Support Model Integration System for Health Management Data
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Solution Overview
Problem
Legacy system design approaches focus on minimizing initial acquisition costs, neglecting availability-driven design and integrated diagnostics, leading to inefficiencies and increased development costs due to internal engineering silos, conflicting interests, and lack of reusable technologies, which hampers effective health management and supportability efforts in complex systems.
Innovation Solution
A support model integration system and method that integrates various health management analytical tools by creating a database for holding health management data and forming a syntactic and semantic interface between client tools and the database, using an integrated support semantic information model to provide an ontology for health domain information, allowing each tool to publish or request data in a specific view required by the tool.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple independent analytical tools are used by different engineering disciplines, then each tool can perform its specific analysis function, but data redundancy and system complexity increase significantly
Solution Approach 1:
The patent merges multiple independent analytical tools into a single integrated system that shares a common database and user interface. Different engineering disciplines (reliability, maintainability, safety, testability) access the same system through discipline-specific views, eliminating data redundancy while maintaining specialized analysis capabilities. The system integrates fault tree analysis, event tree analysis, and other analytical methods within one unified platform.
Solution Approach 2:
The system implements a universal platform that serves multiple engineering disciplines simultaneously. A single system provides reliability analysis, maintainability analysis, safety analysis, and testability analysis through different views and interfaces. The common database stores data that can be accessed and analyzed by any discipline, making the system multi-functional while reducing overall complexity.
2Reliability
If each discipline performs independent analysis using independent tools, then specialized analysis can be conducted, but development costs increase and efficiency decreases
Solution Approach 1:
By combining multiple analytical tools into one integrated system, the patent eliminates the need for separate tool acquisitions, installations, and maintenance for each discipline. The shared database and common infrastructure reduce development costs while maintaining specialized analysis capabilities through discipline-specific views and interfaces.
Solution Approach 2:
The system creates virtual copies or views of the same underlying data model for different disciplines. Each discipline (reliability, safety, maintainability) has its own customized view and interface that copies the necessary data and analysis capabilities from the central system, allowing specialized analysis without requiring separate physical tools or data stores.
3Loss of information
If a comprehensive database stores all health management data, then data reuse and traceability improve, but data management complexity increases
Solution Approach 1:
The patent segments the comprehensive database into discipline-specific views and data subsets. While the underlying database is comprehensive and integrated, each engineering discipline accesses only the relevant portion through customized views. This segmentation reduces the apparent complexity for each user while maintaining the benefits of a unified data repository for traceability and reuse.
Solution Approach 2:
The system introduces an intermediary layer between the comprehensive database and users. This intermediary (the integrated system with its views and interfaces) manages the complexity of data storage and retrieval, allowing users to access traceable and reusable data without directly managing the underlying database complexity. The intermediary handles data integration, consistency, and access control.
Data Source
AI summary
A real time health management analytical system and method that enables a plurality of plug-in tools and extension tools to be interfaced with a central database, and for enabling information to be published to the database from each of the client tools, as well as data to be read from the database by each of the client tools. The system makes use of an engineering model views module that provides a syntactic and semantic interface between the client tools and the central database so that health management data communicated to the client tools is presented in accordance with a specific view required by each specific client tool. An integrated support information model (ISIM) module is interposed between the data base and the engineering model views module, and forms a specification (e.g., an ontology) for all health domain information available for use by the client tools.