Course syllabus

7,5 Credits

Compulsory course in the Master Programme

Production Engineering

In Chalmers University of Technology

Gothenburg, Sweden

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Examiner

Professor Johan Stahre

email: johan.stahre@chalmers.se

Telephone: +46(0)317721288

 

Course administrator

PhD student Greta Braun

E-mail: greta.braun@chalmers.se

Telephone: +46 734483591

 

PhD student Clarissa González

E-mail: clarissa.gonzalez@chalmers.se

Telephone: +46(0)768537741

 

 

Master Programme responsible

PhD Anders Skoogh

email: anders.skoogh@chalmers.se

Telephone: +46(0)317724806


 

 

 

STUDENT REPRESENTATIVES

 soureeshde@gmail.com                    Soureesh De

 marcel.mahler@gmx.de                     Marcel Mahler

 leonique@student.chalmers.se         Leonique Svensson

 frederickrexton24@gmail.com          Frederick Rexton

 kostastul@hotmail.com                      Konstantinos Toulikas

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.

02-09-22

2.                    

A  presentation of the exercise in the module of “Application of 5G in a manufacturing context” must be performed.

09-09-22

3.

A presentation about the Data module will be conducted.

22-09-22

4.

Actively participate in the Sustainability Seminar

06-10-22

 

 

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. Connectivity & 5G
  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-related assignments:

1.                    

Deliverable of Progress report on Sustainability

12-09-22

2.                    

Deliverable of Progress report on Connectivity & Digital Twin 

19-09-22

3.                    

Deliverable of Progress report on Data & Automation

03-10-22

4.

Delivery of final draft to opponent team

11-10-22

5.

Send written opposition to assigned team

13-10-22

6.

Upload Power Point presentation to Canvas

16-10-22

7.

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

17-10-22

8.

Delivery of final report including comments from opposition

27-10-22

 

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

35

29-08-22

13:15

15:00

EF

Introduction

General Course Overview and Future Factories

Johan Stahre

29-08-22

15:15

17:00

EF

Industrial revolutions from traditional to digital systems

Johan Stahre

01-09-22

8:00

9:45

EB

Sustainability Thinking: guided activity

Mélanie Despeisse

01-09-22

10:00

11:45

EB

Working with a culturally diverse group

Becky Bergman

02-09-22

15:15

17:00

EE (lecturer online)

Manufacturing Strategies

David Romero (Tecnológico de Monterry)

36

08-09-22

8:00

9:45

HA2

 

Connectivity & 5G

Connectivity as an enabler of Industry 4.0

Maja Bärring

https://chalmers.zoom.us/j/65208813477

08-09-22

10:00

11:45

HA2

Students work with tasks/presentation

09-09-22

13:15

15:00

EE

Presentations from students

Maja Bärring

09-09-22

15:15

17:00

EE

Examples & learnings from previous industrial projects

Maja Bärring

37

12-09-22

15:15

17:00

EF

Digital Twin & CPS

Digital twins in industry

Pawel Dabrowski (PTC)

15-09-22

9:00

9:45

EB

Digital Twin (System Level)

Anna Syberfeldt

15-09-22

10:00

11:45

EB

Digital Twin (Factory Level)

Anna Syberfeldt

16-09-22

15:15

17:00

HA2

CPS & Standardization, Virtual factory planning

Björn Johansson

38

19-09-22

13:15

15:00

SB-M500

Data 

The role of data in maintenance in PS

Anders Skoogh

19-09-22

15:15

17:00

SB-M500

Introduction to Data Science

Ebru Turanoglu

22-09-22

8:00

9:45

EB

Data Mining & Visualization

22-09-22

10:00

11:45

EB

AI and ML - presentation by students

23-09-22

15:15

17:00

Work on your own

39

26-09-22

13:15

15:00

EF

Human-centered Automation

Human-centered Automation

Dan Li

26-09-22

15:15

17:00

EF

Cognitive levels of Automation

Dan Li

29-09-22

8:00

9:45

EB

Digitalization & cognitive automation

Dan Li

29-09-22

10:00

11:45

EB (online)

Sustainability Workshop (SVR)

Mélanie Despeisse

30-09-22

15:15

17:00

EA

Human-robot collaboration

Omkar Salunkhe

40

03-10-22

13:15

15:00

EF

Servitization

Business models for sustainable manufacturing

Clarissa González

03-10-22

15:15

17:00

EF

Report

Report Preparation

Clarissa González & Greta Braun & Hao Wang & Ninan Theradapuzha

06-10-22

8:00

11:45

EB (online)

Sustainability

Sustainability Seminar

Mélanie Despeisse

41

10-10-22

13:15

17:00

 

Company visit + Report

Emerson Study Visit

Emelie Vikingsson, Mats Rosander

13-10-22

08:00

11:45

 

Report + opposition preparation

 

14-10-22

15:15

17:00

EE

Presentation Preparation

Clarissa González & Greta Braun & Hao Wang & Ninan Theradapuzha

42

17-10-22

13:15

17:00

HA2

Final stretch

Final Project Presentation

Clarissa González & Greta Braun

20-10-22

10:00

10:45

EB

Summary of the course

Johan Stahre, Greta Braun

21-10-22

08:00

12:00

 

Exam

Johan Stahre & Greta Braun

 

LITERATURE

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

 

STUDENT REPRESENTATIVES