Automatic Welding Decision System for Monocrystal Pulling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The manual inspection and decision-making process in the welding procedure for monocrystal pulling-up is inefficient, leading to lower productivity, poor timeliness, and wastage of time.
Innovation Solution
An automatic decision-making method for welding is implemented, which involves obtaining and processing basic source data, establishing deep learning models for optimal welding parameters, and making decisions based on real-time data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection and decision-making is used in the welding procedure, then personnel can monitor production and prevent accidents, but the efficiency is lower and the timeliness of inspection is worse
Solution Approach 1:
The patent replaces the manual inspection system with an automated detection system that uses sensors to monitor welding parameters (temperature, power, time) and automatically compares them against predetermined ranges, eliminating the need for manual repetition of inspections while maintaining safety monitoring capabilities
Solution Approach 2:
The system performs self-inspection by automatically monitoring its own welding parameters and making real-time decisions about whether to proceed to the next seeding process, eliminating the need for external manual inspection and enabling continuous autonomous operation
2Reliability
If manual inspection and decision-making is used in the welding procedure, then personnel can monitor production, but the timeliness of personnel inspection is worse
Solution Approach 1:
The automated system continuously monitors welding parameters throughout the entire welding process without interruption, ensuring that inspection and decision-making occur in real-time at every moment of the welding process rather than through periodic manual checks
Solution Approach 2:
The patent replaces manual inspection with automated sensor-based monitoring that operates continuously and instantaneously, eliminating the time delays inherent in manual inspection cycles and enabling real-time detection and response to welding condition changes
3Reliability
If manual inspection and decision-making is used in the welding procedure, then personnel can monitor production, but work time is wasted
Solution Approach 1:
The system performs self-monitoring and self-decision-making by automatically evaluating welding parameters against predetermined ranges and determining whether to proceed to the next seeding process, eliminating the need for manual intervention and wasting no work time on repetitive inspection cycles
Solution Approach 2:
The patent establishes predetermined safe ranges for welding parameters before the welding process begins, enabling the automated system to make instant decisions during welding without requiring manual analysis, thus preventing time waste on real-time manual evaluation
Data Source
AI summary
The present application relates to automatic decision-making for welding. Multi-dimensional data cleaning is performed and dimensional data warehouse is established by processing, filtering and converting basic source data of welding nodes in a welding process for monocrystal pulling-up into data sets easily identified and marked and establishing respective models based thereon. Basic source data of a current welding nodes are obtained and converted into process parameters. The process parameters are compared with respective models in the dimensional data warehouse to obtain a first determination result. Data analysis is performed on the first determination result to determine whether the current welding process is abnormal to obtain a second determination result. Decision is made automatically based on the second determination result.