Semantic Broker for Industrial Plant State Information Mapping
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Solution Overview
Problem
Industrial plants face challenges in efficiently exchanging information between producers and consumers due to differences in information models, requiring manual translation and increased complexity in managing conversions, which can lead to errors and inefficiencies.
Innovation Solution
A computer-implemented broker entity that facilitates the exchange of state information by using a transformation library to map source values with specific semantic meanings to target values with different semantic meanings, reducing the need for manual conversions and enabling demand-driven data flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual translation of information between different information models is performed by individual consumers, then information can be converted to needed formats, but system complexity and error risk increase significantly
Solution Approach 1:
The patent introduces a broker entity as an intermediary component that mediates between information producers and consumers. The broker maintains a central information model and handles all translation operations, eliminating the need for individual consumers to implement their own translation logic. This centralization reduces system complexity while maintaining adaptability to different information models.
Solution Approach 2:
The broker entity serves multiple functions: it acts as an information collector from various producers, a central translation engine, and a distributor to multiple consumers. This universal component handles all information model conversions centrally, allowing the system to work with multiple different information models without increasing individual consumer complexity.
2Adaptability or versatility
If each consumer implements its own translation logic from source information model to target information model, then information can be adapted to specific needs, but the burden on requesting devices increases
Solution Approach 1:
The broker acts as an intermediary that assumes the translation burden from consumers. Consumers simply request information in their needed format, and the broker handles all the complex translation work using its central information model, significantly easing the operational burden on requesting devices.
Solution Approach 2:
The broker entity autonomously performs all translation operations using its internal central information model without requiring consumer intervention. The system serves itself by automatically adapting information to different models without burdening consumers with translation logic implementation.
3Productivity
If information translation is performed at the consumer level, then each device can obtain information in its specific format, but errors and inefficiencies increase
Solution Approach 1:
By introducing the broker as an intermediary, all translation operations are centralized in a single reliable component. This eliminates the variability and errors associated with multiple independent translation implementations at consumer levels, improving both reliability and efficiency of information exchange.
Solution Approach 2:
The patent merges all translation functionality into a single broker entity rather than distributing it across multiple consumers. This consolidation improves reliability by ensuring consistent translation logic and increases productivity by eliminating redundant translation operations.
Data Source
AI summary
A computer-implemented broker entity receives from a requesting device a request for one or more target values of state information that have sought target semantic meanings; obtains one or more source values of state information that are associated with given source semantic meanings; obtains at least in part from a transformation library one or more transformations, wherein each transformation maps one or more first values that are associated with first semantic meanings to one or more second values that are associated with second semantic meanings; applies the one or more transformations or a new transformation obtained based on the one or more transformations to the source values of state information, thereby obtaining the one or more target values of state information; and transmits the one or more target values to the requesting device.