# Predictive Maintenance for Port Cranes, Done by Sound

Canonical URL: https://deeplyinc.com/cases/port-crane-predictive-maintenance
Language: en
Solution: industrial
Published: 2026-09-23
Last verified: 2026-09-23

Detect anomalies in cranes and rotating equipment by sound instead of vibration sensors. Non-contact microphones monitor continuously without mounting constraints

## Classification

- Industry: Ports & logistics
- Process: Equipment operation
- Inspection target: Crane wires & bearings
- Target sound: Crane & rotating equipment anomalies

## Overview

A single hour of downtime on large port cranes and rotating equipment can seriously disrupt logistics. Detecting crane wire or bearing faults with vibration sensors brings many false alarms, and contact sensors can only be mounted in limited places. Deeply is running field trials of sound-based predictive maintenance with a large Singapore port operator, a Korean port, and a UK port city

## Customer Tasks

- Predictive maintenance for wire vibration inside crane wheels
- Move from repair-after-inspection to catching early signs of anomalies
- Integrate with existing alarm systems and digital twins

## Field Challenges

- Even in normal operation, cranes get louder and vibrate more when they accelerate while lifting containers or run under high load. Telling normal operating changes from real anomalies was the core challenge
- Ports must run 24 hours without interruption, so downtime is costly
- The marine environment imposes demanding hardware durability requirements such as waterproofing and dustproofing
- Contact sensors can only be mounted in limited places, and on equipment as large as cranes they risk wear and damage. The noise sensors used at some sites had room to improve in accuracy and operating cost

## Site Conditions and Constraints

- 24-hour uninterrupted operation
- Marine environment requiring waterproof and dustproof ratings and certifications
- High-noise environment dense with large equipment
- Port and marine environment where communication can be unstable

## Deployment and System Setup

- Continuous monitoring with non-contact microphones
- Analysis at the edge, sending only results
- Results passed to existing control and alarm systems

## Outcomes

Key metric
- 3 regions: Parallel field trials of sound-based predictive maintenance (Definition: Regions running field trials of sound-based predictive maintenance; Scope: Ports in Singapore, Korea, and the UK, as of September 2026)
- 3 regions: Parallel field trials of sound-based predictive maintenance (Definition: Regions running field trials of sound-based predictive maintenance; Scope: Ports in Singapore, Korea, and the UK, as of September 2026)
- Non-contact: Microphone-based detection (Definition: Detecting equipment condition from sound without attaching sensors to it)

## Measurement Conditions and Limitations

- Limitations: All three regions are still in field trials. The Singapore port operator is confirming the accuracy and operating-cost advantage over its existing noise sensors, and results will be summarized again once confirmed

## Related Pages

- [Listen AI Industrial](https://deeplyinc.com/solution/industrial)
- [Inquiry](https://deeplyinc.com/inquiry)

## Machine-Readable References

- [llms.txt](https://deeplyinc.com/llms.txt)
- [llms-full.txt](https://deeplyinc.com/llms-full.txt)