Software Agent Normalizes Manufacturing Data
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Solution Overview
Problem
Current computerized process control and manufacturing information systems face challenges in retrieving and presenting manufacturing information from multiple diverse data sources without regard to the source, particularly due to the inability to estimate non-trending data and the complexity of integrating data from various systems.
Innovation Solution
A software agent receives information requests based on a configured manufacturing data model, adds contextual metadata, and provides a normalized response, while a graphical user interface supports data navigation and refinement, enabling manufacturing information workers to select and contextualize data within the manufacturing data model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is retrieved from multiple diverse backend systems (relational and time-series), then data completeness is improved, but system complexity increases
Solution Approach 1:
The patent introduces a software agent as an intermediary component that sits between the user interface and multiple backend systems (relational and time-series databases). This agent handles all data retrieval operations, translating user requests into appropriate queries for different backend systems and normalizing the results into a unified format. The agent effectively mediates the complexity by absorbing the intricacies of multi-system integration, allowing users to access comprehensive data without directly facing the underlying system complexity.
2Ease of operation
If data is normalized and contextualized with metadata, then data usability is improved, but processing time increases
Solution Approach 1:
The patent implements preliminary action by pre-configuring the manufacturing data model with expected data structures, relationships, and metadata schemas before actual data retrieval occurs. The software agent is pre-programmed with knowledge of how to normalize data from different backend systems and what contextual metadata is needed. This preparation work is done in advance, allowing the agent to quickly process real-time requests without performing complex normalization and contextualization operations during the actual data retrieval, thus reducing processing time while maintaining high data usability.
3Ease of operation
If graphical user interface provides detailed data navigation controls, then user control is improved, but interface complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the graphical user interface into distinct functional zones: a data selection area where users choose specific manufacturing data points, a navigation area with controls for filtering and refining results, and a display area showing contextualized information. Each segment has a specific, simplified function, allowing users to control data retrieval and navigation without being overwhelmed by a monolithic complex interface. The segmentation enables progressive disclosure of complexity, showing users only the controls and options relevant to their current task.
Data Source
AI summary
A software agent is described that receives an information request to retrieve information based on a name defined by a configured manufacturing data model. The agent serves the request by relating data coming from one or multiple backend systems and adding contextual data (Metadata). A result set is prepared to correspond to the format and filtering criteria defined in the information request, and the agent produces a response in a normalized format. The response contains the requested data and metadata used for navigation and contextualization purposes. The response in the normalized format is transmitted by the agent synchronously or asynchronously based on criteria specified in the request.