Cloud Computing for Industrial Equipment Health Monitoring
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Solution Overview
Problem
Conventional equipment health monitoring systems in industrial automation face challenges in accurately predicting equipment failures and scheduling maintenance due to high costs and storage limitations of advanced simulation models, which are often too expensive and resource-intensive to deploy locally.
Innovation Solution
A cloud computing system that includes a processing unit and data storage unit configured to analyze data from industrial automation units, perform predictive analysis, and issue warnings for potential failures, while segregating data and processes between local and cloud environments to optimize performance and reduce costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If advanced simulation models are deployed locally for equipment health monitoring, then prediction accuracy improves, but system cost and resource consumption increase
Solution Approach 1:
The patent introduces cloud computing platforms as an intermediary between local equipment and advanced simulation models. Local devices transmit operational data to the cloud, where sophisticated algorithms process the information and return predictions. This mediator approach enables access to high-accuracy models without requiring expensive local deployment infrastructure.
Solution Approach 2:
The system creates virtual copies of equipment data and operational states in the cloud environment. Instead of running complex simulation models locally on physical hardware, the patent replicates the analytical capabilities in a virtual cloud-based environment, allowing multiple equipment instances to share the same advanced modeling resources.
2Measurement precision
If advanced simulation models are deployed locally for equipment health monitoring, then prediction accuracy improves, but storage requirements increase
Solution Approach 1:
The patent extracts the heavy computational and storage requirements of advanced simulation models from the local equipment environment and relocates them to cloud-based infrastructure. Local devices retain only minimal data storage for operational parameters, while the cloud platform houses the extensive datasets and complex models needed for accurate predictions.
3Speed
If data is processed locally for real-time monitoring, then response speed improves, but processing capability is limited
Solution Approach 1:
The patent segments the monitoring system into two functional parts: local real-time data collection and transmission, plus cloud-based comprehensive analysis. Local devices handle immediate data acquisition and forwarding with minimal processing, while the cloud platform performs the intensive computational analysis, combining fast local response with powerful remote processing.
Data Source
AI summary
A system includes a computing cloud having at least one data storage unit and at least one processing unit. The computing cloud is configured to provide at least one service. The system also includes a plurality of clients each configured to communicate with the computing cloud and at least one industrial automation unit and to transmit information associated with the at least one industrial automation unit to the computing cloud. The at least one processing unit in the computing cloud is configured to determine a status of the at least one industrial automation unit using the information provided the clients.