Cloud Backup Modeling for Industrial Automation Plant Recovery
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Solution Overview
Problem
Industrial automation systems lack an efficient method for backing up and restoring complex configurations, leading to difficulties in maintaining consistency and efficiency across multiple facilities and systems.
Innovation Solution
A cloud-based backup system generates and updates a multi-dimensional model of industrial automation systems, incorporating data from various components and relationships, allowing for standardized configurations and easy restoration or replication of industrial automation systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional backup methods are used for industrial automation systems, then backup and restoration processes become complex and time-consuming, but implementing a cloud-based multi-dimensional model approach requires significant data collection and processing infrastructure
Solution Approach 1:
The patent creates a digital twin (multi-dimensional model) that copies and represents the physical industrial automation system in the cloud. This digital copy includes geometric, physical, and operational data that can be manipulated and restored without affecting the physical system, enabling rapid backup and restoration while reducing on-site complexity.
Solution Approach 2:
The cloud-based platform serves as an intermediary between the physical industrial automation system and the backup/restoration processes. By mediating data collection, storage, and processing in the cloud, the system reduces the complexity burden on local devices while enabling comprehensive system modeling and rapid restoration capabilities.
2Reliability
If comprehensive system data is collected for accurate modeling, then model accuracy and consistency improve, but data collection from multiple sources increases system complexity and integration requirements
Solution Approach 1:
The cloud-based platform provides universal data collection capabilities that can interface with multiple different data sources (industrial devices, sensors, control systems) through standardized protocols. This multi-functional approach enables comprehensive data aggregation without requiring complex custom integration for each data source, thereby improving model accuracy while managing system complexity.
Solution Approach 2:
The patent transitions data storage and processing from a single-dimensional local system to a multi-dimensional cloud-based architecture. This dimensional change allows data to be organized, stored, and processed across multiple layers (geometric, physical, operational) and locations, improving data accessibility and model consistency while distributing system complexity across the cloud infrastructure.
3Productivity
If multi-dimensional models are stored and maintained in the cloud, then system configuration and restoration efficiency improve, but data storage and synchronization requirements increase
Solution Approach 1:
The multi-dimensional model is segmented into distinct components (geometric data, physical data, operational data) that can be independently stored, managed, and synchronized in the cloud. This segmentation allows for efficient data retrieval and restoration by only needing to access relevant segments, reducing the practical impact of total data storage requirements while improving configuration efficiency.
Solution Approach 2:
The system performs preliminary data collection and model creation in the cloud before actual backup or restoration is needed. By pre-processing and organizing data into the multi-dimensional model structure in advance, the system enables rapid restoration operations without needing to transfer or process large amounts of raw data during the actual backup/restoration event, thereby improving productivity while managing storage requirements.
Data Source
AI summary
Cloud-based backup provides a back up of an industrial plant comprising an industrial automation system(s) (IAS(s)). A cloud-based backup component comprising a modeler component can generate a model of industrial assets of the IAS(s) and relationships between industrial assets based on information obtained from the industrial assets via cloud gateways, a communication device associated with the IAS(s), or another source. The cloud-based backup component can store the model in a data store to be employed as a backup of the IAS(s) or to be used to configure a new IAS that is the same as or similar to the IAS(s). The model can be stored in the data store in a standardized or an agnostic format, wherein the backup component can translate the model to a format suitable to an IAS for which it is to be implemented based on characteristics associated with the IAS.