Preventive and Predictive Maintenance

Preventive and predictive maintenance proactively services and monitors port assets to prevent failures, optimize performance, and reduce environmental risks. Preventive maintenance involves scheduled inspections and servicing based on time or usage intervals. Predictive maintenance uses condition monitoring (including vibration, temperature, corrosion, and oil analysis) and data analytics to anticipate failures before they occur.

For DMC ports, preventive and predictive maintenance can prevent leaks, spills, and pollution incidents, maintain energy efficiency of equipment, reduce the need for emergency repairs with higher impacts, extend asset life, and help ensure reliable operation of environmental controls. Mobile inspection applications can support preventive maintenance programs for smaller or remote ports with limited on site engineering capacity.

Preventive and predictive maintenance together form the basis of modern asset management in ports. ISO 55001:2024 Asset management - Asset management system - Requirements provides an international framework for managing physical assets throughout their lifecycle, covering planning, implementation, operation, and continual improvement (ISO, 2024). Adoption of ISO 55001 can provide a systematic approach to balancing asset performance, risk, and cost.

Preventive maintenance is based on scheduled intervals (time based) or accumulated usage (usage based) and includes, among others, inspection of fuel systems, pipelines, and storage facilities; servicing of cargo handling equipment; maintenance of stormwater treatment and pollution control equipment; and inspection of submerged structures and quay walls. Maintenance of environmental controls, such as oil water separators and dust suppression systems, directly affects environmental performance.

Predictive maintenance uses sensor data and analytics to identify developing faults before they cause equipment failure. Technologies include, among others, vibration monitoring for rotating equipment, infrared thermography for electrical and mechanical systems, oil analysis for lubricated equipment, ultrasonic testing for leaks, and corrosion monitoring for steel and concrete structures. Remote sensors and Internet of Things (IoT) platforms can enable continuous monitoring across distributed port assets (Aslam et al., 2025).

Machine learning based predictive maintenance at smart ports has been documented in peer reviewed research, with algorithms using historical failure data and sensor inputs to predict faults in container handling equipment (Aslam et al., 2025). Digital twin platforms, such as the one being developed by the Port of Rotterdam, provide digital representations of port infrastructure, and the Port of Rotterdam uses real time sensors, including tilt sensors on quay walls, to monitor the state of assets and time maintenance measures (Port of Rotterdam Authority, 2022).