Automated Work Order Generation for Power Systems
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Solution Overview
Problem
Existing power generation systems face inefficiencies in processing work requests to generate effective work orders, often relying on manual techniques that are prone to errors and inefficiencies.
Innovation Solution
A system and method utilizing a work order processor with a work request interface that standardizes work requests, a work order generator that determines priority and mode of operation, and a scheduler that deploys service crews based on skill sets, all executed on computing platforms to automate the generation and execution of work orders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual techniques are used to process work requests and generate work orders, then flexibility in handling diverse requests is maintained, but accuracy and efficiency deteriorate due to human errors and manual processing limitations
Solution Approach 1:
The patent replaces manual mechanical processing of work requests with an automated computer-based system that uses machine learning models and natural language processing to standardize and generate work orders, eliminating human errors while maintaining system flexibility through programmable rules and adaptive algorithms
Solution Approach 2:
The system enables self-service automation where the work order generation process automatically standardizes incoming requests, determines priority, selects appropriate templates, and generates finalized work orders without requiring manual intervention at each step, thereby improving accuracy while reducing operational complexity
2Productivity
If manual processing methods are used for work requests, then system complexity is kept low, but productivity and efficiency worsen due to time-consuming manual operations
Solution Approach 1:
The system performs preliminary actions by pre-defining work order templates, priority criteria, and standardization rules before work requests arrive. When a request is received, the system automatically applies these pre-configured elements to rapidly generate work orders, significantly improving efficiency while the apparent complexity is masked by the upfront configuration work
Solution Approach 2:
The system changes parameters by dynamically adjusting work order attributes such as priority level, category, and template selection based on the content and requirements of each incoming work request. This automated parameter adjustment improves processing efficiency while the system manages complexity through programmable decision logic
3Reliability
If automated systems are implemented to process work requests, then accuracy and productivity improve, but system complexity increases due to the need for sophisticated processing algorithms and infrastructure
Solution Approach 1:
The system introduces an intermediary layer consisting of natural language processing components and machine learning models that bridge the gap between unstructured work requests and standardized work order templates. This intermediary automatically interprets and transforms incoming data, improving reliability while managing complexity through modular architecture and standardized interfaces
4Reliability
If standardized processing is applied to work requests, then consistency and reliability improve, but adaptability to unique or non-standard requests may worsen
Solution Approach 1:
The system implements dynamics by making the standardization process adaptive rather than rigid. The machine learning models continuously learn from incoming work requests and can adjust standardization parameters to accommodate unique or non-standard requests while maintaining overall consistency. The system dynamically selects and modifies templates based on the specific characteristics of each request, balancing consistency with adaptability
Data Source
AI summary
A work request interface receives work request data for a power generation system. The work request data includes a work request having data characterizing equipment of the power generation system and a first state of the equipment. The work request interface processes the work request to modify at least one field in the work request to provide a standardized work request. The standardized work request includes data characterizing operations needed to change a state of the equipment from the first state to a second state. A work order generator receives the standardized work request and determines a priority of the standardized work request. The work order generator determines a mode of operation of the power generation system needed to change the state of the equipment from the first state to the second state and generates a set of work orders for the work request.