Distributed Data Platform for Maintenance Synchronization
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Solution Overview
Problem
Current data management systems for sustaining and maintenance operations of distributed physical assets face challenges in efficiently collecting, verifying, and analyzing information related to maintenance needs, trends, part availability, and software updates, making it difficult and costly to inform and guide these operations effectively.
Innovation Solution
A network architecture featuring nodes with data import service containers, system status condition databases, and distribution service containers that synchronize data across the network, allowing for the collection, organization, and sharing of data from physical assets, enabling real-time monitoring and maintenance support through open interfaces and containers that facilitate interoperability and scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a centralized data management system is used for collecting and analyzing maintenance information, then data verification and analysis accuracy can be improved, but system complexity and implementation cost increase
Solution Approach 1:
The system divides data management into distributed nodes, each independently collecting and pre-processing maintenance data locally. Each node segments the overall data management task, handling data collection, verification, and analysis autonomously while contributing to the global data pool, thereby reducing centralized system complexity while maintaining data accuracy.
Solution Approach 2:
The patent transitions from a traditional centralized hierarchical data management structure to a distributed network topology where nodes communicate peer-to-peer. This dimensional shift in system architecture allows data verification to occur both locally at each node and collectively across the network, improving accuracy without proportionally increasing overall system complexity.
2Loss of information
If distributed data collection is implemented across multiple nodes, then data coverage and information completeness improve, but data synchronization and verification difficulty increase
Solution Approach 1:
The system implements feedback mechanisms where each distributed node validates its collected data against local criteria and shares verification results with the network. Data quality metrics flow back through the network, allowing nodes to adjust their collection and verification processes, ensuring information completeness while maintaining verification accuracy across the distributed architecture.
Solution Approach 2:
The patent combines local data verification at each node with collective network-wide validation. Data from multiple distributed nodes is merged into a unified data structure that maintains provenance information, allowing the system to verify data authenticity and completeness through both local and distributed consensus mechanisms.
3Loss of time
If real-time data synchronization is implemented across network nodes, then maintenance response time and operational availability improve, but network bandwidth consumption and system resource usage increase
Solution Approach 1:
The system implements periodic data synchronization intervals rather than continuous real-time updates. Nodes synchronize their data buffers at predetermined intervals, reducing network bandwidth consumption while maintaining sufficiently current maintenance information. The synchronization period is optimized based on data change frequency and maintenance criticality requirements.
Solution Approach 2:
The patent implements dynamic synchronization where data update frequency adapts based on node activity levels, data change rates, and maintenance priorities. During periods of high data volatility or critical maintenance events, synchronization frequency increases automatically, while during stable periods, frequency decreases to conserve network resources, maintaining responsive maintenance capabilities without constant bandwidth consumption.
Data Source
AI summary
A network includes a first node. The first node includes a data import service container, a system status condition database, and a distribution service container. The data import service container includes a first open interface and is configured to receive and organize data from the first open interface. The system status condition database is connected to the data import service container and includes memory for storing the data received and organized by the data import service container. The distribution service container is connected to the system status condition database and includes a second open interface for connecting the first node to a distribution service container of a second node of the network. The distribution service container of the first node is configured to synchronize the system status condition database of the first node with a system status condition database of the second node.