Notes

Hi everyone,

Today, this is a quick presentation on the recent improvements I’ve made to the dispatch process in Clearwater for the DeliverToAsset configs. These changes focus on enhancing efficiency, reducing redundancy, and optimizing the user experience. We’ll walk through what’s been updated, how it impacts our daily operations, and the benefits we can expect moving forward.

So let’s dive in!



Drawbacks of the Current Process:
1. Hardcoded Train Names: The current process relies on a hardcoded list of train names within the code. This setup requires frequent maintenance, as any new train additions or retirements necessitate code updates to keep the list accurate.
2. 1:1 Asset-to-Train Mapping: The one-to-one relationship between each asset and train creates significant clutter and redundancy. This approach not only impacts readability but also complicates configuration management.
3. High Number of Configurations: With 244 configurations currently in place, and this number expected to grow as more assets and trains are added, the process is increasingly prone to performance and storage issues. This expansion also drives up manual workload, creating additional operational burdens.


In the new process dispatching will be done entering the train name directly in the ‘Destination Mainline OS Train’ parameter in Trainline. This removes the need to manually select a unique configuration for each train. Now, users can simply select one configuration per asset, and the system dynamically assigns it based on the train name input.


• Eliminates Hardcoded Train List: Train names are now entered directly, removing the need for manual updates to a hardcoded list.
• Simplified Asset-to-Train Mapping: A 1:Many relationship between Asset and Train enhances readability, reducing complexity and potential confusion.
• Streamlined Configuration Count: The number of configurations drops to 50, which is a 79.51% drop from the current number. This will address the frequent responsiveness issues, will minimize storage constraints, and reduce delays and manual interventions, making the dispatch process far more efficient.