Bibliographic details and abstracts are available to all. Downloads of full-text dissertations are restricted to University of Portsmouth members who must login. MPhils may be accessed by all.

Abstract

The integration of Building Information Modeling (BIM) and the Internet of Things (IoT) opens up disruptive capabilities for predictive maintenance in railway assets, with the potential to greatly improve cost control and asset longevity. This dissertation investigates how BIM and IoT technologies may work together to create a comprehensive framework for predictive maintenance in the railway industry.
Traditional maintenance approaches, which are primarily reactive or scheduled at regular intervals, frequently result in high costs and short asset lifespans due to inefficient resource allocation and unplanned downtime. This study suggests a proactive strategy to maintenance that takes advantage of BIM's detailed digital representations and IoT's real-time data collection capabilities in order to prevent breakdowns and improve asset performance.
The research looks into the present issues that are facing the railway asset management, focusing on the high costs and limited lifespan associated with traditional maintenance procedures. A predictive maintenance model is developed that takes advantage of BIM's detailed digital representations and IoT's real time data collection capabilities to identify and address probable issues before they occur.
Using both of qualitive and quantitively data collection as a mixed method research strategy, including a detailed literature review, case studies, and expert interviews, was employed to assess the feasibility and benefits of combining BIM with IoT for predictive maintenance in terms of cost control and life span.
The findings indicate that this integration between BIM and IoT can result in significant cost savings by minimizing unscheduled repair activities, streamlining maintenance schedules and optimizing resource allocation. Furthermore, the expanded monitoring and data analytics capabilities made possible by IoT assist to increasing the operating lifespan of railway assets by enabling prompt and targeted maintenance interventions.
This research emphasizes the potential of BIM and IoT to transform railway maintenance practices, providing stakeholders with a strong foundation for cost-effective and sustainable asset management.
The dissertation concludes with practical recommendations for industry implementation, as well as future research directions to improve and expand the predictive maintenance model.

Course: Building Information Management - MSc - P2697PTD

Date Deposited: 2025-01-16

URI/permalink: https://library.port.ac.uk/dissert/dis14643.html