Systems Analysis Platform for Process Control Point Detection
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Solution Overview
Problem
Organizations face issues such as data loss, data leakage, system errors, and reduced accuracy due to a lack of controls between independently developed and tested computer-based systems used to implement processes, leading to inefficiencies and resource wastage.
Innovation Solution
A systems analysis platform determines system topology, identifies control points, and measures metrics to detect errors, facilitating actions to improve process efficiency and accuracy by optimizing system interactions and data flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If independently developed and tested computer-based systems are used to implement processes, then system functionality and operational independence are improved, but data loss, data leakage, system errors, and reduced accuracy occur due to lack of controls between systems
Solution Approach 1:
The patent introduces control points as intermediary elements between independently developed systems. These control points act as mediators that enforce data validation, transformation, and control rules, ensuring data integrity while preserving system independence. The control points are placed at strategic locations in the system topology to monitor and regulate interactions between systems.
Solution Approach 2:
The patent implements feedback mechanisms through continuous monitoring of system interactions at control points. The system automatically detects errors, validates data transformations, and provides feedback loops that correct deviations from expected behavior. This feedback ensures that independently developed systems maintain data integrity without requiring centralized control.
2Measurement precision
If manual analysis and monitoring of system interactions are performed, then error detection capability is improved, but time consumption and resource wastage increase
Solution Approach 1:
The patent enables systems to perform self-validation and self-monitoring through automated control points. Each control point automatically validates data, detects errors, and logs interactions without requiring manual intervention. This self-service approach maintains high error detection capability while eliminating time-consuming manual analysis.
Solution Approach 2:
The patent replaces manual mechanical analysis with automated electronic monitoring systems. Control points use software-based validation rules, automated logging, and electronic error detection mechanisms to monitor system interactions, substituting human analysis with automated computational processes that are faster and more consistent.
3Reliability
If comprehensive controls are implemented between all systems, then data integrity and accuracy are improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent divides the control structure into discrete control points placed at specific locations in the system topology rather than implementing comprehensive controls across all system interactions. Each control point handles specific validation and monitoring tasks independently, segmenting the overall control function into manageable units that reduce implementation complexity.
Solution Approach 2:
The patent applies control rules and validation mechanisms locally at specific control points where they are most needed, rather than uniformly across all systems. Each control point is configured with specific validation rules appropriate to its location in the system topology, allowing for targeted control that maintains data integrity without adding unnecessary complexity elsewhere.
4Measurement precision
If system topology and control points are manually identified, then accuracy of analysis is improved, but productivity and efficiency are reduced
Solution Approach 1:
The patent replaces manual identification of system topology and control points with automated discovery mechanisms. The system automatically analyzes system interactions, generates topology maps, and identifies optimal control point locations using computational algorithms, substituting manual analytical processes with automated electronic analysis that is both accurate and efficient.
Solution Approach 2:
The system performs self-analysis by automatically discovering its own topology and identifying control points through monitoring system interactions. This self-service capability allows the system to maintain high analysis accuracy while improving productivity, as the automated process can continuously analyze system behavior without human intervention.
Data Source
AI summary
A device may receive first data associated with a set of systems used to implement a process. The device may determine a system topology for the set of systems. The device may identify a set of control points associated with the set of systems. The set of control points may include a set of points in the system topology where second data is received or provided by the set of systems. The second data may include information to be used by the set of systems during the process. The device may identify a set of values for a set of metrics related to the set of systems. The set of values may be identified based on the first data. The device may identify an error related to the set of control points or the set of metrics. The device may perform an action to facilitate fixing of the error.