Digital Twin for Train Maintenance
Lead Research Organisation:
Brunel University London
Department Name: Mechanical and Aerospace Engineering
Abstract
The aim of this research is to advance the methods and knowledge for planning and scheduling train maintenance through the use of digital twinning technologies.
Architecture pattern for a Digital Twin
There exist two system architecture patterns, namely server-based and edge-based
Communication latency requirement for a Digital Twin
The application scenario determines the required communication latency between a physical device and its Digital Twin.
Data capture mechanism
Two common methods can be used to gather data from physical devices, i.e., capturing changes and taking snapshots.
Functionalities of a Digital Twin
Existing Digital Twin applications are mainly developed for monitoring and prediction purposes.
Digital Twin model version management
A Digital Twin model can evolve over time as a result of engineering changes to its physical counterpart.
RESEARCH QUESTIONS
Q3: What is the impact of carrying out regular train maintenance even if some of it not needed?
Q4: What is the impact of using Digital Twin for train maintenance?
Q5: How could Digital Twine be adapted quicker in rail industry?
ENGINEERING METHODOLOGY
Literature study
Standard literature for existing research will be carried out
Cost-benefit analysis
The assessment of cost and benefits for using digital twin will be compared with the current cost been used IF there is a possibility to obtain the current cost for train maintenance.
Computational design, simulation and/or Lab experiment
Any designed models or suggested ones will be designed using various CAD software and tested using simulation or lab experiments. The result will be validated by testing it again in real depot for maintenance
Mathematical modelling (Optimization)
A mixed integer optimization model could be developed in an iterative approach, by documenting the mathematical formulation and coding it in Python, using OR-Tools as modelling layer and Gurobi as optimization solver.
Novel physical sciences
BACKGROUND
Today transport operators are facing new challenges, with the increase of number of passengers and the growing need for extra service provision, at the same time they have budgetary constraints, in order to meet the demand. One solution for meeting these new challenges is to improve maintenance and adapt the new technologies for maintenance (Digital Twin for maintenance). The term Digital Twin (DT) was brought to the general public for the first time in Shafto et al. (2010) and Shafto et al. (2012). A digital twin is a "live", evolving digital replica of the historical and current behavior of a physical object or process that helps optimize business performance. Digital Twin in the technological world is acting as a mirror in the real world (Glaessgen & Stargel, 2012
Architecture pattern for a Digital Twin
There exist two system architecture patterns, namely server-based and edge-based
Communication latency requirement for a Digital Twin
The application scenario determines the required communication latency between a physical device and its Digital Twin.
Data capture mechanism
Two common methods can be used to gather data from physical devices, i.e., capturing changes and taking snapshots.
Functionalities of a Digital Twin
Existing Digital Twin applications are mainly developed for monitoring and prediction purposes.
Digital Twin model version management
A Digital Twin model can evolve over time as a result of engineering changes to its physical counterpart.
RESEARCH QUESTIONS
Q3: What is the impact of carrying out regular train maintenance even if some of it not needed?
Q4: What is the impact of using Digital Twin for train maintenance?
Q5: How could Digital Twine be adapted quicker in rail industry?
ENGINEERING METHODOLOGY
Literature study
Standard literature for existing research will be carried out
Cost-benefit analysis
The assessment of cost and benefits for using digital twin will be compared with the current cost been used IF there is a possibility to obtain the current cost for train maintenance.
Computational design, simulation and/or Lab experiment
Any designed models or suggested ones will be designed using various CAD software and tested using simulation or lab experiments. The result will be validated by testing it again in real depot for maintenance
Mathematical modelling (Optimization)
A mixed integer optimization model could be developed in an iterative approach, by documenting the mathematical formulation and coding it in Python, using OR-Tools as modelling layer and Gurobi as optimization solver.
Novel physical sciences
BACKGROUND
Today transport operators are facing new challenges, with the increase of number of passengers and the growing need for extra service provision, at the same time they have budgetary constraints, in order to meet the demand. One solution for meeting these new challenges is to improve maintenance and adapt the new technologies for maintenance (Digital Twin for maintenance). The term Digital Twin (DT) was brought to the general public for the first time in Shafto et al. (2010) and Shafto et al. (2012). A digital twin is a "live", evolving digital replica of the historical and current behavior of a physical object or process that helps optimize business performance. Digital Twin in the technological world is acting as a mirror in the real world (Glaessgen & Stargel, 2012
Organisations
People |
ORCID iD |
| Mark Atherton (Primary Supervisor) | |
| Mohamed Ammar (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R512990/1 | 30/09/2018 | 29/09/2023 | |||
| 2337577 | Studentship | EP/R512990/1 | 01/11/2019 | 30/03/2023 | Mohamed Ammar |
| EP/T518116/1 | 30/09/2020 | 29/09/2025 | |||
| 2337577 | Studentship | EP/T518116/1 | 01/11/2019 | 30/03/2023 | Mohamed Ammar |