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Case Study

~1% Fuel Consumption Savings Per Year Achieved for a Cargo Vessel’s Doosan-Sulzer 12-cylinder 2-Stroke Engine

Table of Contents

Background

Industry
Marine
Solution
Engine Condition
Monitoring System
(ECMS)
Make & Model
Doosan-Sulzer
12-cylinder,
2-stroke Engine
Asset
Cargo Ship

Objective

To evaluate our Engine Condition Monitoring System’s ability to identify component-level faults and reduce unnecessary maintenance actions while improving fuel efficiency.

Challenge / Problem Context

  • The customer wanted to verify if the system could identify emerging faults before they impact engine performance.
  • There was a need to scientifically extend engine overhaul intervals and avoid unplanned downtime.
  • The engine showed slightly reduced efficiency at 80 RPM, which needed investigation.
  • Any proposed solution had to be non-invasive, easy to install, and capable of remote monitoring.

What Did We Do?

  • Installed both the Engine Condition Monitoring System and TorqueSense on the main engine without invasive procedures.
  • Enabled remote access to real-time data for seamless monitoring by the Neptunus technical team.
  • Focused on analyzing raw data sets specifically at 80 RPM to identify subtle changes in mechanical behavior.
  • Discovered a non-linear delay caused by the damper getting fully excited at 80 RPM, which led to crankshaft twist and affected combustion timing.
  • Recommended recalibrating valve settings and fuel injection timing to compensate for the damper-induced delay.

Results That We Achieved

  • Identified early signs of combustion imbalance and mechanical deterioration that were not visible through routine inspection.
  • Enabled an estimated 1.2% increase in fuel efficiency, translating to 400–500 tonnes of fuel savings annually for engines of this size.
  • Provided the ship operator with a data-backed strategy to delay unnecessary maintenance, saving cost and reducing downtime.
  • Proved that our ECMS is engine-agnostic, easy to install, and capable of component-level fault detection and remote monitoring .

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