Cable Processing Machine Monitoring for Parameter Consistency
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Solution Overview
Problem
The inefficiencies in monitoring and optimizing production parameters across multiple wire processing machines lead to varying output rates and production qualities, with challenges in identifying and addressing mechanical issues and errors, resulting in reduced machine availability and production efficiency.
Innovation Solution
A computer-implemented method and monitoring system that centralizes the collection, comparison, and analysis of production parameters, error messages, and quality data from multiple wire processing machines, allowing for efficient operation and remote management through a control server with a central database, enabling easy access and comparison of data for optimizing machine performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If production parameters are set locally at each cable processing machine, then operators can adjust settings iteratively during production, but this results in varying output rates and manufacturing qualities across different machines
Solution Approach 1:
The patent merges the previously distributed local databases of multiple cable processing machines into a centralized database. This allows all machines to access and use the same optimized production parameters, ensuring consistent manufacturing quality across the entire production line while maintaining the ease of local operation through centralized parameter management.
Solution Approach 2:
The system implements feedback mechanisms where production data and quality metrics from each machine are collected and stored in the centralized database. This enables continuous optimization of production parameters based on actual performance data, allowing operators to iteratively improve settings while maintaining consistency across all machines.
2Ease of operation
If error messages are acknowledged locally on each cable processing machine, then operators can respond to machine issues, but it becomes difficult to determine which machines are particularly prone to downtime
Solution Approach 1:
The patent combines the locally stored error messages and production data from multiple cable processing machines into a centralized database. This consolidation enables comprehensive analysis of downtime patterns across the entire production line, allowing identification of machines that are particularly prone to failures while maintaining local error acknowledgment capabilities.
3Manufacturing precision
If production parameters are optimized locally through iterative processes, then each machine can be tuned for its specific conditions, but this increases the time and complexity of setup and reduces overall productivity
Solution Approach 1:
The patent implements preliminary action by pre-optimizing production parameters and storing them in a centralized database before production begins. Operators can directly access these pre-configured parameters, eliminating the need for time-consuming iterative adjustments on each machine while maintaining optimized production quality.
Solution Approach 2:
The system creates and distributes copies of optimized production parameters from the centralized database to multiple cable processing machines. This allows all machines to use proven optimal settings without requiring separate optimization processes, significantly reducing setup time while maintaining high manufacturing precision.
Data Source
Figure 1
AI summary
A computer-implemented method for monitoring multiple cable processing machines (1, 1', 2, 2') for processing cables is proposed, the method comprising the following steps: sending production parameters from one or more cable processing machines (1, 1', 2, 2') to a control server (4) with a central database (6), wherein the production parameters comprise settings of the cable processing machine (1, 1', 2, 2') for processing the cables by the respective cable processing machine (1, 1', 2, 2'); receiving the production parameters by the control server (4); and storing the production parameters in the central database (6).