Industrial IoT Problem Classification for Manufacturing Issue Resolution
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Solution Overview
Problem
In Intelligent Manufacturing, the large number of equipment and complex data processing challenges lead to inefficient and costly problem-solving processes, as existing technologies struggle to automatically identify and classify manufacturing issues, resulting in high data processing pressure and manual intervention requirements.
Innovation Solution
An industrial Internet of Things (IoT) system with an acquisition module, problem type determination module, and problem solving module is implemented, using a five-platform structure to obtain equipment information, determine problem types, and solve manufacturing problems through keyword indexing and matching, reducing manual intervention and data processing complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual problem processing center is used to handle manufacturing problems, then problem solving can be performed, but data processing pressure and workload are extremely huge and tedious
Solution Approach 1:
The patent implements self-service by enabling equipment to automatically detect, report, and resolve their own problems through embedded sensors and processing units. Equipment generates problem data, determines problem types, and executes solutions autonomously without requiring manual intervention from a centralized processing center, thereby eliminating the tedious data processing workload while maintaining problem-solving capability
Solution Approach 2:
The patent segments the centralized problem processing function into distributed autonomous problem-solving units embedded in each piece of equipment. Each equipment unit independently handles its own problem detection and resolution, dividing the previously centralized complex data processing task into numerous simple, independent local operations, thereby reducing overall system complexity and processing pressure
2Extent of automation
If equipment automatically solves problems using existing data processing capabilities, then manual intervention is reduced, but problem processing cost and process are not reduced or omitted
Solution Approach 1:
Equipment is equipped with autonomous problem-solving capabilities including sensors for detection, processing units for determining problem types, and execution mechanisms for implementing solutions. This self-service approach enables automatic problem resolution at the equipment level without requiring costly centralized processing, thereby improving productivity while maintaining high automation
Solution Approach 2:
The patent introduces an industrial Internet platform as an intermediary that coordinates between equipment units, providing standardized problem data formats, classification frameworks, and solution repositories. This intermediary enables efficient automatic problem solving by facilitating information exchange and knowledge sharing across the manufacturing system, improving overall problem processing efficiency
3Loss of information
If centralized data processing is used for all manufacturing problems, then comprehensive problem analysis is possible, but data transmission paths are long and processing time is increased
Solution Approach 1:
The patent segments the centralized data processing architecture into distributed local processing units at each equipment. Each unit processes and analyzes problem data locally, eliminating long data transmission paths and reducing processing time. Only essential aggregated information is transmitted to the industrial Internet platform, maintaining analysis completeness while minimizing time loss
Solution Approach 2:
The patent implements preliminary action by pre-configuring problem detection thresholds, classification rules, and solution protocols in equipment units before problems occur. When problems arise, equipment can immediately apply pre-prepared analysis frameworks and solutions locally, avoiding time-consuming data transmission and centralized analysis, thereby reducing problem processing time while maintaining comprehensive analysis capability
Data Source
AI summary
The disclosure provides an industrial Internet of Things for solving manufacturing problems, a control method, and a storage medium. The method includes an industrial Internet of Things for solving manufacturing problems. The industrial Internet of Things includes an acquisition module, a problem type determination module and a problem solving module, the acquisition module is configured to obtain equipment information and data of product manufacturing problems; the problem type determination module is configured to determine a problem type at least based on the data of the product manufacturing problems; and the problem solving module is configured to determine problem processing data based on the problem type, and solve the problem based on the problem processing data.