Tool Load Diagnostics for Multi-Machine Abnormality Detection
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Solution Overview
Problem
Existing tool monitoring systems for working machines require complex operations to set up and manage data for each machine, leading to unnecessary tool replacements and inefficient status monitoring across multiple machines with varying loads.
Innovation Solution
A diagnostic apparatus that acquires program identification, tool, and load transition information from each working machine to diagnose tool abnormalities based on predetermined ranges specific to each machine, tool, and program combination, simplifying the monitoring process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single threshold data is used for all working machines, then the device complexity is reduced, but the measurement precision of tool abnormality detection deteriorates because different machines have different load characteristics
Solution Approach 1:
The patent segments the threshold data into machine-specific groups, where each working machine has its own dedicated threshold data set. This allows the system to maintain simple data management structures while achieving precise abnormality detection tailored to each machine's load characteristics.
Solution Approach 2:
The patent applies local quality by customizing the threshold data for each specific working machine based on its unique load characteristics. Instead of using a uniform threshold across all machines, the system adapts the threshold values to match local conditions of each machine, improving detection accuracy.
2Measurement precision
If machine-specific threshold data is maintained for each working machine, then the abnormality detection accuracy is improved, but the ease of operation deteriorates due to complex data setting and switching operations
Solution Approach 1:
The patent implements self-service by automatically switching to the appropriate machine-specific threshold data when a working machine is selected. The system autonomously retrieves and applies the correct threshold set without requiring manual intervention, thereby maintaining high detection accuracy while simplifying operator tasks.
Solution Approach 2:
The patent creates a universal data management system that handles multiple machine-specific threshold sets through a single interface. The system is designed to work with any working machine by automatically adapting to the selected machine's characteristics, providing both precision and ease of use.
3Productivity
If tools are replaced based on processing count alone, then the productivity is maintained through regular replacement, but the loss of substance increases due to disposal of still-useful tools
Solution Approach 1:
The patent implements feedback by continuously monitoring the actual load experienced by each tool during processing and comparing it against machine-specific threshold values. This feedback mechanism allows the system to determine tool replacement timing based on actual usage conditions rather than fixed schedules, preventing premature replacement of still-useful tools while maintaining productivity.
Solution Approach 2:
The patent applies dynamics by making the tool replacement criterion adaptive rather than static. Instead of using a fixed processing count threshold, the system dynamically adjusts replacement timing based on actual load conditions monitored during operation, allowing tools to be used until their true capacity is exhausted.
Data Source
AI summary
A diagnostic apparatus (10) diagnoses the existence of an abnormality in a tool for processing of a processing target by each of multiple working machines. The diagnostic apparatus (10) includes an acquirer (110) and a diagnoser (160). The acquirer (110) acquires program identification information identifying a program executed in each of the working machines, tool information indicating a type of the tool applied to processing, and transition information indicating transition of load in the working machine from the start to the end of the processing executed by execution of the program, at execution of the processing in the working machine. The diagnoser (160) diagnoses whether an index value of the load obtained from the transition information is out of a predetermined range corresponding to a combination of the program identification information, the tool information, and machine information identifying the working machine that transmits the transition information.