Course syllabus


MPR271 Simulation of production systems lp2 HT23 (7.5 hp)
Course is offered by the department of Industrial and Materials Science
Link to the detailed course PM in PDF version: CoursePM - Simulation of Production Systems 2023 v2.pdf


Contact details

Anders Skoogh, PhD, Professor
Telephone: +46 (0)31 - 772 48 06

Course assistant
Siyuan Chen, PhD student
Telephone: +46 (0)31 772 11 89


Course purpose

The course vision is to provide an in-depth insight about the potential of the virtual world in industrial innovation processes. This includes establishing an improved awareness about methods and tools for the integration of simulation technology in product, process and production development work procedures. Simulation tools have proven to be very powerful in the development of sustainable production systems covering economic, ecologic and social aspects throughout entire product life-cycles.

The purpose of the course is to advance the students’ knowledge and skills in development of production flows, specifically taking dynamic aspects into consideration. A specific aim is to build a model of a production system using professional discrete event simulation software. This model, combined with established theory, is then used to analyze production systems and provide recommendations improving the sustainability performance with focus on the economic and ecologic aspects.



Schedule is available in the PDF version of the course PM and at the bottom of this page.



Course literature

  • Course PM
  • Power-point presentations available at the MPR271 Canvas page
  • Scientific papers
  • Software manual and Xcelerator program


Course design

The course applies problem oriented pedagogy. Centre of learning gravity lays to a great extent on a project work where the students cooperate in groups of two. The practical learning element begins with some basic exercises to familiarize with a professional discrete event simulation software package.

The project work, which is mandatory for examination, aims to support the students putting a systematic methodology for simulation projects into action. Develop a model representing an industrial production flow. Furthermore, with support from Discrete Event Simulation, analyze its weaknesses and in a technical report present proposals for making the production system more efficient. In addition to lectures focusing on theory, the students will read scientific papers and relate them to the project.

Learning Activities

In summary, the course contains five types of learning activities:

  • Lectures – Basis for theoretical understanding and to support your project work.
  • Programming lectures and seminars – To support learning in DES programming and develop skills in a professional software package.
  • Laboratory exercises – Familiarize with the DES software and its user interface. Training in model building, preparation for examination project work.
  • Project work – Practice skills learned throughout the course, show skills in communication, project methodology, DES programming, and analysis of production flows.


Learning objectives

LO1: Explain the fundamentals of Discrete Event Simulation (DES) and determine in what situation it is a useful engineering tool.
LO2: Plan and perform a simulation project following a structured recognized project methodology for simulation of production flows.
LO3: Create a simulation model representing a complex production system using a professional DES software package and established modeling techniques.
LO4: Describe and apply techniques for input data management.
LO5: Plan, design, and perform experiments to improve a production system based on a DES model.
LO6: Evaluate various production improvement possibilities using a DES model and knowledge in production systems.
LO7: Describe and exemplify how DES studies can support increased sustainability of production systems.
LO8: Interpret and relate to state-of-the-art knowledge acquired from scientific papers.
LO9: Communicate and argue for the results of a production simulation study, for example using quantitative data, own analysis and judgments, and model graphics.



Lab exercises, project report (including computer model code), and a written “knowledge test” (quiz) cover all areas of the course. Grades are individual and the grading scale is Failed, 3, 4 and 5.

Students must be approved on all assessment tasks individually (project, laboratory exercises, and knowledge test) to pass the course.

The following logic will be used for deciding the individual grades (maximum 100p):

  • Mandatory project report (including DES model) = maximum 50 points
  • Mandatory individual quiz = maximum 30 points
  • Elective extra tasks to be included in the project report = maximum 20 points

Individual grade 5: Same as for grade 3 AND total number of points ≥ 80 p
Individual grade 4: Same as for grade 3 AND total number of points ≥ 60 p
Individual grade 3: Project report (including DES model) ≥ 25 p AND individual quiz ≥ 15 p AND lab exercises complete.
Individual grade F: Project report (including DES model) < 25 p OR individual quiz < 15 p OR lab exercises incomplete.

Course summary:

Date Details Due