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Industrial Asset Management

Smart Asset, Operation Technology and Maintenance Analytics.

Publisert: Endret:
Facts
Professors

3

PhD fellows

3

Running projects

2

We research on how to enable industry to gain the benefits of Industry 4.0 transformation, through three tracks.

  1. Smart Asset: Dependability Engineering to design industrial asset that are dependable and ready for Maintenance Analytics. 
  1. Smart Operations: Model-based Systems Engineering of the enabling technologies to “fit to purpose”, specially, Digital Twin, Autonomous Vehicle, Augmented reality.  
  1. Smart Maintenance: Maintenance Analytics (Diagnostic, Predictive, Prescriptive) and simulation modelling to enable data-driven decision making. 

Maintenance Analytics and Dependability Engineering for Industrial Transformation (MADE 4 IT) 

Simply, we have three main research questions: 

  • How to design the asset and operations to be ready for Industry 4 transformation? Validity 
  • How much a specific industrial technology fit to the purpose? Effectiveness 
  • What is the value and benefit of applying Industry 4.0 technologies? Feasibility 

In our research group, these three questions are applied on several industry technologies for different industrial sectors (Oil and gas, Offshore wind, Tunnel, etc.): Condition based maintenance, Predictive Maintenance, Digital twin, Model-based systems engineering, etc. 

  • For the 1st research question, we are applying case study methodology, where we try to design smart asset and operations at the industry and extracted a generic models (Project execution models and analytical study worksheets).  
  • For the 2nd research question, we are applying experimental testing methodology at our IAM lab.  
  • For the 3rd research question, we usually apply simulation modelling approach to predict the potential impacts (positive and negative) of applying specific technology in a specific context. Our simulation models are at the asset level (using Anylogic). 

Projects

Predictive Maintenance Modelling for Production Critical Equipment

2018-2022, GASSCO

Data Driven Decisions

2022-2025, Kairos

Educating graduates for applying Industry 4.0

2019-2022, Diku Eurasia Program

Research themes

5 projects

1 project

1 project

1 project

1 project

1 project

UN Sustainable Goals

Lab facilities

Lab facts
Instruments

x

Methods

x

Researchers

Professor
51831440
Faculty of Science and Technology

Department of Mechanical and Structural Engineering and Materials Science
Førsteamanuensis
Faculty of Science and Technology

Department of Mechanical and Structural Engineering and Materials Science
Førsteamanuensis
51832794
Faculty of Science and Technology

Department of Mechanical and Structural Engineering and Materials Science
Stipendiat
Faculty of Science and Technology

Department of Mechanical and Structural Engineering and Materials Science

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