media & reading list
Lecture slides, lecture video recordings and case studies, in-class exercises, homework
assignments and their solutions.
Books
Pinedo, M., Planning and Scheduling in Manufacturing and Services, Second edition, Springer,
2009, ISBN: 978-1-4419-0909-1, e-ISBN 978-1-4419-0910
Williams, H. P., Model building in mathematical programming, Fifth edition, Wiley, 2013
Paced assembly systems
Boysen, N., Fliedner, M., Scholl, A., Sequencing mixed-model assembly lines: Survey,
classification and model critique. European Journal of Operational Research, 192 (2), 2009, 349–
373.
Boysen, N.; Fliedner, M., Comments on “Solving real car sequencing problems with ant colony
optimization”. European Journal of Operational Research 182 (1), 2007, 466–468.
Gagné, C., Gravel, M., Price, W. L., Solving real car sequencing problems with ant colony
optimization, European Journal of Operational Research, 174(3), 2006, 1427-1448
Solnon, C., Cung, V.D., Nguyen, A., Artigues, C., The car sequencing problem: Overview of state-
of-the-art methods and industrial case-study of the ROADEF’2005 challenge problem, European
Journal of Operational Research 191(3), 2008, 912-927.
Block planning
Günther, H.O., An application of MILP-based block planning in the chemical industry, Proceedings
of the Eighth International Symposium on Operations Research and Its Applications (ISORA’09),
Zhangjiajie, China, September 20–22, 2009, 103–110. Günther, H.O., The blockplanning approach
for continuous time-based dynamic lot sizing and scheduling, Business Research, published online
2014
Kilic, O. A., Akkerman, R., van Donk, D. P., & Grunow, M. (2013). Intermediate product selection
and blending in the food processing industry. International Journal of Production Research, 51(1),
26–42.
Lütke-Entrup, M., Günther, H.O., van Beek, P., Grunow, M., Seiler, T., Mixed integer linear
programming approaches to shelf-life integrated planning and scheduling in yogurt production,
International Journal for Production Research, 43(23), 2005, 5071-5100.
Flow lines
Stefansdottir, B., Grunow, M., Classifying and modeling setups and cleanings in lot sizing and
scheduling, European Journal of Operational Research, 216(3), 2017, 849-865
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