Cloud Data Processing for Industrial Automation
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Solution Overview
Problem
Industrial automation systems face challenges in efficiently managing and analyzing large volumes of data from various sources, with existing on-site data storage systems limited by finite capacity and single-point failure issues, and high maintenance requirements.
Innovation Solution
A cloud-based architecture is implemented where operational data from industrial machines is stored in a local cache and then transferred to an unstructured data storage system in the cloud, processed to convert it into a structured format, and analyzed upon request, using a scalable infrastructure that simplifies data collection, distribution, and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is stored in on-site storage systems, then data access is fast and reliable, but storage capacity is limited and maintenance requirements are high
Solution Approach 1:
The patent extracts data storage from on-site local systems and relocates it to cloud-based storage infrastructure. This allows the industrial automation system to access virtually unlimited storage capacity while the cloud provider handles maintenance, backups, and system updates, thereby reducing on-site maintenance requirements.
Solution Approach 2:
The patent introduces a cloud gateway or interface as an intermediary between the industrial automation system and cloud storage. This intermediary manages data transmission, formatting, and access protocols, enabling the system to leverage cloud storage capacity while maintaining simple on-site operations.
2Reliability
If data is stored locally, then data access is quick and reliable, but single-point failure issues occur and scalability is limited
Solution Approach 1:
The patent segments data storage across multiple cloud-based storage nodes and locations rather than relying on a single local storage system. This distribution provides redundancy against single-point failures while allowing the system to scale by adding more storage resources in the cloud without modifying on-site infrastructure.
Solution Approach 2:
The patent implements a universal cloud-based storage infrastructure that serves multiple functions: primary data storage, backup, archival, and analytics processing. This multi-functional approach improves reliability through redundancy while providing scalable capacity for growing data requirements.
3Loss of information
If more data is collected and stored, then better analytics and insights are achieved, but data processing time and resource requirements increase
Solution Approach 1:
The patent applies preliminary data processing, filtering, and aggregation in the cloud before analytics operations. Data is pre-processed, validated, and organized into structured formats in advance, which reduces the time required for actual analytics while maintaining complete and accurate data for comprehensive insights.
Data Source
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AI summary
Systems, methods, and software to facilitate cloud-based data processing and analysis in an industrial automation environment are disclosed herein. In at least one implementation, operational data generated by at least one industrial machine is stored in a local cache. The operational data is transferred for storage in an unstructured data storage system in a cloud-based architecture. In the cloud-based architecture, the operational data is processed to convert the operational data to a structured format and the operational data in the structured format is then stored in a structured data storage system. In response to receiving a request for analytics, at least a portion of the operational data is extracted from the structured data storage system and the analytics are executed on the at least the portion of the operational data.