Industrial IoT Problem Matching for Distributed Manufacturing Response
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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 manual intervention in identifying and solving manufacturing problems, as existing systems struggle to automatically classify and process the vast and varied issues effectively.
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 classify and match problems, allowing for automated identification and processing of manufacturing issues without manual intervention, reducing data processing pressure and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual problem processing center is used to handle manufacturing problems, then problems can be processed with human expertise, but data processing pressure and workload increase significantly due to large number of equipment and complex data
Solution Approach 1:
The system segments the centralized problem processing into distributed autonomous processing units. Each equipment or production line is equipped with an independent problem processing system that can autonomously identify, classify, and solve problems locally, dividing the overwhelming centralized workload into manageable distributed tasks.
Solution Approach 2:
The system enables equipment and production lines to serve themselves by autonomously detecting problems, classifying them using keyword matching, and executing solutions without manual intervention. The intelligent manufacturing equipment automatically updates data, programs, and instructions to resolve issues independently.
2Extent of automation
If automated equipment is used to solve manufacturing problems, then manual intervention is reduced, but data processing, computing, classification and transmission capabilities required are huge and complex
Solution Approach 1:
The automated problem solving system is segmented into modular functional components: problem detection modules, keyword extraction modules, classification modules, and solution execution modules. Each module performs a specific function with simplified data processing requirements, avoiding the need for a single complex system to handle all operations.
Solution Approach 2:
The system introduces an intermediary layer of standardized problem description protocols and keyword databases that mediate between raw equipment data and complex solution processing. This intermediary structure simplifies data classification and matching by transforming diverse equipment data into standardized keyword-based problem representations.
3Reliability
If all manufacturing problems are processed through centralized system, then uniform processing standards can be maintained, but processing time and efficiency decrease due to data transmission and handling overhead
Solution Approach 1:
The system segments processing authority between centralized standard-setting and distributed problem-solving. The centralized system maintains standardized problem classification frameworks and solution databases, while distributed autonomous units execute problems locally, eliminating data transmission overhead for routine issues while maintaining standardization through shared protocols.
Solution Approach 2:
The system performs preliminary actions by pre-classifying problems using keyword matching against a standardized database before full processing is required. Problems are pre-identified and categorized using simple keyword extraction, allowing rapid routing and execution without requiring complete centralized analysis for each issue.
Data Source
AI summary
The disclosure provides an industrial Internet of Things for identifying and processing manufacturing problems, a control method, and a storage medium. The method includes an industrial Internet of Things for identifying and processing 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.