"An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition, planning and cost"
- Submitting institution
-
Cranfield University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 19629775
- Type
- D - Journal article
- DOI
-
10.1016/j.trc.2018.02.010
- Title of journal
- Transportation Research Part C: Emerging Technologies
- Article number
- -
- First page
- 234
- Volume
- ="89"
- Issue
- ="April"
- ISSN
- 0968-090X
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
9
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This research led to ten more research contracts (£1.2M) under Shift2Rail, mostly with Network Rail: In2Smart 730569 13453/02/6559 Rail Robot Demonstrator and Cobots; 13451/02/6559 Simulations and V&V for Railway Inspection and Repair System (RIRS); 11032/02/6559 Non-contact system for detecting rail defects; In2Track 730841: 3441804 Self-adjusting Switches and Crossings; In2Smart 2 881574: 22245/02/6559, System Integration; In2Track 2 826255: ECM22352, Autonomous Track Geometry Repair, ECM21659, Autonomous ultrasonic testing, Remote monitoring of rail defects, Whole system design of next generation Switches and Crossings (with SNCF); and two funded PhD projects on infrastructure systems and inspection. (Principal Engineer, Contact Details: Audit_file_19629775).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
