Course syllabus

7,5 Credits

Compulsory course in the Master Programme

Production Engineering

In Chalmers University of Technology

Gothenburg, Sweden

 PPU161 Picture.png

Examiner

Professor Johan Stahre

email: johan.stahre@chalmers.se

Telephone: +46(0)317721288

 

 

 

Course administrator and project supervisors

PhD Student Sandra Jaksic

E-mail: Sandra.jaksic@chalmers.se

 

PhD Student Anita Notarianni

E-mail: anitacl@chalmers.se

Master Programme responsible

PhD Anders Skoogh

email: anders.skoogh@chalmers.se

Telephone: +46(0)317724806

STUDENT REPRESENTATIVES

MPPEN   henssonlin@gmail.com    Hanxuan Lin
MPPEN   hamza9897pk@gmail.com   Hamza Ahmed Tanveer Tanveer
MPPEN   oscar.h.wallin@gmail.com        Oscar Wallin
MPSYS   emilia@wenneberg.se     Emilia Wenneberg
UTBYTE  jan.wittenmeier@rwth-aachen.de  Jan Wittenmeier

PURPOSE OF THE COURSE

Students who graduated from Chalmers Master's Programme in Production Engineering must have achieved the knowledge and judgment skills to be able to conceptualize, develop and improve production systems with an emphasis on digital technologies and sustainability.

The primary objective is to convey fundamental knowledge about the role of digital technologies in production systems and to serve as a foundation for further learning in more specialized courses within the Master's Programme.

 

LEARNING OBJECTIVES

After this course the students will be able to:

LO1.- Analyze and contrast paradigms in the history of production systems and project the impact of digital technologies on the future of industrial production systems.

LO2.- Evaluate a range of enablers and challenges that influence decision-making in a production system.

LO3.- Compare and contrast the application of digital technologies in current production systems and recommend their implementation in the design of new ones.

LO4.- Analyze and evaluate the role of automation in a production system considering both physical and cognitive aspects.

LO5.- Describe how connectivity can enable an adaptive information system in a production environment.

LO6.- Apply basic data analytics to address problems in production systems.

LO7.- Identify and evaluate the implications of digital technologies regarding environmental and social sustainability in production systems.

LO8.- Apply acquired knowledge and collaborative skills in diverse teams to analyse, evaluate, and develop technical solutions and complex production systems.

 

COURSE CONTENT

 The course covers the following topics:

  • History of production systems and production paradigms;
  • The application of digital technologies in current production systems;
  • Connectivity applications in production systems;
  • Use of data analytics for optimization of production systems;
  • Levels of automation for a production system;
  • Implications of digital technologies regarding sustainability.

 

ORGANIZATION

Students will learn the course content using a problem oriented pedagogy supported by lectures. This course includes a project that is performed in diverse teams. An industrial case is used to apply the knowledge acquired in the course modules. If circumstances allow it, the course intends to organise company visits

  The learning activities are:

  • Lectures: Provides theoretical foundation and support for project work;
  • Assignments: Reflections of the use of the digital technologies and impact on the development of sustainable production systems;
  • Project: Applying skills learned throughout the course to analyze and improve productions systems;
  • Presentation: Be able to present and defend project results.

 

EXAMINATION

The course examination is based on three parts:  modules' assignments, project work, final exam. It is compulsory to sign up for the exam in order to join a session examination. 

  • Modules' assignments - Pass or fail. You have to pass all the assignments.
  • Project - project's assignments, report and presentation - maximum 30 points (report = 20 points, presentation = 10 points, assignments= pass or fail).
  • Exam - maximum 20 points, you need at least 8 points to pass.

The grading scale is: Failed, 3, 4 and 5.

The points are summed up and result in the following scale:

40-50 points   = 5 (the maximum grade cannot exceed 50 points).

30-39 points   = 4

20-29 points   = 3

0-19   points   = Failed

Modules' assignments

All assignments from the different modules must be approved to pass the course. The expectations from each assignment, are explained in each exercise in the Assignments section (the assignments will be published along with the development of the lectures).

The mandatory activities are:

1.                    

The sustainability module should be completed and the quiz must be passed.

07-09-2026

2.                    

A  presentation of the exercise in the module of “Digital platforms in a manufacturing context” must be performed.

17-09-2026

3.

A presentation about the Data module will be conducted.

25-09-2026

4,

Attend the company visits

2 and 8-10-2026

5.

Actively participate in the Sustainability Workshop

06-10-2026

 

 

Exam

The student needs to pass the exam in order to be approved in the course and achieve a final grade. The written exam covers the content of all the different modules in this course:

  1. Introduction
  2. Sustainability
  3. Digital twin
  4. Data
  5. Digital platforms
  6. Automation

 

Project

The project work aims at applying the skills throughout the course to understand and implement digital technologies for the development of a sustainable production system. This is a group activity and further information can be found in the Module "Project".  Directions for the project can be found here.

 

Project supervisors:

 

Project-related assignments:

1.                    

Deliverable of Progress report on Sustainability

13-09-2026

2.                    

Deliverable of Progress report on Automation & Digital Platforms

25-09-2026

3.                    

Deliverable of Progress report on Data & Digital Twin

07-10-2026

4.

Delivery of final draft to opponent team

09-10-2026

5.

Send written opposition to assigned team

12-10-2026

6.

Upload Power Point presentation to Canvas

14-10-2026

7.

Presentation of project. You are expected to make questions to an assigned team.

15-10-2026

8.

Delivery of final report including comments from opposition

20-10-2026

 

COURSE SCHEDULE

Note: All the sessions of this course will be held on site.

During self-study sessions and project work, you and your team are responsible to define how to communicate and where to meet.

Week

Date

Start

End

Location

Block

Lecture

Lecturer

36

01-09-2026 

13:15

15:00

ML11 

Introduction

General Course Overview and Future Factories

Prof. Johan Stahre 

Sandra Jaksic 

01-09-2026 

15:15

17:00

ML11 

Working with a culturally diverse group 

Dr. Becky Bergman  

03-09-2026 

13:15

15:00

ML11 

From Question to Credible Source: Searching, Source Evaluation, Referencing and AI in PPU161

Dr. Marco Schirone 

03-09-2026 

15:15

17:00

ML11 

Sustainability Thinking   

Prof. Mélanie Despeisse 

04-09-2026 

13:15

15:00

 

Self-study

 

37

 

08-09-2026 

13:15

15:00

ML11 

 

Automation 


 

Human-centered Automation 

Dr. Omkar Salunhke

 

 

08-09-2026 

15:15

17:00

ML11 

Cognitive levels of automation 

10-09-2026 

13:15

15:00

ML11 

Digitalisation and cognitive automation  

10-09-2026 

15:15

17:00

ML11 

The future of work and skill gaps in industry

Dr. Greta Braun

11-09-2026

13:15

15:00

ML11 

XR in manufacturing

Huizhong Cao

38

15-09-2026 

15:15

17:00

ML11 

Digital platforms

Business models for sustainable manufacturing

Dr. Clarissa González

17-09-2026 

13:15

14:00

ML11 

Preparing for presentations

Dr. Fabio Monetti

 

17-09-2026 

14:15

16:00

ML11 

Presentations from students

18-09-2026 

13:15

15:00

ML11 

Platform data in Manufacturing

Magnus Wahlgård

39

22-09-2026 

13:15

15:00

ML11 

Data

The role of data in maintenance of production systems

Senior Lecturer Ebru Turanoglu 

 

22-09-2026 

15:15

17:00

ML11 

Introduction to Data Science

24-09-2026 

13:15

15:00

ML11 

Data mining & visualization, AI and ML in Maintenance

24-09-2026 

15:15

17:00

ML11 

Preparation for presentations

25-09-2026 

13:15

15:00

EL51, EL52 

Presentations by students

40

29-09-2026

13:15

15:00

ML11 

Digital Twin & CPS 

AI & Digital Twin (Systems level) 

Prof. Anna Syberfeldt


 

29-09-2026

15:15

17:00

ML11 

AI & Digital Twin (Factory Level) 

30-09-2026

15:15

17:00

ML11 

Cyber-Physical Systems and Standards

Prof. Björn Johansson

02-10-2026

13:15

17:00

Battery Center Gothenburg

Industrial Immersion

Visit to Battery center

Dr. Daniel Nåfors

41

 

06-10-2026

13:15

17:00

ML11

Sustainability

Sustainability Workshop

 Prof. Mélanie Despeisse & Qi Fang

08-10-2026

13:15

17:00

SKF

Industrial Immersion  Visit to SKF   Magnus Wahlgård

42

13-10-2026

13:15

15:00

ML11

Final stretch

Course Summary

Prof. Johan Stahre 

Sandra Jaksic 

15-10-2026

13:15

15:00

ML11

Final presentation

Prof. Johan Stahre 

Sandra Jaksic

 

15-10-2026

15:15

17:00

ML11

43

20-10-2026 - 23:59 Online

Report

Deliver Final Report

 

44

29-10-2026 8:30 12:30 Johanneberg

 

EXAM

 

LITERATURE

Check the suggested literature for each module in the Files menu. The literature will be updated with the development of the course.