Course syllabus
7,5 Credits
Compulsory course in the Master Programme
Production Engineering
In Chalmers University of Technology
Gothenburg, Sweden
Examiner
Professor Johan Stahre
email: johan.stahre@chalmers.se
Telephone: +46(0)317721288
|
Course administrator and project supervisors Postdoctoral researcher Clarissa González E-mail: clarissa.gonzalez@chalmers.se Telephone: +46(0)768537741
PhD Student Mohan Rajashekarappa E-mail: rmohan@chalmers.se |
Master Programme responsible PhD Anders Skoogh email: anders.skoogh@chalmers.se Telephone: +46(0)317724806 |
STUDENT REPRESENTATIVES
Matilda Graad - matilda.m.graad@gmail.com
Karl Steen - karl00steen@gmail.com
Johannes Lövhall - jolo0036@student.hv.se
Diego Perez Oliver - diegop@student.chalmers.se
Ahmed Mohamed Abokor - abokor@student.chalmers.se
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. |
06-09-24 |
|
2. |
A presentation of the exercise in the module of “Digital platforms in a manufacturing context” must be performed. |
19-09-24 |
|
3. |
A presentation about the Data module will be conducted. |
04-10-24 |
|
4, |
Attend the company visit |
8 or 10-10-24 |
|
5. |
Actively participate in the Sustainability Workshop |
17-10-24 |
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:
- Introduction
- Sustainability
- Digital twin
- Data
- Digital platforms
- 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 |
13-09-24 |
|
2. |
Deliverable of Progress report on Digital Twin, Connectivity & Platforms |
26-09-24 |
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3. |
Deliverable of Progress report on Automation & Data |
09-10-24 |
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4. |
Delivery of final draft to opponent team |
11-10-24 |
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5. |
Send written opposition to assigned team |
15-10-24 |
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6. |
Upload Power Point presentation to Canvas |
19-10-24 |
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7. |
Presentation of project. You are expected to make questions to an assigned team. |
22-10-24 |
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8. |
28-10-24 |
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 |
03-09-24 |
13:15 |
15:00 |
HA2 |
Introduction |
General Course Overview and Future Factories |
Prof. Johan Stahre, Clarissa González, Mohan Rajashekarappa |
|
03-09-24 |
15:15 |
17:00 |
HA2 |
Industrial revolutions from traditional to digital systems |
Prof. Johan Stahre |
||
|
05-09-24 |
13:15 |
15:00 |
EF |
Research criteria: Source criticism and trust while referencing |
Beate Granström |
||
|
05-09-24 |
15:15 |
17:00 |
EF |
Sustainability Thinking |
Assoc. Prof. Mélanie Despeisse |
||
|
06-09-24 |
13:15 |
15:00 |
HC2 |
Self-study |
|
||
|
37 |
10-09-24 |
13:15 |
15:00 |
HC2
|
Digital Twin & CPS |
Digital Twin (System Level) |
Prof. Anna Syberfeldt
|
|
10-09-24 |
15:15 |
17:00 |
HC1 |
Digital Twin (Factory Level) |
|||
|
11-09-24 |
13:15 |
15:00 |
HA2 |
CPS & Standardization, Virtual factory planning |
Prof. Björn Johansson |
||
|
13-09-24 |
13:15 |
15:00 |
EE |
XR in manufacturing |
Huizhong Cao & Henrik Söderlund |
||
|
38 |
17-09-24 |
13:15 |
15:00 |
HC2 |
Digital platforms |
Working with culturally diverse groups |
Senior Lecturer Becky Bergman |
|
17-09-24 |
15:15 |
17:00 |
HC2 |
Digital platforms in Manufacturing |
Dr. Clarissa González |
||
|
19-09-24 |
13:15 |
14:00 |
HC3 |
Digital platforms in Manufacturing |
Dr. Clarissa González |
||
|
19-09-24 |
14:15 |
16:00 |
HC3 |
Workshop |
Dr. Clarissa González |
||
|
20-09-24 |
13:15 |
15:00 |
EE |
Digital platforms as enablers of circularity |
Assistant Professor. Federica Acerbi |
||
|
39 |
24-09-24 |
13:15 |
15:00 |
SBMultisal (SB3) |
Automation |
Human-centered automation |
Dr. Omkar Salunkhe
|
|
24-09-24 |
15:15 |
17:00 |
SB Multisal (SB3) |
Cognitive-levels of automation |
|||
|
26-09-24 |
13:15 |
17:00 |
HC2 |
Digitalization & Cognitive Automation |
|||
|
27-09-24 |
15:15 |
17:00 |
No booked room |
Work on your own | |||
|
40 |
01-10-24 |
13:15 |
15:00 |
HB2 |
Data |
The role of data in maintenance in production systems |
Senior Lecturer Ebru Turanoglu
|
|
01-10-24 |
15:15 |
17:00 |
HB2 |
Introduction to Data Science |
|||
|
03-10-24 |
13:15 |
15:00 |
HC2 |
Data Mining & Visualization, AI and ML |
|||
|
03-10-24 |
15:15 |
17:00 |
HC2 |
Preparation for presentations |
|||
|
04-10-24 |
13:15 |
15:00 |
HA3, MB |
Presentations by students |
|||
|
41
|
08-10-24 |
13:15 |
15:15 |
SKF |
Industrial Immersion |
Visit to SKF Group 1 |
|
|
08-10-24 |
14:00 |
17:00 |
SII Lab |
XR |
XR Workshop |
Huizhong Cao |
|
|
10-10-24 |
13:15 |
15:15 |
SKF |
Industrial Immersion |
Visit to SKF Group 2
|
|
|
|
42 |
15-10-24 |
13:15 |
15:00 |
SII Lab |
Workshops |
XR Workshop |
Huizhong Cao |
|
15-10-24 |
15:15 |
17:00 |
SII Lab |
||||
|
17-10-24 |
13:15 |
15:00 |
SB3 |
Sustainability Workshop |
Assoc. Prof. Mélanie Despeisse and Assistant Prof. Federica Acerbi
|
||
|
17-10-24 |
15:15 |
17:00 |
SB3 |
||||
|
43 |
22-10-24 |
13:15 |
17:00 |
HA2 |
Final stretch |
Final Project Presentation |
Clarissa González & Mohan Rajashekarappa |
|
25-10-24 |
13:15 |
14:00 |
EB |
Summary of the course |
Clarissa González |
||
|
43 |
31-10-24 |
08.00 |
12:00 |
TBD |
|
Exam |
|
LITERATURE
Check the suggested literature for each module in the Files menu. The literature will be updated with the development of the course.