Containerized Model Management for Faster Plant Model Deployment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional model management systems in production plants are cumbersome and time-consuming, making large-scale deployment and maintenance of code impractical due to the need for thorough quality control of entire model code, even when only a small portion is functional.
Innovation Solution
A model management system that stores and implements model modules and non-core functions separately, using application containers to provide a suitable computing environment for each model, allowing for efficient deployment and maintenance by focusing on specific code changes rather than the entire model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire model code is reviewed and approved as part of the quality control process, then the reliability of the model is improved, but the time required for deployment and maintenance increases significantly
Solution Approach 1:
The patent segments model code into distinct modules with clear separation between functional code (core logic) and deployment code (infrastructure support). This segmentation allows quality control to focus only on functional code modules, eliminating the need to review entire model packages including deployment scripts, thereby reducing deployment time while maintaining reliability through targeted code review of critical functional components.
Solution Approach 2:
The patent extracts and isolates functional code from deployment code into separate modules. By taking out only the essential functional logic from the complete model package, the system enables streamlined quality control processes that review only the extracted functional components, significantly reducing the time required for approval while ensuring the reliability of the core model functionality.
2Reliability
If the entire model code is reviewed and approved as part of the quality control process, then the reliability of the model is improved, but the complexity of the deployment process increases
Solution Approach 1:
The patent segments model code into distinct modules with clear separation between functional code (core logic) and deployment code (infrastructure support). This segmentation allows quality control to focus only on functional code modules, eliminating the need to review entire model packages including deployment scripts, thereby reducing deployment time while maintaining reliability through targeted code review of critical functional components.
Solution Approach 2:
The patent extracts and isolates functional code from deployment code into separate modules. By taking out only the essential functional logic from the complete model package, the system enables streamlined quality control processes that review only the extracted functional components, significantly reducing the time required for approval while ensuring the reliability of the core model functionality.
3Ease of manufacture
If functional code is separated from deployment code into separate modules, then the ease of deployment is improved, but the device complexity increases due to modular architecture
Solution Approach 1:
The patent creates reusable functional code modules that can be deployed across multiple models and contexts. These universal functional modules handle common operations that can be instantiated by different deployment configurations, reducing the need for custom code for each model while maintaining ease of deployment through standardized, multi-functional components.
Solution Approach 2:
The patent merges multiple functional operations into standardized modules that can serve multiple purposes. By combining related functional logic into unified modules that can be reused across different models and deployment scenarios, the system reduces overall complexity while improving ease of deployment through consistent, reusable components.
Data Source
AI summary
A model management system manages models that carry out at least one function on data obtained from at least one tag. The system stores data indicative of a plurality of model modules, each model module configured to implement core functionality of a model, and data indicative of a plurality of non-core functions, each non-core function configured to implement non-core functionality of a model. The system also stores a plurality of application containers, each application container including components required to execute a model and each application container defining a computing environment suitable for implementing the model. A model implementer implements a model by implementing at least one model module defined for the model and implementing at least one non-core function defined for the model, and the model implementer can further implement the model using a stateless container suitable for implementing the model.


