Master of Science in Industrial Engineering and Operations Research
EUR-ACE® Master (EURopean ACcredited Engineering Master)
The EUR-ACE label was accredited to this programme by the Commission des titres d’ingénieur (CTI), under the auspices of the European Network for Accreditation of Engineering Education (ENAEE).
EUR-ACE® is a framework and accreditation system that provides a set of standards that identifies high-quality engineering degree programmes in Europe and abroad.
EUR-ACE® Master (EURopean ACcredited Engineering Master)
The EUR-ACE label was accredited to this programme by the Commission des titres d’ingénieur (CTI), under the auspices of the European Network for Accreditation of Engineering Education (ENAEE).
EUR-ACE® is a framework and accreditation system that provides a set of standards that identifies high-quality engineering degree programmes in Europe and abroad.
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
1
|
sem 1
|
nl
|
El-Houssaine Aghezzaf
|
6
|
|
|
1
|
sem 1
|
nl
|
Stijn De Vuyst
|
6
|
|
|
1
|
sem 1
|
nl
|
Birger Raa
|
6
|
|
|
1
|
sem 1
|
nl
|
Sofie Verbrugge
|
6
|
|
|
1
|
sem 2
|
nl
|
El-Houssaine Aghezzaf
|
6
|
|
|
1
|
sem 2
|
nl
|
Michiel Vlaminck
|
3
|
|
|
1
|
sem 1
|
nl
|
Sidharta Gautama
|
3
|
|
|
1
|
sem 1
|
nl
|
Birger Raa
|
6
|
|
|
1
|
sem 2
|
nl
|
Dieter Claeys
|
6
|
|
|
1
|
sem 2
|
nl
|
Stijn De Vuyst
|
6
|
|
|
1
|
sem 1
|
nl
|
Dieter Claeys
|
6
|
|
Students take either 15 credit units from module 2.1 (in-depth elective courses) or the Minor Artificial Intelligence of at least 18 credit units. Supplement with course units from the other modules.
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
|
sem 2
|
nl
|
Mario Pickavet
|
4
|
|
|
|
sem 1
|
en
|
Clara-Mihaela Ionescu
|
6
|
|
|
|
sem 1
|
nl
|
Joris Walraevens
|
6
|
|
|
|
sem 1
|
nl
|
Joni Dambre
|
6
|
|
|
|
sem 2
|
nl
|
Guillaume Crevecoeur
|
6
|
|
|
|
sem 2
|
nl
|
Mia Loccufier
|
6
|
|
|
|
sem 1
|
en
|
Heidi Steendam
|
6
|
|
|
|
sem 1
|
en
|
Hiep Luong
|
6
|
|
|
|
sem 1
|
en
|
Dieter De Witte
|
4
|
|
|
|
sem 2
|
en
|
Sidharta Gautama
|
6
|
|
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
|
sem 1
|
en
|
Joni Dambre
|
6
|
|
|
|
sem 2
|
en
|
Aleksandra Pizurica
|
4
|
|
|
|
sem 2
|
en
|
Toon De Pessemier
|
6
|
|
|
|
sem 1
|
en
|
Heidi Steendam
|
6
|
|
|
|
sem 1
|
en
|
Jefrey Lijffijt
|
3
|
|
|
|
sem 1
|
en
|
Dieter De Witte
|
4
|
|
|
|
sem 2
|
en
|
Dieter De Witte
|
3
|
|
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
|
year
|
nl,en
|
Patrick Segers
|
6
|
|
|
|
year
|
en
|
Patrick Segers
|
6
|
|
|
|
year
|
en
|
Patrick Segers
|
3
|
|
|
|
year
|
nl,en
|
|
6
|
|
|
|
year
|
nl,en
|
|
3
|
|
|
|
sem 2
|
en
|
Mario Vanhoucke
|
6
|
|
|
|
sem 2
|
nl
|
Jos Knockaert
|
3
|
|
|
|
sem 2
|
nl
|
Erik Mannens
|
3
|
|
|
|
sem 2
|
nl
|
Jochen Maes
|
6
|
|
|
|
sem 2
|
en
|
Katrien Verleye
|
3
|
|
|
|
sem 2
|
en
|
Johan Verrue
|
4
|
|
|
|
sem 1
|
nl
|
Stijn Baert
|
5
|
|
|
|
sem 1
|
nl
|
Freddy Heylen
|
6
|
|
|
|
sem 2
|
nl
|
Bart Wille
|
5
|
|
|
|
sem 1
|
nl
|
Diederik Bruloot
|
3
|
|
|
|
sem 2
|
en
|
Mieke Audenaert
|
4
|
|
|
|
sem 2
|
en
|
Virginie Mataigne
|
6
|
|
|
|
sem 1
|
en
|
Michael Frömmel
|
6
|
|
|
|
sem 2
|
en
|
Frederik Gailly
|
4
|
|
UKV
|
|
year
|
nl
|
Elisabeth De Schauwer
|
3
|
|
|
|
sem 1
|
nl
|
Kim Verbeken
|
3
|
|
|
|
sem 2
|
nl
|
Lode Daelemans
|
3
|
|
|
|
sem 1
|
en
|
Luc Martens
|
3
|
|
|
|
sem 1
|
nl
|
Wim Notebaert
|
3
|
|
UKV
|
|
sem 2
|
nl
|
Veerle Segers
|
3
|
|
|
|
sem 2
|
en
|
Bernard Mazijn
|
5
|
|
|
|
sem 2
|
en
|
Koen De Turck
|
5
|
|
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
2
|
sem 1
|
nl
|
Birger Raa
|
6
|
|
Students take either 15 credit units from module 2.1 (in-depth elective courses) or the Minor Artificial Intelligence of at least 18 credit units. Supplement with course units from the other modules.
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
|
sem 2
|
nl
|
Mario Pickavet
|
4
|
|
|
|
sem 1
|
en
|
Clara-Mihaela Ionescu
|
6
|
|
|
|
sem 1
|
nl
|
Joris Walraevens
|
6
|
|
|
|
sem 1
|
nl
|
Joni Dambre
|
6
|
|
|
|
sem 2
|
nl
|
Guillaume Crevecoeur
|
6
|
|
|
|
sem 2
|
nl
|
Mia Loccufier
|
6
|
|
|
|
sem 1
|
en
|
Heidi Steendam
|
6
|
|
|
|
sem 1
|
en
|
Hiep Luong
|
6
|
|
|
|
sem 1
|
en
|
Dieter De Witte
|
4
|
|
|
|
sem 2
|
en
|
Sidharta Gautama
|
6
|
|
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
|
sem 1
|
en
|
Joni Dambre
|
6
|
|
|
|
sem 2
|
en
|
Aleksandra Pizurica
|
4
|
|
|
|
sem 2
|
en
|
Toon De Pessemier
|
6
|
|
|
|
sem 1
|
en
|
Heidi Steendam
|
6
|
|
|
|
sem 1
|
en
|
Jefrey Lijffijt
|
3
|
|
|
|
sem 1
|
en
|
Dieter De Witte
|
4
|
|
|
|
sem 2
|
en
|
Dieter De Witte
|
3
|
|
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
|
year
|
nl,en
|
Patrick Segers
|
6
|
|
|
|
year
|
en
|
Patrick Segers
|
6
|
|
|
|
year
|
en
|
Patrick Segers
|
3
|
|
|
|
year
|
nl,en
|
|
6
|
|
|
|
year
|
nl,en
|
|
3
|
|
|
|
sem 2
|
en
|
Mario Vanhoucke
|
6
|
|
|
|
sem 2
|
nl
|
Jos Knockaert
|
3
|
|
|
|
sem 2
|
nl
|
Erik Mannens
|
3
|
|
|
|
sem 2
|
nl
|
Jochen Maes
|
6
|
|
|
|
sem 2
|
en
|
Katrien Verleye
|
3
|
|
|
|
sem 2
|
en
|
Johan Verrue
|
4
|
|
|
|
sem 1
|
nl
|
Stijn Baert
|
5
|
|
|
|
sem 1
|
nl
|
Freddy Heylen
|
6
|
|
|
|
sem 2
|
nl
|
Bart Wille
|
5
|
|
|
|
sem 1
|
nl
|
Diederik Bruloot
|
3
|
|
|
|
sem 2
|
en
|
Mieke Audenaert
|
4
|
|
|
|
sem 2
|
en
|
Virginie Mataigne
|
6
|
|
|
|
sem 1
|
en
|
Michael Frömmel
|
6
|
|
|
|
sem 2
|
en
|
Frederik Gailly
|
4
|
|
UKV
|
|
year
|
nl
|
Elisabeth De Schauwer
|
3
|
|
|
|
sem 1
|
nl
|
Kim Verbeken
|
3
|
|
|
|
sem 2
|
nl
|
Lode Daelemans
|
3
|
|
|
|
sem 1
|
en
|
Luc Martens
|
3
|
|
|
|
sem 1
|
nl
|
Wim Notebaert
|
3
|
|
UKV
|
|
sem 2
|
nl
|
Veerle Segers
|
3
|
|
|
|
sem 2
|
en
|
Bernard Mazijn
|
5
|
|
|
|
sem 2
|
en
|
Koen De Turck
|
5
|
|
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
2
|
year
|
nl
|
|
24
|
|
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
1
|
sem 1
|
nl
|
El-Houssaine Aghezzaf
|
6
|
|
|
1
|
sem 1
|
nl
|
Stijn De Vuyst
|
6
|
|
|
1
|
sem 1
|
nl
|
Birger Raa
|
6
|
|
|
1
|
sem 1
|
nl
|
Sofie Verbrugge
|
6
|
|
|
1
|
sem 2
|
nl
|
El-Houssaine Aghezzaf
|
6
|
|
|
1
|
sem 2
|
nl
|
Michiel Vlaminck
|
3
|
|
|
1
|
sem 1
|
nl
|
Sidharta Gautama
|
3
|
|
|
1
|
sem 1
|
nl
|
Birger Raa
|
6
|
|
|
1
|
sem 2
|
nl
|
Dieter Claeys
|
6
|
|
|
1
|
sem 2
|
nl
|
Stijn De Vuyst
|
6
|
|
|
1
|
sem 1
|
nl
|
Dieter Claeys
|
6
|
|
|
2
|
sem 1
|
nl
|
Birger Raa
|
6
|
|
Students take either 15 credit units from module 2.1 (in-depth elective courses) or the Minor Artificial Intelligence of at least 18 credit units. Supplement with course units from the other modules.
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
|
sem 2
|
nl
|
Mario Pickavet
|
4
|
|
|
|
sem 1
|
en
|
Clara-Mihaela Ionescu
|
6
|
|
|
|
sem 1
|
nl
|
Joris Walraevens
|
6
|
|
|
|
sem 1
|
nl
|
Joni Dambre
|
6
|
|
|
|
sem 2
|
nl
|
Guillaume Crevecoeur
|
6
|
|
|
|
sem 2
|
nl
|
Mia Loccufier
|
6
|
|
|
|
sem 1
|
en
|
Heidi Steendam
|
6
|
|
|
|
sem 1
|
en
|
Hiep Luong
|
6
|
|
|
|
sem 1
|
en
|
Dieter De Witte
|
4
|
|
|
|
sem 2
|
en
|
Sidharta Gautama
|
6
|
|
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
|
sem 1
|
en
|
Joni Dambre
|
6
|
|
|
|
sem 2
|
en
|
Aleksandra Pizurica
|
4
|
|
|
|
sem 2
|
en
|
Toon De Pessemier
|
6
|
|
|
|
sem 1
|
en
|
Heidi Steendam
|
6
|
|
|
|
sem 1
|
en
|
Jefrey Lijffijt
|
3
|
|
|
|
sem 1
|
en
|
Dieter De Witte
|
4
|
|
|
|
sem 2
|
en
|
Dieter De Witte
|
3
|
|
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
|
year
|
nl,en
|
Patrick Segers
|
6
|
|
|
|
year
|
en
|
Patrick Segers
|
6
|
|
|
|
year
|
en
|
Patrick Segers
|
3
|
|
|
|
year
|
nl,en
|
|
6
|
|
|
|
year
|
nl,en
|
|
3
|
|
|
|
sem 2
|
en
|
Mario Vanhoucke
|
6
|
|
|
|
sem 2
|
nl
|
Jos Knockaert
|
3
|
|
|
|
sem 2
|
nl
|
Erik Mannens
|
3
|
|
|
|
sem 2
|
nl
|
Jochen Maes
|
6
|
|
|
|
sem 2
|
en
|
Katrien Verleye
|
3
|
|
|
|
sem 2
|
en
|
Johan Verrue
|
4
|
|
|
|
sem 1
|
nl
|
Stijn Baert
|
5
|
|
|
|
sem 1
|
nl
|
Freddy Heylen
|
6
|
|
|
|
sem 2
|
nl
|
Bart Wille
|
5
|
|
|
|
sem 1
|
nl
|
Diederik Bruloot
|
3
|
|
|
|
sem 2
|
en
|
Mieke Audenaert
|
4
|
|
|
|
sem 2
|
en
|
Virginie Mataigne
|
6
|
|
|
|
sem 1
|
en
|
Michael Frömmel
|
6
|
|
|
|
sem 2
|
en
|
Frederik Gailly
|
4
|
|
UKV
|
|
year
|
nl
|
Elisabeth De Schauwer
|
3
|
|
|
|
sem 1
|
nl
|
Kim Verbeken
|
3
|
|
|
|
sem 2
|
nl
|
Lode Daelemans
|
3
|
|
|
|
sem 1
|
en
|
Luc Martens
|
3
|
|
|
|
sem 1
|
nl
|
Wim Notebaert
|
3
|
|
UKV
|
|
sem 2
|
nl
|
Veerle Segers
|
3
|
|
|
|
sem 2
|
en
|
Bernard Mazijn
|
5
|
|
|
|
sem 2
|
en
|
Koen De Turck
|
5
|
|
Course | Ref | MT1 | Semester | Language | Instructor | Crdt |
---|---|---|---|---|---|---|
|
2
|
year
|
nl
|
|
24
|
|
- Master and apply advanced knowledge in the own engineering discipline in solving complex problems.
- Apply Computer Aided Engineering (CAE) tools and advanced communication instruments in a creative and purposeful way.
- Have a thorough knowledge of fundamental fields of industrial systems engineering such as company- and production management, corporate finance, time study and methods engineering, operations research, quality measurement techniques and ICT.
- Have a thorough knowledge of supporting fields of industrial systems engineering such as cost price evaluation, investment analysis, project management and ergonomics.
- Master and apply advanced industrial engineering techniques in industrial production, logistics, service sectors and administrative and management processes.
- Have a thorough knowledge of the advanced mathematical and statistical foundations of production systems and business processes.
- Master and apply advanced operational research techniques to the field of production and logistic systems and in operational business processes.
- Analyse complex problems and translate them into concrete research questions.
- Consult the scientific literature as part of the own research.
- Select and apply the appropriate models, methods and techniques.
- Develop and validate mathematical models and methods.
- Interpret research findings in an objective and critical manner.
- Analyse business processes under the circumstances of variability and uncertainty through the use of mathematical optimisation, simulation and statistical techniques.
- Calculate and follow up the costs and benefits of projects and project proposals, taking the uncertainty and impreciseness of data into account adequately.
- Autonomously develop optimisation and simulation models for complex industrial systems.
- Creatively develop optimisation and simulation models for realistic industrial systems.
- Independently form an opinion on complex situations and problems, and defend this point of view.
- Apply knowledge in a creative, purposeful and innovative way to research, conceptual design and production.
- Critically reflect on one’s own way of thinking and acting, and understand the limits of one’s competences.
- Stay up‐to‐date with the evolutions in the discipline to elevate the own competences to expert level.
- Readily adapt to changing professional circumstances.
- Show a holistic conception about the role of the human factor in company processes in order to effectively put the planned process improvements into practice.
- Show a holistic conception about the role of technology in business processes in order to effectively put the planned process improvements into practice.
- Have the ability to communicate in English about the own field of specialisation.
- Project management: have the ability to formulate objectives, report efficiently, keep track of targets, follow the progress of the project,...
- Have the ability to work as a member of a team in a multi‐disciplinary working‐environment, as well as being capable of taking on supervisory responsibilities.
- Report on technical or scientific subjects verbally, in writing and using graphics.
- Work together with colleagues from the own and other fields of expertise as well as with technical and assisting staff.
- Provide a training in the developed working methods to the involved assisting staff, bearing in mind multidisciplinary aspects.
- Act in an ethical, professional and social way.
- Recognize the most important business and legal aspects of the own engineering discipline.
- Understand the historical evolution of the own engineering discipline and its social relevance.
- Integrate social and societal impacts of new industrial and technological developments into business strategies, systems and processes.
- Master the complexity of technical systems by using system and process models.
- Reconcile conflicting specifications and prior conditions in a high‐quality and innovative concept or process.
- Synthesize incomplete, contradictory or redundant data into useful information.
- Possess sufficient ready knowledge and understanding to evaluate the results of complex calculations, or make approximate estimates.
- Pay attention to entire life cycles of systems, machines, and processes.
- Pay attention to sustainability, energy‐efficiency, environmental cost, use of raw materials and labour costs.
- Pay attention to all aspects of reliability, safety, and ergonomics.
- Have insight into and understanding of the importance of entrepreneurship.
- Show perseverance, innovativeness, and an aptitude for creating added value.
- Continuously and critically analyse and optimise the stages a product completes in order to improve the efficiency of business processes.
- Design and improve operational systems that generate products and services, based on scientific principles.
- Plan and clearly describe operational duties that employees have to perform, taking into consideration the necessary machinery and resources.
- Develop methods that allow to design new goods and services, avoiding any waste of resources.