Navgathi understand the Ship owners needs in managing energy resources for the entire fleet and have planned the best & proven methods to attain it. Through the accurate monitoring of the data using instrumentation and software’s areas for energy efficiency Improvements are identified.
We will offer our performance analysis solution in following ways.
- Performance Monitoring
- Performance Prediction
- Reporting Tools
Broadly the performance of a vessel can be measured based on the money input that goes in to the vessel versus the money generated by the vessel. This cover the entire gamut of cost and revenue from the vessel. This can be further sub-divided in to three main groups:
- Economic analysis
- Technical analysis
- Engine performance
- Hull & Propeller performance
- Electric Power
- Aux. Engine performance
- Electric Power consumers
- Other machinery
- Other machinery performance
- Selection of energy saving technologies
- Efficacy of energy saving technologies
- Economic cost using metrics
The economic analysis covers the financial performance. The technical analysis focus primarily on propulsion (main engine as well as hull & propeller combination) and to a lesser degree on electric power (generation and consumption). In tankers, aux. boilers performance covers the steam generation apart from other machinery.
Many energy saving technologies have come to market offering gains in reducing consumption in all the above machinery – main engine, aux. engine, and other machinery. The efficacy of such installation is another area of monitoring.
The first two groups are financial and technical metrics. There are some metrics that are a combination of the two, where the need to associate the cost to each parameter. Some such metrics include – cost/tonne-nautical mile of cargo movement, etc.
Many of the parameters like FO, Engine power, etc. can be predicted by studying the historical data of the ship. These prediction tools can be presented in many different formats – excel, web tools, mobile apps, etc.
The prediction for FO or power is based on multi-variable regression that factors the difference in draft (displacement), speed and sea state in taking historical data. It also add a time factor by accounting for number of days since last dry dock or major husbandry.
The reporting is using a web based toll called SID – Ship Information Dashboard. There are three areas of focus:
- How the data is organised
- Types of metrics and analysis
- How data is shared