Cloud-Platform IIoT Management for Cross-Factory Data Sharing
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Solution Overview
Problem
Industrial Internet of Things (IIoT) systems face challenges in data sharing and synchronization across different factories or branches of an enterprise, leading to information silos, inefficient resource utilization, and inadequate decision-making support.
Innovation Solution
A cloud platform-based system that integrates distributed servers to communicate with multiple IIoT platforms, utilizing dedicated communication interfaces, big data processing modules, and redundancy mechanisms to ensure seamless data transmission and processing, enabling real-time adjustments and optimizations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If each factory or branch independently collects and processes production information, then local data processing capability is improved, but information sharing and synchronization between different factories deteriorate
Solution Approach 1:
The system divides the enterprise IIoT into multiple independent factory-level IIoT platforms, each capable of autonomous data collection and processing. This segmentation allows each factory to maintain local processing capabilities while the cloud platform enables information sharing across all factories, resolving the contradiction between local autonomy and global information sharing.
Solution Approach 2:
A cloud platform is introduced as an intermediary between multiple factory-level IIoT platforms. The cloud platform receives data from various factories, performs centralized processing and analysis, and distributes relevant information back to the appropriate factories. This intermediary mechanism enables information sharing and synchronization without compromising local data processing capabilities.
2Length of moving object
If data is collected and processed independently at each factory, then data transmission distance is reduced, but information synchronization and sharing between factories deteriorate
Solution Approach 1:
The system adds a new dimension to data transmission by implementing a two-level architecture: local data transmission within each factory (short distance) and cloud-based data exchange between factories (long distance). This dimensional approach allows data to travel short distances locally while maintaining synchronization through the cloud, effectively resolving the contradiction between transmission distance and information synchronization.
3Quantity of substance
If massive industrial data is collected from multiple factories, then data volume for analysis is improved, but efficient processing and extraction of valuable information deteriorates
Solution Approach 1:
The system implements local quality processing by having each factory's IIoT platform perform preliminary data filtering, cleaning, and preprocessing before transmitting data to the cloud. This ensures that only high-quality, relevant data is transmitted and processed centrally, maintaining processing efficiency while utilizing large data volumes from multiple factories for comprehensive analysis.
Solution Approach 2:
Preliminary data processing and filtering are performed at each factory level before data is transmitted to the cloud platform. This preliminary action reduces the burden on centralized processing systems and ensures that valuable information is efficiently extracted from massive data volumes through pre-prepared, high-quality datasets.
4Loss of information
If a centralized cloud platform is used for all IIoT systems, then information sharing is improved, but system complexity and communication overhead increase
Solution Approach 1:
The system segments the IIoT architecture into independent factory-level platforms that maintain their own data collection and processing systems. The cloud platform serves only as a coordination layer for information sharing, rather than a centralized control system. This segmentation reduces overall system complexity while enabling effective information sharing between factories.
Data Source
AI summary
Provided are a method, a system, and a storage medium for information management of IIoT based on a cloud platform. The method includes: obtaining a production condition of a factory, signaling information, and communication information between a communication device and a plurality of data processing devices; determining a data communication effect of each of the plurality of data processing devices; determining a first signal interference type of the factory and a first probability distribution; determining one or more reference factories from the at least one associated factory and determining a second signal interference type of the factory and a second probability distribution; generating a pre-adjustment instruction, and generating a real-time adjustment instruction; and sending the pre-adjustment instruction and the real-time adjustment instruction to an IIoT sensing network platform, and sending an adjustment result to an IIoT user platform sequentially through an IIoT management platform and an IIoT service platform.