Computational Accelerator for MBSE Change Control
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Solution Overview
Problem
Model-based system engineering (MBSE) faces challenges in efficiently linking and managing changes across diverse sets of model and document components, which is typically a resource-intensive task due to the complexity of linking and propagating changes among various types of documents and models created by different teams over time.
Innovation Solution
A computational accelerator system is introduced, featuring a MBSE work preprocessor that autonomously segments and compares content to determine statement-wise linkages, and a revision control engine that selectively updates linked statements based on linkage strength and operational conditions, prioritizing changes with significant impact and reducing computational burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If change propagation is performed across all linked statements in MBSE systems, then completeness of change tracking is improved, but computational load and processing time increase significantly
Solution Approach 1:
The system segments change propagation into priority levels, dividing the monolithic change tracking process into hierarchical segments. High-priority changes propagate through all linked statements, while low-priority changes are selectively propagated based on linkage strength, thereby reducing overall processing time while maintaining essential completeness.
Solution Approach 2:
The system applies different propagation behaviors to different statements based on their linkage strength and priority characteristics. Statements with strong linkages receive full propagation attention, while statements with weak linkages receive selective propagation, creating local quality variations in the change tracking process that optimize both completeness and efficiency.
2Reliability
If change propagation is performed across all linked statements in MBSE systems, then completeness of change tracking is improved, but computational resources consumed increase
Solution Approach 1:
The system segments the set of linked statements into priority groups and processes them accordingly. By dividing change propagation into high-priority and low-priority segments, the system reduces the total computational resources required while maintaining essential tracking completeness through selective processing of critical changes.
Solution Approach 2:
The system performs partial change propagation by selectively applying propagation to only the most impactful statements based on linkage strength and priority. This partial action approach reduces computational resource consumption while still achieving sufficient completeness for critical system changes.
3Reliability
If all changes are propagated throughout the MBSE system, then thoroughness of update propagation is improved, but system responsiveness deteriorates
Solution Approach 1:
The system segments update propagation into priority-based batches, with high-priority updates propagated immediately to maintain system responsiveness, while low-priority updates are propagated in subsequent batches. This segmentation enables the system to remain responsive to critical changes while still achieving thorough propagation over time.
Solution Approach 2:
The system employs periodic batch processing for change propagation, where high-priority changes are propagated in real-time and lower-priority changes are propagated in periodic batches. This periodic action maintains system responsiveness to urgent changes while ensuring thorough propagation of all updates across the MBSE system.
4Adaptability or versatility
If manual change tracking is performed across diverse model and document components, then flexibility in handling different document types is maintained, but human resources and operational effort increase
Solution Approach 1:
The system implements automated change tracking that operates autonomously across diverse model and document components. The automated system identifies, tracks, and propagates changes without human intervention, thereby maintaining flexibility in handling different document types while dramatically reducing operational effort and human resources required.
Solution Approach 2:
The system replaces manual mechanical change tracking processes with automated computational mechanisms. This substitution maintains the ability to handle diverse document types through programmable logic while eliminating the operational burden of manual tracking across heterogeneous MBSE artifacts.
Data Source
AI summary
A computational accelerator architecture facilitates change management of works in a model-based system engineering (MBSE) system in which each of the MBSE works includes a plurality of separately-identifiable statements. A linkage data store stores statement-wise, variable-strength linkages between certain statements of the MBSE works, where the linkages are indicative of associations between those certain statements. A revision control engine detects changes made to statements of MBSE works, and selectively indicates calls for revision of other statements in response to those changes based on respective strengths of linkages associated with the changed statements.