Knowledge management practices in Singapore’s tunnel industry

This article is part of an ongoing series looking at knowledge management (KM) in the building and construction industries.

Introduction

Having worked in the construction industry for several years, I have come to appreciate the direct impact of knowledge management (KM) on project execution, safety, and innovation. This article explores the role of KM in the Singapore tunnel industry, combining actual industry practice with academic perspectives. Singapore’s tunnel industry plays a key role in urban infrastructure construction, from Mass Rapid Transit (MRT) expansion to underground expressways. However, as projects grow in scale and complexity, KM has become essential for optimizing execution, reducing risks, and ensuring knowledge transfer. An effective KM system¹ must integrate both explicit knowledge, which is structured and documented, and tacit knowledge, which is experience-based and difficult to articulate.

Status of KM in Singapore’s tunnel industry

KM involves² the capture, storage, sharing and application of knowledge. In the long-term and high-risk field of tunnel construction, the core value of KM is reflected in:

• Experience retention – Documenting and transferring senior engineers’ expertise to guide future projects.
• Risk reduction – Improving construction safety and minimizing accidents through historical data analysis.
• Cross-agency collaboration – Facilitating information sharing among government agencies, contractors, and engineers.
• Technology integration – Utilizing artificial intelligence (AI) and enterprise resource planning (ERP) systems to enhance KM intelligence.

Knowledge in tunnel construction exists in two primary forms:

• Explicit knowledge – Formalized knowledge that can be documented, stored, and easily transferred, such as engineering drawings, technical manuals, and case databases.
• Tacit knowledge – Personal insights, hands-on skills, and experiential knowledge that is difficult to articulate and must be transferred through mentorship and on-site experience.

Singapore’s tunnel industry actively manages both knowledge types through structured digital tools and human-cantered approaches.

How KM optimized tunnel construction in Singapore

1. Digitalization of knowledge through BIM and ERP systems

Building information modelling (BIM) and ERP systems have become important tools for tunnel engineering management. BIM provides a structured knowledge storage system for sharing design and construction data, while the ERP system integrates key financial, scheduling, and resource knowledge to ensure best practices are accumulated and reused. For example: For the Thomson-East Coast Line project, Singapore’s Land Transport Authority (LTA) has adopted the BIM + ERP system to allow the design, construction and maintenance teams to share information in real time, thereby reducing errors and maximizing construction efficiency. Additionally, BIM and ERP also facilitate improved design and implementation, as well as minimizing errors.

In addition, the integration of BIM and ERP can also restrict repetitive information transmission and improve data accuracy. For example, during the tunnel construction process, the system can automatically verify whether there is any inconsistency between the design and the construction plan and inform relevant personnel. This intelligent KM strategy remarkably improves construction efficiency and reduces wastage.

2. Managing tacit knowledge through experience transfer

Tacit knowledge, such as soil stability assessment and groundwater control, is essential in tunnelling but hard to put on paper. Singapore facilitates this through:

• Mentorship programs – Pairing senior engineers with junior staff to transfer vital hands-on knowledge.
• Industry workshops – Hosting expert panels to share underground engineering experiences.
• Case databases – Documenting lessons learned from past projects to act as references for new project teams.

For example, in the Marina Coastal Expressway project, Singapore used expert interviews and historical case analysis to make sure that the team is able to learn from past successes and avoid known risks. As documented in similar projects by the Singapore Land Transport Authority (LTA), this KM-based approach not only improved project execution but also laid the foundation for future infrastructure development.

3. Risk optimization through knowledge analysis

By analyzing past accident data and geological conditions, knowledge-based systems can help organizations identify potential risks early³, as KM provides a framework for capturing and reusing experiential knowledge. For instance: in the Deep Tunnel Sewage System project, according to Public Utility Board (PUB) updates, the construction team used past geological data to predict possible problems in tunnel excavation and developed response plans in advance, reducing the risk of construction delays and cost overruns.

Additionally, by establishing an intelligent risk assessment model, construction teams can leverage AI technologies⁴ such as real-time visual and audio data analytics to identify potential risk points and generate proactive safety suggestions. For example, during the construction of the MRT tunnels, the AI system can monitor the construction environment in real time, such as detecting air quality detection, soil pressure, and water level fluctuations, and automatically issue warnings in the event of abnormalities. This data-driven KM method has greatly reduced engineering risks.

4. Establish an industry knowledge sharing network

In order to improve the KM level of the tunnel industry, Singapore has established a number of industry organizations, such as the Tunnelling and Underground Construction Society of Singapore (TUCSS). These organizations promote industry knowledge exchange through:

• Annual knowledge seminars – Sharing new technologies, materials and construction experience.
• Cross-industry cooperation – Encouraging joint research projects between engineering firms, universities, and government bodies.

The government’s Smart Construction Initiative further enhances knowledge accessibility by standardizing data-sharing frameworks, making industry-wide KM more efficient.

Challenges of KM

Despite the huge application value of KM in the tunnel industry, the following challenges still exist:

• ׇKnowledge protection – Competitive pressure makes contractors reluctant to disclose their construction experience.
• Data fragmentation – Project data is scattered in different departments and lacks a unified management platform.
• Technology adaptation – Continuous investment of resources is needed to train engineers to use the new generation of KM tools.

Managing tacit knowledge presents additional challenges:

• Difficulty in documentation – Many insights are learned through experience and cannot be easily written down.
• Knowledge retention risks – When senior engineers retire, undocumented knowledge may be lost.

Future development of KM in tunnel industry

In the future, the tunnel industry can deepen KM through the following ways:

• AI-driven knowledge base – Automatically categorizing and analyzing engineering knowledge for better retrieval.
• Augmented reality (AR) training – Simulating tunnel construction environments to help engineers gain practical experience.
• Blockchain technology – Securing intellectual property and proprietary engineering techniques to encourage knowledge sharing.

Conclusion

The application of KM in Singapore’s tunnel industry has achieved initial results, helping to improve project collaboration efficiency, optimize construction safety, and ensure long-term knowledge inheritance. In the future, with the development of new technologies, a new generation of KM systems combined with tools such as AI, BIM, and ERP will further promote industry progress. To ensure continuous optimization, industry stakeholders should continue to explore new KM methods and strengthen cross-organizational cooperation to promote the long-term sustainable development of tunnel projects.

Our lecturer Rajesh Dhillon has recognized several key directions for KM in MRT and tunnel works. He emphasizes the need for effective knowledge transfer to enhance safety resilience, reduce risks, and deliver operations continuity. His findings suggest the promise of AI-enabled safety assessment models, BIM-enabled collaboration, and standardized digital KM tools in improving safety, coordination, and decision-making. He also suggests the adoption of advanced technologies such as augmented reality (AR)-based training and blockchain-based knowledge pools to develop a future-proof workforce in metro operations.

Article source: Adapted from Knowledge Management practices in Singapore’s tunnel industry, prepared as part of the requirements for completion of course KM6304 Knowledge Management Strategies and Policies in the Nanyang Technological University Singapore Master of Science in Knowledge Management (KM).

Artificial intelligence (AI) statement: This article was prepared with the assistance of ChatGPT to support clarity, formatting, and reference integration. Final content reflects the author’s judgment.

Header image source: Photo taken by the author, 2025.

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