Spinning Mill Output Classification Using Configuration-Based Benchmarks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
It is challenging for control devices and operators in spinning mills to accurately classify the current production output, making it difficult to initiate necessary actions for improving production efficiency, as existing systems lack effective methods to differentiate between normal and abnormal production outputs.
Innovation Solution
An electronic device that determines the current production output by evaluating it against expected outputs stored in a database, using the current configuration of the spinning mill to identify any deviations and provide a classification, which can be visualized on operator devices to facilitate timely actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If control devices and operators continuously monitor and control the spinning mill, then production quality and quantity can be maintained, but it remains difficult to accurately classify the current production output to distinguish between normal and abnormal states
Solution Approach 1:
The patent segments the complex production output classification problem into distinct categories (normal, abnormal, and specific abnormal types). By dividing the classification task into manageable segments with clear criteria, the system achieves accurate classification without requiring overly complex monitoring mechanisms. Each production output state is defined with specific measurable characteristics that simplify the classification process.
Solution Approach 2:
The patent establishes predetermined classification criteria and thresholds before production monitoring begins. By pre-defining what constitutes normal versus abnormal production outputs and the specific conditions for each abnormal type, the system eliminates the need for complex real-time analysis during operation. The classification rules are prepared in advance, enabling straightforward application during continuous monitoring.
2Adaptability or versatility
If the spinning mill configuration is frequently changed to produce different yarn types, then production versatility is improved, but it becomes more difficult to determine whether the current production output is normal or abnormal
Solution Approach 1:
The patent implements dynamic classification criteria that automatically adapt to the current spinning mill configuration. When the configuration changes to produce different yarn types, the system adjusts the expected production output parameters and classification thresholds accordingly. This dynamic adaptation maintains high classification accuracy across multiple yarn types without requiring manual reconfiguration of monitoring parameters.
Solution Approach 2:
The patent changes the reference parameters and expected output values based on the current production configuration. By adjusting the baseline parameters for what constitutes normal production output according to the active configuration, the system maintains accurate classification capability across diverse yarn types. The classification system monitors deviations from configuration-specific expectations rather than using fixed thresholds.
3Manufacturing precision
If detailed monitoring of individual parts and quality parameters is implemented, then production quality control is improved, but the ability to quickly classify overall production output status deteriorates
Solution Approach 1:
The patent extracts and prioritizes the key parameters that most significantly indicate normal versus abnormal production states. Instead of analyzing all monitored parameters equally, the system identifies and focuses on the critical few parameters that provide the most discriminatory power for classification. This extraction of essential information enables rapid classification while maintaining quality control effectiveness.
Solution Approach 2:
The patent implements a feedback mechanism where the classification result is immediately available to operators based on real-time parameter monitoring. The system continuously compares current production parameters against expected values and provides timely feedback on the production output status. This immediate feedback enables quick decision-making without requiring time-consuming manual analysis of detailed monitoring data.
Data Source
AI summary
An electronic device, and associated method of operation, determines a classification of a current production output of one or more parts of a spinning mill. The electronic device is configured to: determine the current production output of the spinning mill parts; determine a current configuration of the spinning mill; based on the current configuration, look up an expected production output of the spinning mill parts in a database; and determine the classification of the current production output by evaluating the current production output with respect to the expected production output for the current configuration of the spinning mill.