Collaborative Technical Configuration Synchronization
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Solution Overview
Problem
Current CAD/CAE software tools lack effective methods for synchronizing and coordinating technical data across different engineering domains, leading to low productivity and inefficiencies in design and simulation due to lack of synchronization and coordination between technical experts.
Innovation Solution
A method for collaborative generation of technical configuration data using a computing server that communicates with user terminals, storing reference data vectors with configuration parameters and constraints, and performing compliance and consistency checks to ensure data synchronization and coordination among experts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple technical experts work on different engineering domains using separate CAD/CAE tools, then each expert can efficiently design and simulate within their own domain, but synchronization and coordination between experts becomes difficult leading to low productivity
Solution Approach 1:
The patent merges multiple independent CAD/CAE tools and data models into a unified collaborative environment where technical data from different engineering domains are integrated. A central server coordinates data exchange between experts, enabling simultaneous work on the same product while maintaining domain-specific capabilities. This resolves the contradiction by combining individual expertise efficiency with collective coordination.
Solution Approach 2:
The system implements automated feedback mechanisms where changes made by one expert are automatically communicated to other experts and their respective tools. Conflict detection and resolution feedback loops ensure data consistency without requiring manual iteration. This reduces the time lost in coordination while maintaining efficient domain-specific design processes.
2Ease of operation
If a generic data model is used to organize technical data across different engineering domains, then communication between experts is facilitated, but managing consistency between technical data sets becomes complex
Solution Approach 1:
The patent segments the generic data model into domain-specific data models that maintain their own structures and rules. Each engineering domain (mechanical, electrical, thermic) has its own specialized data model instantiated from the generic framework. This segmentation enables easy domain-specific operations while the central server manages cross-domain consistency, reducing the complexity of managing the entire system at once.
Solution Approach 2:
A central server acts as an intermediary between different domain-specific data models and experts. It handles the complex tasks of translating between models, detecting conflicts, and ensuring consistency across technical data sets. This intermediary approach simplifies the user interface and operations for each expert while systematically managing the underlying complexity of data consistency.
3Loss of information
If existing data exchange tools like PDM, SDM, IGES or STEP are used, then technical data exchange between models is enabled, but conflict management between data produced by different experts is not provided
Solution Approach 1:
The patent replaces manual conflict management processes with automated computational mechanisms. Instead of relying on experts to manually coordinate and resolve conflicts using standard data exchange tools, the system implements automated conflict detection, analysis, and resolution algorithms that operate on the technical data. This substitution maintains full data exchange capability while adding reliable automated conflict management.
4Ease of operation
If manual synchronization is performed where each user decides what to share and when, then user control over data sharing is maintained, but productivity is reduced due to lack of automatic coordination
Solution Approach 1:
The patent implements a dynamic synchronization system that adapts to user needs and project context. Users can control the level and type of automatic synchronization for their domain, adjusting between manual and automated modes as needed. The system dynamically coordinates data sharing based on change detection, project priorities, and user preferences, maintaining user control while significantly improving productivity through automated coordination where appropriate.
Data Source
AI summary
A reference configuration is defined in a main software by a set of reference data vectors, each reference data vector referring to a technical aspect of said product. A reference data vector comprises at least one configuration parameter and/or at least one constraint to be verified by a value assigned to a configuration parameter of a reference data vector. User data vectors are instantiated on the basis of a subset of reference data vectors of the reference configuration and define a user configuration.A software synchronization module 111 running on one said user terminal in the context of an auxiliary software generates at least one value for a parameter associated to a configuration parameter in the main software. The value is assigned to associated configuration parameter of at least one user data vector instantiated in the main software. A compliance check is performed relatively to constraints defined in the main software for the associated configuration parameter. An indicator representative of a result of the compliance check is sent to the software synchronization module 111. A consistency check is performed by comparing values assigned to a same configuration parameter in at least one first modified data vector of the first user configuration and in a second modified data vector of the second user configuration.