Content
Decisions related to designing 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
• Job shops
• Single flow row
• Traditional assembly lines
• Flexible assembly lines
• Production systems under uncertainty
Learning outcomes
After the module the students will be able to:
• Give an overview of methods used in designing production systems.
• Distinguish the most important production layout types (job shop, flow lines and production
centers). Analyze the
layout types advantages and disadvantages, decide for practical layout problems, which type to
choose.
• Apply rough and exact planning approaches for the most important layout types, including the
application of
heuristics and the formulation and adaption of mathematical models.
Examination
The students demonstrate that they can create appropriate designs for different production
systems using the approaches introduced in the lecture. Furthermore, students show that they
are able to explain the fundamentals of the different design approaches and evaluate them. At the
end of the lecture students will have a good understanding of the design of production systems
and layouts, like job shops, flow lines, single flow rows, production centers, and flexible assembly
layouts.
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 optional assignments
involve the modelling of the design 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
Cachon, G., Terwiesch, C., Matching Supply with Demand: An Introduction to Operations
Management, Fourth edition, McGraw-Hill, 2019, ISBN: 9781260084610
Günther, H.-O., Tempelmeier, H., Supply Chain Analytics, 13th edition, Springer, 2020, ISBN:
9783750437661
Heragu, S. S., Facilities Design, Fourth edition, CRC Press, 2016, ISBN: 9781498732895
Hopp, W. J., Spearman, M. L., Factory Physics, Third edition, Waveland Press, 2011, ISBN:
1577667395, 9781577667391
Williams, H. P., Model building in mathematical programming, Fifth edition, Wiley, 2013
General papers
Benjafaar, S., Heragu, S. S., Irani, S. A., Next generation factory layouts: research challenges and
recent progress, Interfaces, 32(6), 2002, 58-76
Singh, S. P., Sharma, R. R. K., A review of different approaches to the facility layout problems,
International Journal of Advanced Manufacturing Technology, 2006, 30 (5-6), 425-433
Drira A., Pierreval H., Hajri-Gabouj S., Facility layout problems: A survey, Annual Reviews in
Control, 31 (2), 2007, 255-267
Job shops
Heragu, S. S., Kusiak, A., Efficient models for the facility layout problem, European Journal of
Operational Research, 53 (1), 1991, 1-13
Single row flow
Ho, Y.C., Moodie, C.L., Machine layout with a linear single row flow path in an automated
manufacturing system, Journal of Manufacturing Systems, 17(1), 1998, 1-22
Flow systems design
Higle, J. L., Stochastic Programming: Optimization When Uncertainty Matters. INFORMS, 30–53,
2005
Sundaramoorthy A, Evans JMB, Barton PI (2012) Capacity Planning under Clinical Trials
Uncertainty in Continuous Pharmaceutical Manufacturing, 1. Mathematical Framework. Industrial &
Engineering Chemistry Research 51(42):13692–13702.
Stefansdottir, B., Grunow, M., Selecting new product designs and processing technologies under
uncertainty: Two-stage stochastic model and application to a food supply chain. International
Journal of Production Economics 201 89–101, 2018
Assembly lines
Boysen, N., Fliedner, M, Scholl, A., Assembly line balancing: Which model to use when?,
International Journal of Production Economics, 111 (2), 2008, 509-528
Scholl, A., Becker, C., State of the art exact and heuristic solution procedures for simple assembly
line balancing, EJOR; 168, 2006, 666- 693. (excluding sections 3.3-3.5, 4.2, 4.3, 5.2, 5.3)
Becker, C., Scholl, A.: A survey on problems and methods in generalized assembly line balancing,
European Journal of OperationsResearch. 168, 2006, 694-715
Gökcen, H., Erel, E., Binary integer formulation of mixed-model assembly line problem, Computers
and Industrial Engineeing, 34, 1998,451-461
Flexible Assembly Layouts
Hottenrott, A., Grunow, M., Flexible layouts for the mixed-model assembly of heterogeneous
vehicles, OR Spectrum, 41, 2019, 943-979
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