Error Log Analysis Platform for Real-Time Machine Maintenance Alerts
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Solution Overview
Problem
Conventional methods for indicating machine failures in car manufacturing sites are inadequate, leading to delayed responses and increased losses due to the lack of real-time monitoring and analysis.
Innovation Solution
An error log list and alarm service platform that includes an execution terminal for receiving alarms, a monitoring server for collecting and analyzing error information from machine facilities, and a measuring module for collecting state and environment information, which provides real-time alerts and maintenance recommendations based on error analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional alarm methods (red light or siren) are used to indicate machine failures, then the system is simple and easy to implement, but the response time is delayed and loss increases
Solution Approach 1:
The system performs preliminary actions by continuously collecting and analyzing error logs before actual machine failures occur. The error log collection unit gathers error information in advance, and the analysis unit processes this data to predict potential failures, enabling maintenance to be performed before critical failures happen, thus reducing response time without proportionally increasing system complexity
Solution Approach 2:
The patent introduces an intermediary error log analysis system between the machine facility and the alarm notification. The error log collection unit, analysis unit, and notification unit act as intermediaries that process error information systematically, transforming raw error data into actionable maintenance alerts, which improves response time while keeping the overall system architecture manageable through modular design
2Productivity
If real-time monitoring and error analysis systems are implemented, then response time improves and maintenance efficiency increases, but device complexity and implementation cost increase
Solution Approach 1:
The system is segmented into distinct functional modules: error log collection unit, error log analysis unit, and notification unit. Each module performs a specific function - collecting error data, analyzing error patterns, and notifying maintenance personnel respectively. This segmentation allows the complex monitoring system to be implemented in a manageable way, improving maintenance efficiency while controlling system complexity through modular architecture
Solution Approach 2:
The error log analysis system is designed to be universal and multi-functional, capable of handling various types of machine errors and providing comprehensive maintenance management. The analysis unit can process different error log formats and generate various types of maintenance alerts, making the system adaptable to different machine facilities and error scenarios, thereby improving overall maintenance efficiency without requiring separate systems for each function
3Measurement precision
If comprehensive error log collection and analysis is performed, then maintenance scheduling accuracy improves, but information processing load increases
Solution Approach 1:
The system extracts only the essential and relevant error information from the collected error logs for analysis and maintenance scheduling. The error log analysis unit identifies and extracts key error patterns, frequencies, and trends necessary for accurate maintenance planning, rather than processing every single data point. This extraction approach improves maintenance scheduling accuracy while reducing the overall information processing load by focusing on critical information
Data Source
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AI summary
According to an embodiment, an error log list and alarm service system comprises an execution terminal receiving an alarm including error information according to an operation error in a machine facility designated through an error log list and alarm service platform and a monitoring server collecting a result of monitoring an operation state and operation error in the machine facility, extracting the error information according to an information setting value set by the execution terminal, and providing the extracted error information through a web or app platform.