Automated Cabin Class Mapping for Airline Disrupted Flights
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Airline companies face challenges in quickly and efficiently re-accommodating passengers affected by flight disruptions, as existing systems lack an automated method to accurately map cabin and travel class structures of disrupted flights into replacement flights, leading to high costs and passenger dissatisfaction.
Innovation Solution
A method that automatically maps the cabin and travel class structures of disrupted flights into replacement flights by retrieving the base disrupted flight, splitting the disruption period into sub-periods, establishing direct matches, validating against actual structures, and applying class matching rules to resolve discrepancies, with optional features including default rules and manual audits to ensure minimal passenger impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual re-accommodation processes are used for disrupted flights, then service quality can be maintained through human judgment, but operational costs increase and processing time extends
Solution Approach 1:
The system enables automated self-service mapping of cabin and travel class structures. The automated mapping system independently retrieves disruption information, determines base disrupted flights, splits disruption periods into sub-periods, establishes direct matches between cabin structures, validates against actual structures, and applies class matching rules without requiring manual intervention for each passenger re-accommodation case.
Solution Approach 2:
The patent replaces the manual mechanical process of skilled personnel reviewing and mapping cabin structures with an automated computerized system. The automated system uses algorithms to retrieve disruption data, determine base flights, split disruption periods, establish direct matches, validate cabin structures, and apply class matching rules, substituting human manual operations with automated computational processes.
2Productivity
If automated re-accommodation systems are implemented, then processing speed increases, but mapping accuracy between cabin structures may deteriorate
Solution Approach 1:
The system incorporates validation feedback mechanisms where the automated mapping results are validated against the actual cabin and travel class structure of replacement flights. The system pinpoints discrepancies between the mapped structure and actual structure, then applies class matching rules from a repository to resolve these discrepancies, ensuring mapping accuracy is maintained through iterative feedback and correction.
Solution Approach 2:
The system performs preliminary actions by pre-establishing direct matches between cabin structures before validation, and by pre-retreiving class matching rules from a repository. This preliminary setup allows the automated system to quickly process mappings while having validation and correction mechanisms ready, maintaining both speed and accuracy.
3Measurement precision
If skilled personnel are deployed for re-accommodation, then mapping accuracy improves, but operational costs and time requirements increase
Solution Approach 1:
The automated system performs the entire mapping process independently without requiring skilled personnel intervention. It retrieves disruption information, determines base disrupted flights, splits disruption periods, establishes direct matches, validates cabin structures, and applies class matching rules automatically, eliminating the time loss associated with deploying skilled personnel while maintaining accuracy through automated validation.
4Reliability
If comprehensive validation and discrepancy resolution are performed, then mapping reliability improves, but system complexity increases
Solution Approach 1:
The system segments the validation process into distinct modular steps: retrieving disruption information, determining base disrupted flight, splitting disruption period into sub-periods, establishing direct match, validating against actual structure, pinpointing discrepancies, and applying class matching rules. This segmentation makes the complex validation process more manageable and systematic while improving reliability through thorough step-by-step verification.
Data Source
AI summary
In a method for automatically mapping a cabin and travel class structure of an disrupted flight into replacement flights, cabin and travel class structure of the disrupted flight are retrieved. For each affected passenger, a base disrupted flight is determined from the passenger itinerary. For the disruption period, cabin and travel class structure of the replacement flights are split into sub-periods. For each sub-period, mapping begins by establishing a direct match between cabin and travel class structures. The direct match is validated against actual cabin and travel class structure of the replacement flights, including pinpointing all found discrepancies. All class matching tables (CMTs) applying to the disrupted flight and disruption period considered are retrieved from a rule repository. Cabin and travel class structure of the replacement flights are further split in sub-periods to imbed the actual validity periods of retrieved CMTs. Rules of the retrieved CMTs resolve all found discrepancies.