Industrial Plant Data Synchronization With Selective Record Sync
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Solution Overview
Problem
Existing systems for data synchronization between mobile client devices and centralized servers in industrial plants face inefficiencies due to the need to download large amounts of unnecessary data, difficulties in selecting specific records, manual version comparison leading to potential data integrity issues, and interruptions causing re-initiation of synchronization processes.
Innovation Solution
Implementing data record selection parameters and version synchronization rules to optimize data transfer by selecting only necessary records based on criteria such as shift time and operator ownership, automating version selection, and resuming synchronization sessions without retransmitting fully downloaded data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data records are downloaded to mobile client devices during synchronization, then data availability for field operators is improved, but data transfer volume and bandwidth usage increase significantly
Solution Approach 1:
The patent extracts and downloads only the specific data records that are relevant to each field operator's current tasks and location, rather than downloading all available data records. This selective extraction approach maintains data availability for needed information while significantly reducing overall data transfer volume and bandwidth consumption.
Solution Approach 2:
The system applies local quality by customizing the data set for each mobile client device based on the specific field operator's role, current task, and location within the plant. Each operator receives a tailored subset of data records that is optimized for their specific needs, rather than a uniform comprehensive data set.
2Reliability
If manual version comparison is performed during synchronization, then data integrity can be verified, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system implements self-service by automatically comparing data record versions between the centralized server and mobile client devices, and autonomously resolving version conflicts based on predefined rules. This eliminates the need for manual version comparison by field operators, maintaining data integrity through automated verification while significantly reducing synchronization time and eliminating human error.
Solution Approach 2:
The system uses feedback mechanisms to automatically detect version discrepancies between server and client data records, and implements automated conflict resolution based on version timestamps and predefined synchronization rules. This feedback-driven approach ensures data integrity is maintained while eliminating time-consuming manual intervention.
3Reliability
If synchronization sessions are re-initiated after interruption, then data consistency is restored, but the process wastes previously downloaded data and increases time loss
Solution Approach 1:
The system performs preliminary actions by maintaining state information about previously downloaded and synchronized data records. When a synchronization session is interrupted and resumed, the system uses this preliminary state information to identify which data records have already been successfully transferred, avoiding redundant re-downloads and restoring consistency efficiently.
Solution Approach 2:
The system ensures continuity of useful action by resuming interrupted synchronization sessions from the point of interruption rather than restarting from the beginning. The system continuously tracks synchronization progress and maintains data about completed transfers, allowing the useful action of data synchronization to continue seamlessly after interruption without wasting previously downloaded data.
4Quantity of substance
If selective data record download is implemented, then bandwidth usage is reduced, but the complexity of selecting appropriate records increases
Solution Approach 1:
The system applies universality by implementing a standardized selection mechanism that uses field operator profiles, task types, and location data to automatically determine relevant data records. This multi-functional selection approach handles various operator roles, task categories, and plant locations through a single unified mechanism, reducing the perceived complexity while enabling selective data download.
Solution Approach 2:
The system uses an intermediary selection layer that sits between the centralized data repository and mobile client devices. This intermediary component automatically filters and selects appropriate data records based on operator profiles, current tasks, and location information, shielding field operators from the complexity of selection criteria while achieving efficient bandwidth utilization through selective data transfer.
Data Source
AI summary
The present invention provides methods, systems and computer program products that enable the optimized synchronization of data between mobile client devices assigned to field operators in an industrial plant and a centralized repository for plant data. The invention optimizes synchronization of data between mobile client devices assigned to field operators in an industrial plant and a centralized repository for plant data by selecting a reduced set of data records associated with a field operator, for data synchronization based on one or more of a set of data record selection parameters, and a set of version synchronization rules to ensure that only data records that are relevant to a field operator's foreseeable activities in a shift are downloaded to the field operator's mobile client device.