Industrial Assets, Modern Uncertainties, and Performance Dynamics (IAM560)

The Course has a main focus on practically important technical themes within Industrial assets and engineering infrastructures, modern uncertainties and dynamics that they are exposed to, as well as decision making and performance under modern complex industrial conditions. The course has a more practical approach with various real world examples from many industrial sectors where assets, systems, and critical processes are continuously exposed to new industrial demands, modern performance challenges and new uncertainties due to new industrial forces, for instance industrial transformations, digitalization processes, societal and environmental impact, and sustainability concerns, etc. The course also covers simulation modelling and digital twin technology at the asset level (for example, entire production or service system) to enable and support more data-driven and model-based decisions based on a better understanding of complex performance dynamics of industrial assets and systems through various practical industrial scenarios.


Course description for study year 2025-2026. Please note that changes may occur.

Facts

Course code

IAM560

Version

1

Credits (ECTS)

10

Semester tution start

Spring

Number of semesters

1

Exam semester

Spring

Language of instruction

English

Content

The main content is based on the major changes and critical characteristics of modern industrial assets and engineering infrastructures from a real world perspective. It covers new uncertainties, challenging performance demands in modern industrial environments, and how complex processes influence different types of scenarios, decision settings, and performance indicators, etc., to manage; technical, operational, and overall performance demands of complex industrial assets, engineering infrastructures, systems, and critical processes in modern times.

The simulation engineering or simulation modelling process are utilized in the course for making simulation models (a digital prototype) of a system or process, which can be a process plant, production line, warehouse, transportation system, service centre or other systems. This allows identification of various performance patterns as well as resolving potential challenges and problems proactively. Use of simulation models as a valuable tool for identifying operational layouts and performance strategies is demonstrated, since it is becoming popular and important as a core element of digital twin technologies that has proven economic, societal, and environmental benefits.

Throughout the course, various practical industrial examples are used to emphasise on the real world industrial dynamics and inherent uncertainties of performance, mutual interdependencies to mitigate risks and to enhance value creation, as well as to discuss dilemmas between Industrial assets and performance challenges in modern complex industrial contexts.

Learning outcome

Knowledge

  • has knowledge on theories and methods that cover uncertainties, decisions, and performance, relating to modern industrial assets, engineering infrastuctures, systems, and critical processes
  • has knowledge and understanding on simulation engineering and simulation modelling processes related to complex industrial contexts based on systems thinking
  • can apply knowledge to modern industrial assets, engineering infrastuctures, systems, and critical processes for industrial risk mitigation and value creation purposes
  • can analyze professional problems and challenges related to technical and operational processes, decision making, and performance for economic, societal, and environmental benefits.

Skills

  • can use relevant methods, techniques, and understanding for research and professional development work relating to modern industrial assets, engineering infrastuctures, systems, and critical processes
  • can analyze and deal critically with various sources of information relating to modern industrial assets, engineering infrastuctures, systems, and critical processes and use them to structure and formulate scholarly arguments
  • can model, simulate, and analyse performance patterns of given industrial contexts based on sensitive performance features and metrices, using simulation engineering and simulation modelling techniques
  • can carry out a limited research or development project under supervision relating to modern industrial assets, engineering infrastuctures, systems, and critical processes and in accordance with applicable norms, standards, and practices.

General competence

  • can apply his/her knowledge and skills in new areas in order to carry out professional assignments and projects relating to modern industrial assets, engineering infrastuctures, systems, and critical processes
  • can communicate about academic issues, analyses and conclusions in the field in terms of uncertainties, decisions, and performance, relating to modern industrial assets, engineering infrastuctures, systems, and critical processes, both with specialists and the general public.
  • can contribute to new thinking and innovation processes for economic, societal, and environmental benefits.

Required prerequisite knowledge

None

Exam

Form of assessment Weight Duration Marks Aid
Report 1/1 3 Weeks Letter grades

The assignment is individual. There is no continuation possibility on the assignment. Students who do not pass the assignment can take this part again the next time the course has regular teaching.

Coursework requirements

Presentation in groups

Obligatory presentations based on Groupwork. If the group presentation is not approved, then the student will have the opportunity to deliver an individual report and to have an own oral assessment.

Obligatory requirements must be approved by responsible lecturer within the given deadline.

Course teacher(s)

Course teacher:

Idriss El-Thalji

Head of Department:

Mona Wetrhus Minde

Course coordinator:

Jayantha Prasanna Liyanage

Method of work

Lectures and discussions. Interactive groupwork. Presentations. Reports and Oral assessment when necessary.

Overlapping courses

Course Reduction (SP)
Decision Engineering and Performance Management (MOM440_1) 10
Industrial assets, Processes, and Performance under modern contexts (OFF560_1) 10

Open for

Admission to Single Courses at the Faculty of Science and Technology
Environmental Engineering - Master of Science Degree Programme Structural and Mechanical Engineering - Master of Science Degree Programme Industrial Asset Management - Master of Science Degree Programme Petroleum Engineering - Master of Science Degree Programme
Exchange programme at Faculty of Science and Technology

Course assessment

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.

Literature

Search for literature in Leganto