Kies de Nederlandse taal
Course module: 201800008
After Sales Service Logistics
Course info
Course module201800008
Credits (ECTS)5
Course typeCourse
Language of instructionEnglish
Contact persondr. M.C. van der Heijden
Contactperson for the course
dr. M.C. van der Heijden
dr. M.C. van der Heijden
dr. E. Topan
Academic year2022
Starting block
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
Get familiar with concepts and methods for the design and optimization of after-sales service supply chain for maintaining advanced capital good. After successful completion of the course, the student understands:
  • the meaning of after-sales service logistics and the key decisions to influence its efficiency and effectiveness
  • the specifics of spare part inventory models compared to standard inventory models.
  • the impact of some new developments on after sales service supply chains (for example, additive manufacturing, or control towers for operational decision making). These new developments may change on a yearly basis.
Furthermore, the student is able to:
  • apply a wide range of spare part inventory models in a multi-item, multi-echelon, multi-indenture setting
  • apply Level-Of-Repair Analysis (LORA) for after-sales service supply chains, and to integrate it with multi-item, multi-echelon, multi-indenture spare part models
This course focuses on a specific type of supply chains for the maintenance of advanced capital goods. In such supply chains, failed parts from a geographically dispersed installed base of assets have to be removed and replaced by working parts. The supply chain cover forward flows of working parts, reverse flows of failed parts that may be repaired, and management of repair shops. The course contains several mandatory assignments, amongst others multiple assignments related to an industrial case study. Contact hours are mainly focused on helping students to apply the theory in assignments (tutorials). The largest part of the theory is explained in videos  (screen casts) that can be viewed any time the students prefer and as often as students need. Next to the videos, there are a few (guest) lectures. Attendance is only mandatory at guest lectures.
Assumed previous knowledge
• Basic Excel skills
• Basic probability and statistics
• Basic calculus
• Basic stochastic inventory models
• Basic operational research techniques, such as linear programming
These topics are covered in the first year of the BSc IEM. Some self-study materials to fill a (minor) gap in prior knowledge are available
Participating study
Master Industrial Engineering and Management
Required materials
Various book chapters and papers. Links to the UT library will be mentioned on the website of the course
Recommended materials
Instructional modes

Compulsory attendance at guest lectures

Self study without assistance


Exam and group assignments

Grades for exam and assignments should be at least 5.5, otherwise the lowest grade counts.

Kies de Nederlandse taal