Skip to main content
Green Ports Toolkit
Southeast Asia · Case study

PSA Singapore, Digital Maintenance Planning at Tuas Port

Singapore2019 to 2025 (plans announced 2019; system reported 2023)

PSA Singapore, part of the PSA International group, operates container and multipurpose terminals at the City Terminals, Pasir Panjang Terminals, Tuas Port, Pasir Panjang Automobile Terminal, Sembawang Wharves and Jurong Island Terminal (PSA Singapore, n.d.). PSA describes Tuas Port as the world's largest fully automated container terminal. Its first Phase 1 berths began operating in 2021, and it is planned to handle 65 million TEU a year when fully completed in the 2040s (PSA Singapore, n.d.).

Approach

Plan maintenance capability at the design stage. When it announced Tuas Port in October 2019, PSA said the port would integrate predictive and prescriptive maintenance capabilities to reduce equipment downtime and increase the productivity of its engineering team. It described predictive maintenance as using sensors and data analysis to pre-empt and prevent failures on a specific asset before they occur (PSA International, 2019).

Use one system for infrastructure and critical crane components. PSA Singapore developed Next Gen Maximo to plan and track maintenance of infrastructure assets, and to track the component life of hundreds of critical components on Tuas Port quay cranes (PSA International, 2023b). Maximo is the name of IBM's asset and facilities management software, which brings maintenance, inspections and reliability together in one system (IBM, n.d.). PSA's report does not describe how its version was built.

  • Use crane sensor data. At a 2018 technology showcase, PSA described quay cranes undergoing regular preventive maintenance, with sensors on each crane providing data that, with machine learning, can better predict failure times (Maritime Executive, 2018).
  • Move from scheduled to predictive maintenance. In 2025, PSA was reported as using AI for anomaly detection in crane equipment and components, allowing proactive maintenance, as operational data enables a shift from scheduled to predictive maintenance (Maritime Gateway, 2025).
  • Reach hard-to-access parts. PSA also planned to co-develop autonomous aerial and underwater drones with specialist partners to detect and rectify faults in hard-to-access parts (PSA International, 2019).

Results

PSA has not published outcome data, such as crane availability, downtime or maintenance cost, for Next Gen Maximo or its predictive maintenance work. The sources describe capabilities and intentions rather than measured results.

Transferability

DMC ports can start with a computerized maintenance management system that covers both infrastructure and the critical components of their most important equipment, such as quay cranes. Sensors and predictive analytics can be added once asset records are reliable.

Ports building new terminals can plan their maintenance data needs at the design stage, as PSA did for Tuas.

Because PSA does not publish outcome data, ports adopting a similar approach should set their own baseline measures for availability and maintenance cost.

Sources

All information used for this case study was based on publicly available resources.