Implementation of Artificial Intelligence in Construction Project Scheduling

Abstract

This thesis investigates the potential of Artificial Intelligence (AI) in the field of construction project scheduling, which has traditionally relied on human and semi-automated approaches. The construction industry, which provides the foundation for economic growth and infrastructure advancement, encounters regular problems such as schedule delays and cost overruns, which are frequently intensified by traditional project management and scheduling procedures. With the emerging trend of AI, the construction industry is on its way to a big change. By implementing AI into project scheduling, there is a great possibility to not only reduce these frequent challenges, but also improve project planning and execution. However, as the construction industry adopts AI technologies, it faces challenges such as integration complexity, the need for new skill sets, and resistance to change from traditional practices. This study seeks to identify and highlight these challenges for transparent understanding. Additionally, our research delves into how AI fosters better collaboration and communication among project stakeholders. Keeping these objectives in mind, the following three research questions were developed to cover these objectives: (1) How does AI-powered scheduling differ from traditional scheduling methods and software in terms of efficiency, resource optimization, accuracy, and overall project management effectiveness? (2) What are the challenges construction projects can expect to encounter when implementing artificial intelligence technology into project scheduling? (3) How does the integration of AI technology in project scheduling influence and encourage collaboration and communication among stakeholders, such as project managers and contractors, during a construction project?

Our research, which included qualitative interviews and a thorough case study of the OYSTER Data Centre Project provided by CTS Nordics, offers insights into AI's efficiency, accuracy, and resource optimization capabilities for project scheduling. The results show that AI-powered scheduling surpasses traditional techniques in terms of decision-making, mistake reduction, and overall project management performance. Furthermore, the study investigates implementation challenges and the influence of AI on stakeholder collaboration and communication in construction projects.

The results highlight AI's ability to handle complex data and scenarios more efficiently than traditional tools, allowing for dynamic scheduling and real-time modifications, which are important in today's fast-paced construction industry. This thesis not only contributes to academic research but also gives practical insights for construction professionals considering using artificial intelligence to enhance project outcomes.