Medical System Self-Service Knowledge Engine for Automated Condition Resolution
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Solution Overview
Problem
The existing methods for providing service assistance to equipment in industrial, medical, and research settings are resource and time intensive due to the need for on-site support by highly trained field personnel, often resulting in costly and time-consuming service calls for issues that can be resolved without technical expertise.
Innovation Solution
A processor-based system that detects reportable conditions and provides machine data to a knowledge engine to identify and implement solutions, allowing operators to address issues without field engineers, with the knowledge engine being updated based on the success or failure of these solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If field personnel are deployed to provide on-site support, then service quality and problem resolution capability are improved, but service time and operational costs increase
Solution Approach 1:
The system enables self-service by automatically detecting reportable conditions through sensors and monitores, diagnosing problems using a knowledge engine that searches for solutions based on machine data, and implementing fixes without requiring field personnel deployment. The medical system autonomously resolves issues by executing identified solutions from the knowledge base.
Solution Approach 2:
The patent replaces the mechanical system of field personnel travel and on-site intervention with an automated electronic system. Sensors, data communication networks, and a knowledge engine substitute for human technicians, enabling remote diagnosis and automated problem resolution without physical presence at the customer site.
2Reliability
If field personnel are deployed to provide on-site support, then complex problems can be resolved, but operational costs and resource requirements increase
Solution Approach 1:
The system performs self-diagnosis and self-repair by automatically detecting conditions, searching for solutions in the knowledge engine, and implementing fixes. This eliminates the need for expensive field personnel deployment while maintaining problem resolution capability for both simple and complex issues through automated analysis and execution.
Solution Approach 2:
The knowledge engine acts as an intermediary between the detected problem and the solution implementation. It receives machine data from sensors, searches the database for appropriate solutions, and provides guidance for implementation, replacing the intermediary role previously filled by field technicians.
3Productivity
If automated solution implementation is used, then service response time is improved, but system complexity increases
Solution Approach 1:
The system segments the problem resolution process into distinct functional modules: sensors for condition detection, data communication for information transfer, a knowledge engine for solution search and diagnosis, and execution mechanisms for implementing fixes. This modular segmentation manages complexity by organizing functions into separate, manageable components.
Solution Approach 2:
The knowledge engine serves multiple functions: storing solution knowledge, diagnosing problems based on sensor data, selecting appropriate solutions, and guiding implementation. This multi-functionality reduces overall system complexity by consolidating multiple roles into a single intelligent component rather than requiring separate systems for each function.
Data Source
AI summary
A technique is provided for resolving a reportable condition. Upon detection of a reportable condition on a processor-based medical system, machine data is provided to a knowledge engine. One or more identified solutions are received from the knowledge engine and implemented on the processor-based medical system. The one or more solutions are verified as they are implemented to determine if the currently implemented solution resolves the reportable condition. Routines implementing some or all of the technique may be provided on a processor-based system or on a machine-readable medium.