Connected FMS Data Integration for Real-Time Cargo Flight Planning
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Solution Overview
Problem
Large air-cargo operators face challenges in optimal cargo flight planning due to limited time and lack of accurate, real-time information about dynamic aircraft parameters, leading to inefficient load planning and increased fuel usage.
Innovation Solution
Implementing a Connected FMS Software as a Service (SaaS) platform that provides real-time aircraft intelligence through a simulation engine, utilizing APIs to access dynamic aircraft parameters for optimal cargo load planning, cargo placement, and flight parameter adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ground based simulation and modelling systems utilizing historical, predicted data are used for cargo flight planning, then the planning process can be completed with available data, but the accuracy of dynamic aircraft parameters is insufficient and time for adequate load planning is limited
Solution Approach 1:
The system implements real-time feedback by continuously receiving actual aircraft performance data (fuel consumption, weight, center of gravity) from en-route aircraft via data links. This feedback loop allows ground-based planning systems to update and refine cargo load plans based on actual aircraft behavior rather than relying solely on historical or predicted data, thereby improving parameter accuracy without extending planning time.
Solution Approach 2:
The system performs preliminary cargo load planning using available data before the aircraft departs, and then continuously refines these plans during flight using real-time data. This allows the initial planning to be completed within time constraints while subsequent real-time updates improve accuracy dynamically, resolving the contradiction between planning time and parameter accuracy.
2Productivity
If real-time aircraft intelligence is integrated into cargo planning, then cargo planning efficiency and fuel optimization are improved, but system complexity increases
Solution Approach 1:
The system integrates multiple functions into a unified platform that handles real-time data acquisition from aircraft, data processing and analysis, cargo load optimization calculations, and communication with ground operations. This multi-functional integration improves cargo planning efficiency while managing complexity through a consolidated system architecture rather than separate independent systems.
Solution Approach 2:
The system introduces an intermediary ground-based processing platform that receives real-time aircraft data via data links, processes the information through simulation and optimization algorithms, and generates updated cargo plans. This intermediary layer manages the complexity by handling data processing and optimization calculations centrally, allowing real-time intelligence integration without requiring complex modifications to individual aircraft systems.
3Ease of manufacture
If historical and predicted data are used for cargo planning calculations, then the planning process is simpler to implement, but the accuracy of load planning and fuel consumption predictions is reduced
Solution Approach 1:
The system transitions from static historical and predicted data to dynamic real-time data by continuously receiving actual aircraft performance parameters during flight. This dynamic approach maintains ease of implementation through automated data links and processing algorithms while significantly improving load planning accuracy by using actual aircraft behavior data rather than static historical averages or predictions.
Data Source
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AI summary
Disclosed are systems, methods, and non-transitory computer-readable medium for fleet based aircraft flight planning using real-time intelligence. For example, a system may include a simulation engine configured to calculate flight modification parameters associated with an aircraft based on real-time flight data of the aircraft, real-time weather data along a flight path of the aircraft, and real-time planning data of the aircraft, and then transmit the flight modification parameters to a flight management system (FMS) of the aircraft.