Train Asset Management via Hypothetical Operational Scenario Simulation
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Solution Overview
Problem
Current train management systems lack the ability to efficiently manage the availability and reliability of train assets, particularly in predicting the likelihood of assets completing missions and optimizing maintenance schedules, and do not allow remote operators to receive status information or send commands to locomotives effectively.
Innovation Solution
A train asset management system that includes sensors generating real-time signals and a controller simulating hypothetical operational scenarios based on prognostic data to determine predictive information on maintenance needs and operational improvements, allowing for remote control and optimization of train assets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional train management systems are used, then basic operational control is maintained, but the ability to predict mission completion likelihood and optimize maintenance schedules is lacking
Solution Approach 1:
The system performs preliminary actions by simulating hypothetical operational scenarios before actual maintenance or operational decisions are made. The controller predicts mission completion likelihood and schedules maintenance activities in advance based on prognostic data, rather than reacting to failures after they occur. This allows optimization of maintenance timing to improve reliability while reducing unnecessary maintenance time.
2Ease of operation
If remote controller interface is added to allow off-board control, then operator accessibility is improved, but system complexity increases
Solution Approach 1:
The system introduces an intermediary communication interface that allows remote operators to access and control train assets without being physically present on the train. The controller acts as a mediator between the remote operator interface and the train's operational systems, transmitting control commands and receiving status information through communication protocols. This improves ease of operation while managing complexity through standardized interface protocols.
3Measurement precision
If multiple sensors are deployed to monitor operational characteristics, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The system employs a universal sensor framework where multiple sensors monitor various operational characteristics (temperature, pressure, vibration, etc.) using standardized data collection and processing protocols. The controller integrates data from these diverse sensors through a unified approach, processing prognostic data to predict mission completion likelihood. This multi-functional sensor network improves measurement precision while managing complexity through standardized interfaces and integrated processing.
Data Source
AI summary
A method for managing train assets increases the time between required maintenance of the train assets, improves the future availability of the train assets, or increases the likelihood that the train assets will successfully complete future missions. A controller may receive from a sensor on a train asset a real-time signal indicative of at least one of a measured operational characteristic or a maintenance activity associated with the train asset, receive from a memory prognostic data providing information on a likelihood the train asset will complete a mission, and simulate a hypothetical operational scenario (HOS) based at least in part on the prognostic data and involving one or more train assets. Predictive data associated with the HOS may provide information on a likely benefit to a train asset from a change in at least one of an operational parameter, designated operational configuration for the train assets, or maintenance-related activity.