Maritime Intelligence & Maintenance Forecast Platform

Business Objective

Develop an automated platform that:

Monitors vessels globally.
Identifies vessels approaching significant maintenance milestones.
Identifies vessels entering drydocks, repair facilities and shipyards.
Estimates future maintenance and survey events where schedules are not publicly available.
Identifies fleet operators with multiple vessels approaching maintenance programs.
Identifies organisations responsible for the vessels.
Produces daily and weekly intelligence reports.
Prioritises opportunities using configurable scoring criteria.
Core Requirement 1: Survey & Docking Intelligence

The primary purpose of the system is to identify vessels approaching significant maintenance activity.

The platform should identify or estimate vessels approaching:

5-Year Events
Intermediate Surveys
Class Surveys
Drydock Surveys
Planned maintenance periods
Refurbishment activities
10-Year Events
Special Surveys
Major class renewals
Life extension programs
Retrofit projects
Major overhaul programs
Modernisation projects

The system should provide visibility of future opportunity windows wherever possible.

Core Requirement 2: Predictive Maintenance Forecasting

Where direct scheduling information is unavailable, the platform should estimate future maintenance events using available vessel data.

Potential inputs may include:

Vessel build date
Vessel age
Historical docking records
Historical survey records
Classification information
Previous maintenance intervals
Vessel type

Example output:

Predicted Opportunity

Vessel: Example Explorer

Built: 2018
Current Age: 8 years
Predicted Major Maintenance Window: Q2 2028
Confidence Score: 84%
Core Requirement 3: Fleet Planning Intelligence

The platform should identify companies with multiple vessels approaching significant maintenance events.

Example:

Fleet Opportunity

Company: Example Marine

Fleet size: 45 vessels
7 vessels approaching 5-year maintenance cycle
4 vessels approaching major survey cycle
Multiple vessels expected to enter repair facilities within next 24 months

Priority Level: High

The goal is to identify fleet-wide business development opportunities, not just individual vessel events.

Vessel Monitoring

System should monitor:

Commercial shipping fleets
Offshore support vessels
Ferries
Passenger vessels
Government fleets
Defence support vessels
Tankers
Bulk carriers
Tugs
Dredgers
Special purpose vessels

Coverage should be worldwide.

Opportunity Scoring Engine

Create a configurable scoring system based on:

Vessel age
Time since build
Docking history
Survey cycle timing
Shipyard arrivals
Repair facility arrivals
Fleet maintenance programs
Vessel type
Geographic region
Historical maintenance patterns

Users must be able to modify weighting and scoring rules.

Contact & Organisation Intelligence

Where available, provide:

Vessel owner
Fleet operator
Ship manager
Technical manager
Fleet manager
Company website
Country
Fleet size

The objective is to connect identified opportunities with the responsible peoplein our organisation.

Reporting

Automated reports should be delivered by email.

Example:

High Priority Opportunities
Vessel

Example Explorer

Current Age: 9.5 years
Predicted Maintenance Window: Q2 2028
Current Destination: Singapore
Opportunity Score: 92%
Organisation

Example Shipping Ltd

Fleet Size: 38 vessels
Multiple vessels approaching survey cycles within 24 months

Recommended Action:

Business development engagement recommended.

Dashboard

Develop a web-based dashboard displaying:

Vessel Name
IMO Number
Vessel Type
Vessel Age
Owner
Manager
Current Location
Destination
Predicted Maintenance Window
Opportunity Score

Filters should include:

Region
Country
Vessel Type
Fleet Owner
Maintenance Window
Arrival Date
Opportunity Score
Preferred Technology

Developer may propose architecture.

Current preference includes:

Python
Microsoft 365
Power Automate
Azure
Power BI
SQL Database

Open to alternative recommendations.

Data Sources

Developer should recommend appropriate maritime data sources.

Examples may include:

AIS providers
Vessel movement databases
Port schedules
Repair facility schedules
Maritime intelligence providers
Classification databases
Public maritime information sources

Ongoing operating costs should be minimised wherever practical.

Deliverables
Fully functioning production platform
Automated email reporting
Opportunity scoring engine
Predictive maintenance module
Fleet intelligence module
Searchable database
Dashboard
Documentation
Administrator training
Full source code handover
Success Criteria

The platform should enable users to:

Identify vessels approaching significant maintenance events.
Predict future maintenance opportunities.
Identify fleets with multiple upcoming maintenance requirements.
Identify responsible organisations and relevant contacts.
Receive actionable business development intelligence ahead of maintenance activity.
Prioritise opportunities globally using automated reporting and scoring.
Important Note

The system should focus on predicting future maintenance opportunities rather than merely reporting vessel arrivals. The most valuable output will be identifying vessels and fleet operators likely to be planning maintenance, survey, repair, retrofit, refurbishment or lifecycle activities over the next 6-36 months.