Modellering og simulering for bærekraftig drift 4.0 (OFF640)

Modelling and Simulation is the process of designing a model of a system and conducting simulation experiments to understand the behavior of the system and/or evaluate various strategies for the operation of the system. Modeling & Simulation has become an important tool in all phases of the acquisition process and can be used within most systems life cycle processes, including requirements analysis, architectural design, design, development, test, verification, operations, and maintenance. System dynamics is a rigorous modelling method that enables us to use computer simulations of complex systems in order to design more effective policies and strategies for greater success. Asset simulation helps to determine the impact of your business decisions before they were implemented into our technical systems.

This course teaches the skills required for understanding how the structure of complex systems creates their behaviour. Learning in a world of growing dynamic complexity requires us to become systems thinkers in order to expand the boundaries of our engineering and management models. Therefore, systems dynamics modelling is important for the analysis of policy and strategy, with a focus on business and engineering applications. The course is based on system development and dynamic modelling methodology. The course teaches the most commonly used simulation techniques: system dynamics simulation (continuous systems), discrete-event simulation, and agent-based modelling with help of the most well-known simulation packages e.g. AnyLogic, Vensim, Arena.


Dette er emnebeskrivelsen for studieåret 2023-2024

Fakta

Emnekode

OFF640

Versjon

1

Vekting (stp)

10

Semester undervisningsstart

Høst

Antall semestre

1

Vurderingssemester

Høst

Undervisningsspråk

Engelsk

Tilbys av
Timeplan

Vis timeplan

Innhold

The course provides understanding and knowledge of industrial systems modelling, discrete and continuous distribution models, discrete-event simulation, system dynamics simulation, the alternatives evaluation analysis, and Performance improvement analysis. Some of the psychological and judgmental aspects of how people understand dynamic behaviours of systems, under uncertain and complex decision situations, will be discussed.

Læringsutbytte

Knowledge

  • Understand the complexity of the modern systems behaviors and multi-disciplinary systems e.g. energy systems.
  • Gain an understanding of system thinking and its toolbox.
  • Gain the required knowledge of modelling deterministic and stochastic processes, entities, events, conditions, and queues of several production and service systems.
  • Gain the required knowledge of simulation analysis: discrete events, continuous dynamics, data collection, alternatives evaluation and comparison.
  • Gain good understanding of operating production, service and energy systems.

Skills

  • Able to develop the business process model for any production and service system.
  • Able to collect the required data sets and select the effective distribution models to simulate the dynamic behavior of the studied system.
  • Able to simulate the system performance based on key metrics such as costs, throughput, cycle times, equipment utilization, energy losses and resource availability.
  • Able to evaluate potential alternatives to determine the best approach to enhancing performance.
  • Determine the impact of uncertainty and variability on system performance.
  • Run "what-if" scenarios to evaluate proposed process changes.
  • Visualize results with 2D and 3D animation.

General competence

  • Acquire system-thinking, problem-solving, multi criteria - decision-making approach.

Forkunnskapskrav

Ingen

Eksamen / vurdering

Prosjektoppgave og muntlig presentasjon

Vurderingsform Vekting Varighet Karakter Hjelpemiddel
Prosjektoppgave 90/100 Bokstavkarakterer
Muntlig presentasjon 10/100 Bokstavkarakterer

Det er ikke kontinuasjonsmuligheter på prosjektoppgaven, dersom studenter ønsker å ta denne delen på nytt må vedkommende ta emnet på nytt neste gang det har ordinær undervisning.Studenter som ikke møter opp på presentasjonen kan ikke påregne å få ta denne delen på nytt. Dersom det foreligger gyldig fravær kan studenten etter avtale med faglærer gjennomføre presentasjonen på et senere tidspunkt.Studenter som ikke består en av vurderingsdelene, eller som ønsker å forbedre sin karakter, må ta alle vurderingsdeler på nytt innenfor samme semester for å oppnå en ny samlet karakter.

Vilkår for å gå opp til eksamen/vurdering

Self study/Group work, Obligatory written reports and oral presentations.

Fagperson(er)

Faglærer:

Idriss El-Thalji

Faglærer:

Jayantha Prasanna Liyanage

Emneansvarlig:

Idriss El-Thalji

Instituttleder:

Mona Wetrhus Minde

Arbeidsformer

Lectures, Lab/Case study work (Case-based learning), Self-study/Group work, and Interactive discussions.

Overlapping

Emne Reduksjon (SP)
Agentsimulering og digitale tvillinger (IAM640_1) 10

Åpent for

Industriell teknologi og driftsledelse - master i teknologi/siv.ing.

Emneevaluering

Det skal være en tidligdialog mellom emneansvarlig, studenttillitsvalgt og studentene. Formålet er tilbakemelding fra studentene for endringer og justering i emnet inneværende semester.I tillegg skal det gjennomføres en digital emneevaluering minimum hvert tredje år. Den har som formål å innhente studentenes erfaringer med emnet.

Litteratur

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