Cloud-Mediated Data Exchange in Industrial Automation
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Solution Overview
Problem
Industrial automation systems face inefficiencies in data exchange and coordination between devices, leading to suboptimal operations and maintenance processes.
Innovation Solution
A tri-partite communication paradigm involving industrial automation devices, computing devices, and cloud-based computing systems, where data is shared and analyzed to facilitate efficient operations and maintenance by identifying relevant information and coordinating tasks across the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data exchange methods are used between industrial automation devices, then device operations continue, but data exchange efficiency is low and coordination between devices is poor
Solution Approach 1:
The patent introduces a cloud-based computing system as an intermediary that receives data from multiple industrial automation devices, processes it centrally, and distributes relevant information back to appropriate devices. This mediator architecture enables efficient data exchange and coordination without requiring direct peer-to-peer communication between all devices, thus improving productivity while reducing coordination time.
Solution Approach 2:
The patent moves data exchange from a traditional two-dimensional device-to-device communication model to a three-dimensional architecture involving edge computing devices, cloud-based systems, and multiple industrial devices. This dimensional expansion allows for more efficient data routing, centralized processing, and improved coordination across the industrial automation system.
2Adaptability or versatility
If more devices are connected in the industrial automation system, then system capability increases, but data exchange complexity and coordination difficulty increase
Solution Approach 1:
The patent segments the data exchange architecture into multiple layers: industrial automation devices at the edge, cloud computing devices for processing, and a cloud-based computing system for coordination. This segmentation allows each component to handle specific tasks independently, reducing overall system complexity while maintaining high adaptability and versatility across multiple devices.
Solution Approach 2:
The cloud-based computing system serves as a universal platform that can handle data from various types of industrial automation devices, perform multiple functions including data collection, processing, analysis, and distribution. This multi-functional approach enables the system to accommodate diverse devices without proportionally increasing data exchange complexity.
3Productivity
If real-time data analysis is implemented across all devices, then operational efficiency improves, but computational resource requirements and system load increase
Solution Approach 1:
The patent extracts heavy computational processing tasks from individual industrial automation devices and concentrates them in cloud-based computing systems. Edge devices collect and transmit data, while cloud systems perform complex real-time analysis. This extraction allows operational efficiency to improve through comprehensive data analysis without imposing excessive computational resource requirements on individual devices or the overall distributed system.
Data Source
AI summary
A system may include an industrial automation device, a computing device configured to receive a first set of data associated with the industrial automation device, and a cloud-computing system. The cloud-computing system may receive the first set of data from the computing device, identify a second set of data associated with the industrial automation device based on the first set of data, and send the second set of data to the computing device when the second set of data is relevant to the first set of data.