Service Engineering

Winter Semester 2024/2025

Lecture

Service Engineering offers a systemic insight into service design, engineering and management. This advanced master’s level course delves deeper into the concepts of service engineering and management, with a specific emphasis on the integration of digitalization and artificial intelligence in the realm of service provision.
Within group projects, you will form small project teams to apply your obtained knowledge in case studies, where you’ll receive weekly or bi-weekly scenarios to handle. After completing the course, all participants will be familiar with state-of-the-art service engineering and management approaches and receive all the tools for designing, developing, and managing a service. Furthermore, you will be familiar with performing team-based service design processes. The accompanying exercise will deepen your knowledge on the lecture content and prepares you for the exam.

Organisation

  • Semester: WS 2024/2025

  • Scope: Lecture (2 SWS), Exercise and Group Projects (2 SWS) / Total 6 CP

  • Exam: The lecture covers a module test consisting of an exam (120 minutes), the final and presentation of the group project. The module grade is composed as follows: 60% exam, 40% mini project. Passing the group project is NOT a mandatory requirement to attend the exam.

  • Language: English

  • Exercise: Independent work on group projects, including discussion of the respective project scenarios, as well as topic-specific workshops and additionally exercise sheets

  • Moodle

  • First lecture: Friday, 18.10.2024

  • Time: 10:15 – 11:45

  • Exercise: Monday’s, 14:15 – 15:45

  • Place: 0.07, Building B4 1

  • Lecturer: Univ.-Prof. Dr.-Ing. Wolfgang Maass

  • Contact person: Hannah Stein (hannah.stein@iss.uni-saarland.de)

  • All participants can post questions about the current lecture in the “Participant Forum” on the learning platform, which will then be discussed there.

Overview

The lecture includes the following topics:

  • Advanced Service Engineering

  • Digital Transformation of Service Processes

  • Service Design with AI Integration

  • AI-Powered Customer Interaction and Engagement

  • Forecasting and Managing Demand

  • Managing Demand and Capacity

  • Queuing Models and Capacity Planning

  • Data-Driven Decision Making in Services

  • Ethical Considerations in AI-Enhanced Services