Crew Routing System for Utility Service Restoration
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Solution Overview
Problem
Utility companies face challenges in efficiently restoring services like power, water, and gas after storms, due to the complexity of managing multiple service outages and crew deployments, often resulting in prolonged restoration times and inadequate resource allocation.
Innovation Solution
A method and system for determining service routes for crews based on outage data, crew skills, and estimated repair times, utilizing a routing determination system that includes a processor and computer-readable medium to assign routes and communicate updates, ensuring optimal deployment and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual routing methods are used to assign crews to service outages, then flexibility in crew assignment is maintained, but restoration time increases and resource allocation becomes inefficient
Solution Approach 1:
The patent replaces manual routing methods with an automated computer-based system that uses processors and algorithms to determine optimal crew assignments and service routes. This substitution of mechanical/manual processes with automated computational systems directly increases restoration speed while managing complexity through software-based solutions.
Solution Approach 2:
The system dynamically changes routing parameters such as crew skill indicators, service outage locations, and estimated repair times to optimize restoration efficiency. By adjusting these parameters in real-time based on incoming data, the system achieves faster restoration without requiring overly complex fixed structures.
2Reliability
If crews are deployed without considering skill matching to outage locations, then deployment speed increases, but repair quality and effectiveness decrease
Solution Approach 1:
The patent applies local quality by matching specific crew skill indicators to specific service outage requirements at each location. Rather than using a uniform assignment approach, the system tailors crew assignments to the specific skills needed at each outage location, ensuring repair effectiveness while maintaining efficient deployment through automated matching algorithms.
3Measurement precision
If comprehensive outage data is collected and analyzed for each service location, then routing accuracy improves, but data processing time and computational complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and organizing outage data as it is received, preparing it for rapid analysis. By initiating data processing early and continuously updating routing determinations as new information becomes available, the system achieves high routing accuracy without excessive delays in crew deployment.
Solution Approach 2:
The patent maintains continuity of useful action by continuously processing outage data and updating service route determinations in real-time rather than batch-processing. This continuous data analysis allows the system to maintain high routing accuracy while minimizing delays, as the computational process runs concurrently with other restoration activities.
Data Source
AI summary
A method of determining service routes for a plurality of crews is provided. Outage data identifying a plurality of service outage source locations, a number of affected customers associated with each location of the plurality of locations, and a type of repair to perform at each location of the plurality of locations is received. A repair time is estimated for each location. Crew data identifying a plurality of crews and a start location for the plurality of crews is received. A service route for each crew is determined based on a crew skill indicator associated with each crew satisfying the type of repair to perform at each location and based on the estimated repair time for each location. The service route for a crew of the plurality of crews includes the start location as a first location and at least one location of the plurality of locations.