Turn Time Analytics for Commercial Vehicle Scheduling
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Solution Overview
Problem
Commercial vehicle operators face challenges in determining realistic turn times for operations like aircraft, trains, and ships, as existing methods often result in either insufficient time for tasks or overly long stop times, due to variations in activities such as refueling, passenger loading, and maintenance, which can lead to inefficient scheduling and revenue loss.
Innovation Solution
A computer-implemented method that analyzes past operations data to identify and remove isolated instances of turn times, then uses statistical analysis to fit a mathematical function to the remaining data, identifying the shortest realistic turn time within a threshold distance from the function, which is used to schedule future operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If turn time is minimized to increase productivity, then revenue generation improves, but operational reliability deteriorates due to insufficient time for necessary activities
Solution Approach 1:
The patent changes the parameter of turn time from a fixed scheduled value to a dynamically optimized value based on statistical analysis of historical data. By fitting a mathematical function to historical turn time data and identifying the shortest realistic turn time within a threshold distance from the function, the system determines an optimized turn time that balances productivity and reliability requirements
Solution Approach 2:
The patent implements feedback by using historical operation data to continuously refine turn time estimates. The system collects actual turn time data from past operations, analyzes it through statistical functions, and uses the results to optimize future scheduling decisions, creating a closed-loop system that improves both productivity and reliability over time
2Reliability
If turn time is extended to ensure sufficient time for activities, then operational reliability improves, but productivity deteriorates due to excessive stop times
Solution Approach 1:
The patent transforms the turn time parameter from conservative fixed estimates to data-driven optimized values. By removing isolated instances from historical data and fitting a mathematical function to the remaining data, the system identifies the shortest realistic turn time that maintains operational reliability, thereby reducing excessive stop times and improving productivity
3Measurement precision
If isolated instances are removed from data to improve measurement precision, then turn time estimation accuracy improves, but data quantity decreases
Solution Approach 1:
The patent applies the extraction principle by removing isolated instances from historical data sets. These isolated instances represent outliers that do not reflect typical operational conditions. By extracting and removing these anomalous data points, the patent improves the precision of turn time estimates while retaining sufficient data quantity for reliable statistical analysis through mathematical function fitting
Data Source
AI summary
Methods, apparatuses, and computer program products are provided for automatically identifying a shortest duration of time for an aspect of an operation. Electronic data related to instances of past operations of at least one vehicle is received. The data comprises respective available durations of time and actual durations of time for an aspect of the past operations. A candidate data set is generated by removing data related to past operations identified as isolated instances of available durations of time and actual durations of time. A mathematical function is generated that fits the candidate data set. An instance from the candidate data set with the shortest actual duration of time that is less than a threshold distance from the mathematical function is identified. The actual duration of time for the identified instance is assigned as a future duration of time for future operations of the at least one vehicle.