Autonomous Service Validation for Field Assets
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Solution Overview
Problem
Conventional on-site servicing of large-scale assets is often subjective and incomplete, leading to sub-optimal performance and repeated issues due to human error and variability in testing.
Innovation Solution
An automated method using autonomous tests and performance comparison with peer assets in similar environments, facilitated by a device with a processor, memory, and sensors, which implements an interface and validation agent to verify service quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If field engineer performs service and determines service completion at discretion, then ease of operation is improved, but measurement precision and reliability deteriorate
Solution Approach 1:
The device performs self-validation by automatically executing tests and comparing its own performance metrics against expected thresholds, eliminating the need for subjective human assessment while maintaining operational simplicity
Solution Approach 2:
The manual testing and validation process performed by field engineers is replaced with an automated electronic testing system that executes predefined test routines and objectively measures device performance
2Measurement precision
If field engineer performs exhaustive tests, then measurement precision is improved, but productivity and time efficiency deteriorate
Solution Approach 1:
Test routines and validation criteria are pre-configured and stored in the device memory before field service occurs, allowing rapid execution during service operations without requiring engineers to design and perform exhaustive tests manually
Solution Approach 2:
The time-consuming manual testing process is replaced with automated electronic testing that rapidly executes comprehensive validation routines, achieving both high measurement precision and operational efficiency
3Device complexity
If service validation is performed manually, then device complexity is reduced, but reliability and consistency deteriorate
Solution Approach 1:
The device autonomously validates its own service completion status by comparing performance metrics against expected thresholds, ensuring consistent and reliable validation without human intervention
Solution Approach 2:
The system automatically compares actual device performance data with expected performance thresholds and provides feedback on service completion status, ensuring reliable and consistent validation outcomes
Data Source
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AI summary
The present approach relates to an automated approach for verifying sufficiency of and/or quality of a service operation performed on an asset by a field engineer. In one implementation the approach employs autonomous tests and/or compares performance of the serviced asset with that of comparable peers operating in similar or co-local environments.