eMaintenance solution for enhanced asset management in railway – using industrial AI

The project aims to streamline and optimize asset management and rail maintenance, with a focus on railway infrastructure.

Goal

Develop AI solutions for the maintenance of railways

Project status and Results

The project aims to streamline and optimize asset management and rail maintenance, with a focus on railway infrastructure. From an academic perspective, the project will explore and investigate how technologies and methodologies in the so-called. 'Industrial Artificial Intelligence (IAI)', incl. deep learning, can be used to develop eMaintenance solutions that help to improve TAK, eng. OEE and streamline the infrastructure management of railway infrastructure.
The project builds on previous research results and obtained research findings carried out in the eMaintenance research area at Luleå University of Technology. The eMaintenance research aims to enable and facilitate complex data analyses in the operation and maintenance process.
This project will aim to design frameworks, approaches, technologies and methodologies based on 'Industrial AI' that contribute to fact-based decision support in operation and maintenance of railway infrastructure.
The project are performing a state of the art literature survey and state of the art review in the field of Railway infrastructure, Artificial intelligence and Machine Learning methodologies.

Researchers: Jaya Kumari (PhD candidate), Ramin Karim (PL), Miguel Castano
Sponsor: Trafikverket/JVTC
Duration: 2019-2023