Asset Data Integration Platform Using Ontology-Based Runtime Models
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Solution Overview
Problem
Current maintenance solutions for industrial plants often focus on individual assets without considering their context, leading to inefficiencies, high manual configuration efforts, and difficulties in integrating heterogeneous data sources, resulting in increased costs and risks.
Innovation Solution
A method for integrating data from assets into a uniform platform using domain-specific ontologies and general models, allowing for the creation of asset instances that can be easily configured and accessed by applications, facilitating comprehensive data analysis and improved life cycle management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual configuration is used for onboarding assets, then individual assets can be configured, but it causes high effort, time consumption and errors
Solution Approach 1:
The patent uses templates to create copies of asset configurations. Instead of manually configuring each asset individually, standardized templates are created once and then copied and adapted for multiple assets, dramatically reducing the time and effort required for onboarding while maintaining consistency and reducing errors
Solution Approach 2:
The patent implements preliminary configuration through templates that are prepared in advance. Asset configurations are pre-defined with standard parameters, relationships, and metadata structures before actual assets need to be onboarded, allowing for rapid deployment when assets are introduced to the system
2Adaptability or versatility
If heterogeneous data sources from different manufacturers are integrated, then comprehensive asset data becomes available, but data consistency and integration complexity increase
Solution Approach 1:
The patent implements a universal template structure that can accommodate data from multiple manufacturers and asset types. The template system defines standardized data models and relationships that work across different data sources, allowing the system to handle heterogeneous data uniformly without requiring separate integration logic for each manufacturer
Solution Approach 2:
The patent introduces templates as an intermediary layer between heterogeneous data sources and the asset management system. These templates act as mediators that translate and normalize data from different manufacturers into a common structure, simplifying integration while maintaining the ability to handle diverse data formats and schemas
3Loss of information
If asset data is integrated without context, then individual asset information is available, but comprehensive analysis and life cycle management are limited
Solution Approach 1:
The patent segments asset information into hierarchical levels: individual asset data, asset relationships, and contextual information. This segmentation allows the system to organize and manage different types of information separately while maintaining their connections, enabling comprehensive analysis without losing the context that links assets to each other and to their operational environment
Data Source
AI summary
The invention relates to a method for integrating data from assets of a technical installation into a platform (CB), wherein general models (AM, VM) are initially defined for the assets of domain-specific technical installations using ontologies and general data sources containing information in connection with the assets are identified. The data from the identified general data sources are then assigned to the previously defined general models. An asset is then selected for a specific installation and the corresponding general model is imported into the platform (CB). The data sources of the specific installation are then configured in such a manner that the general model (AM, CM) can be filled with the specific data relating to this installation iteratively and at runtime for the selected asset on the basis of the data sources of the specific installation. Entities (AI, CI) for the selected asset are formed by filling the general model with the specific data and are stored in the platform. The asset entities can now be easily configured in the platform, with the result that any desired applications can access the asset entities and the data thereof without any problems via programming interfaces.