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Abstract

The Architecture, Engineering, and Construction (AEC) industry is increasingly adopting digital technologies to enhance efficiency and decision-making processes. This dissertation explores the implementation of Big Data and Internet of Things (IoT) technologies in off-site manufacturing (OSM) environments, focusing on their application in the pre-construction. The study aims to develop a comprehensive framework for optimising component design and production in OSM using these advanced technologies.
The research employs a mixed-methods approach, combining an extensive literature review and focus group surveys. The literature review examines the current state of Big Data and IoT adoption in OSM, performance assessment methods for off-site constructed assets, and existing approaches to optimising off-site components using operational data. Based on this review, a conceptual framework is developed outlining key components for implementing IoT and Big Data in OSM. Focus group surveys are then conducted to validate the proposed framework.
Key findings highlight the potential of Big Data and IoT technologies to enhance decision-making in OSM processes, improve supply chain management, and enable real-time monitoring of manufacturing processes. The research identifies critical components for successful implementation, including IoT sensors and RFID tags for data collection, edge computing for data processing, cloud-based platforms for data storage, Big Data analysis, and blockchain for secure data sharing.
The study also reveals challenges in data management, standardisation, and workforce adaptation that need to be addressed for successful implementation. The validated conceptual framework provides a roadmap for leveraging advanced technologies to improve efficiency, quality, and sustainability in off-site construction processes.
This research contributes to the body of knowledge by proposing a novel approach to leveraging operational data to optimise off-site components. The findings have implications for both industry practitioners and researchers, providing a foundation for future studies on data-driven decision-making in off-site manufacturing and the broader AEC industry.

Course: Building Information Management - MSc - P2657FTC

Date Deposited: 2025-01-17

URI/permalink: https://library.port.ac.uk/dissert/dis14687.html