Process Data Detection System with Context-Sensitive Expert Knowledge
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Solution Overview
Problem
Current systems lack a comprehensive approach for continuous validation processes, including preparation, implementation, and evaluation of experiments, and fail to provide context-sensitive information access across process steps, leading to inefficiencies in knowledge management and decision-making.
Innovation Solution
A device and method for acquiring, checking, and storing status data from multiple process steps using graphical models to represent expert knowledge, allowing for context-sensitive information filtering and networking of data circuits for continuous validation and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If information is stored in a database with structured data, then information can be called up globally using search terms, but the correct search terms must already be known to obtain helpful results
Solution Approach 1:
The patent introduces an intermediary system that automatically extracts keywords and generates search terms from process data and contextual information. This intermediary layer bridges the gap between stored expert knowledge and user queries, eliminating the need for users to know precise search terms while maintaining global accessibility of the database.
Solution Approach 2:
The system implements feedback mechanisms where search queries and results are analyzed to automatically refine and expand the database of search terms and keywords. This feedback loop continuously improves the system's ability to retrieve relevant information without requiring users to possess expert-level search knowledge.
2Quantity of substance
If documents or information are stored on local computers, then memory requirements increase significantly, but centralized access and updating become problematic
Solution Approach 1:
The patent merges distributed local storage with centralized database access by implementing a hybrid architecture. Local computers maintain cached versions of frequently accessed expert knowledge, while the central database ensures unified access and centralized updating. This combination reduces memory requirements at individual locations while maintaining ease of access and simplifying update management.
3Loss of information
If expert knowledge is stored in a centralized database, then it can be accessed globally, but the information lacks context-sensitivity for different process steps
Solution Approach 1:
The patent applies local quality by associating different subsets of expert knowledge with specific process steps, products, or applications. The system dynamically retrieves and presents only the context-relevant information based on the current process context, ensuring that globally available knowledge is delivered with appropriate local customization and context-sensitivity.
Solution Approach 2:
The system dynamically adapts the presentation and selection of expert knowledge based on real-time process data, user roles, and contextual parameters. This dynamic behavior allows the same centralized database to provide context-sensitive information tailored to different process steps, products, or user needs without requiring separate storage systems.
4Reliability
If comprehensive process data from multiple process steps is collected and analyzed, then statistically secure decisions can be made, but the complexity of data management and processing increases
Solution Approach 1:
The patent segments the comprehensive data processing system into modular components, each handling specific process steps or data types. This segmentation allows the system to collect and analyze data from multiple process steps while managing complexity through organized, independent modules that can be developed, maintained, and scaled separately.
Data Source
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AI summary
Device for acquiring, verifying and storing process data from at least two process steps (1, 2, 3, 4), comprising at least two data circuits (7, 8, 9, 10), wherein each data circuit is assigned to a process step, with one information processing device (6) per data circuit with an input for process data and for stored expert knowledge, a processing logic for processing the process data with the stored expert knowledge to create new expert knowledge and an output for the new expert knowledge, and a storage unit (5) for storing the new expert knowledge from all data circuits as stored expert knowledge, wherein access to the stored expert knowledge is provided for all data circuits.