IIoT Instruction Analysis for Abnormal Command Correction
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Solution Overview
Problem
Intelligent manufacturing systems face issues with instruction conflicts and equipment errors leading to large-scale failures due to the complex interdependence of intelligent manufacturing equipment and management systems across different levels, regions, and categories, causing manufacturing risks and disruptions.
Innovation Solution
An Industrial Internet of Things (IIoT) system with a management platform that analyzes and modifies abnormal instructions by using a cyclic neural network model for sequence modeling and a probability suffix tree model to predict and correct execution errors, ensuring smooth operation and coordination among manufacturing tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If intelligent manufacturing equipment and management systems operate independently without coordination, then each system can function autonomously, but instruction conflicts and task conflicts occur leading to equipment errors and large-scale failures
Solution Approach 1:
The patent introduces an instruction analysis device as an intermediary component that mediates between multiple intelligent manufacturing systems. This device receives instructions from different systems, analyzes them for conflicts, and coordinates their execution. The intermediary prevents direct conflicts between independent systems while maintaining their autonomy, thereby improving reliability without requiring complete system integration.
Solution Approach 2:
The instruction analysis device implements a feedback mechanism by continuously monitoring instructions from various intelligent manufacturing systems, analyzing potential conflicts, and providing coordination feedback. This closed-loop feedback system detects abnormal instructions, identifies conflict sources, and adjusts instruction execution accordingly, preventing failures before they occur while maintaining system independence.
2Productivity
If the number of intelligent manufacturing equipment and management systems is increased to handle complex manufacturing tasks, then manufacturing capability is improved, but the likelihood of instruction conflicts and task conflicts increases
Solution Approach 1:
The patent segments the instruction analysis function into a dedicated instruction analysis device that operates independently from the manufacturing execution systems. This segmentation allows multiple manufacturing systems to operate in parallel without directly interfering with each other, while the segmented analysis device handles conflict detection and coordination, enabling scalable expansion without proportionally increasing conflict risk.
3Reliability
If instruction analysis and conflict detection are performed in real-time, then equipment failures are prevented, but system response time and processing overhead increase
Solution Approach 1:
The instruction analysis device performs preliminary analysis of incoming instructions before they are executed by manufacturing equipment. By analyzing instructions in advance for potential conflicts and abnormalities, the system prevents failures before they occur without causing delays during actual execution. The preliminary action principle allows conflict detection to occur during the instruction preparation phase rather than during critical manufacturing operations.
Data Source
AI summary
The embodiments of the present disclosure provide an Industrial Internet of Things system for abnormal analysis, a method, and a storage medium thereof. The Industrial Internet of Things system includes a management platform, and the management platform is configured to obtain an ordered set of instructions for a preset time period, the ordered set of instructions including a plurality of instructions, and instruction content of each instruction of the plurality of instructions including at least one of instruction type, instruction parameter, and instruction execution time; determine whether there is an abnormal instruction based on the ordered set of instructions; and analyze and modify the abnormal instruction in response to a determination that there is the abnormal instruction.