Robot Alarm Prediction During Teaching Operations
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Solution Overview
Problem
In robot systems, operators often fail to correctly address program errors or communication issues during teaching operations, leading to repeated alarms and potential accidents due to the lack of effective prediction and notification systems for past alarm occurrences.
Innovation Solution
An alarm notification system that stores past alarm data and uses a judging section to predict potential future alarms, notifying operators through augmented reality devices during teaching operations, allowing for visual, auditory, or haptic alerts when specific conditions are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional alarm display methods are used, then alarm information can be shown, but operators cannot predict future alarms and may repeat mistakes
Solution Approach 1:
The system performs preliminary actions by storing past alarm data and proactively predicting future alarms before they occur. The judging section compares current program execution status with historical alarm patterns to issue warnings in advance, allowing operators to correct issues before they manifest as actual alarms.
Solution Approach 2:
The system implements feedback by continuously monitoring program execution and comparing it against stored alarm history. The alarm predicting section provides feedback to operators about potential future alarms based on patterns detected in past alarm occurrences, creating a closed-loop system that learns from historical data.
2Productivity
If operators manually correct programs after alarms occur, then immediate issues can be addressed, but repeated alarms may occur due to human error or oversight
Solution Approach 1:
The system performs preliminary corrections by warning operators of upcoming alarms before they occur during program execution. This allows operators to proactively modify programs to prevent repeated alarm conditions, rather than reacting after alarms have already interrupted operation.
Solution Approach 2:
The system enables self-service by automatically analyzing program execution patterns and generating alarm predictions without requiring manual intervention. The judging section autonomously compares current status with historical data and triggers warnings, reducing reliance on operator memory and attention.
3Ease of operation
If simple alarm notification is used, then system complexity is low, but operator awareness of impending issues is insufficient
Solution Approach 1:
The system introduces an intermediary alarm predicting section that acts as a mediator between the judging section's analysis and the operator. This intermediary translates complex pattern recognition results into simple, actionable warnings that enhance operator awareness without requiring the operator to understand the underlying complexity.
Solution Approach 2:
The system replaces mechanical reliance on operator memory and attention with an automated electronic prediction system. The judging section and alarm predicting section use computational methods to analyze patterns and generate warnings, substituting human cognitive limitations with electronic processing capabilities.
Data Source
AI summary
An alarm notification system configured to assist an operator so that the operator can effectively carry out a teaching operation, etc. The alarm notification system includes: a storing section configured to, with respect to a past alarm which occurred when a program generated by a teach pendant was executed, store alarm data including a name of the program and a number of a line of the program when the alarm occurred; a judging section configured to judge as to whether or not an alarm prediction condition using the alarm data stored in the storing section is satisfied, when the program is executed again; and an alarm predicting section configured to notify the operator who is carrying out teaching of the robot of alarm information relating to the alarm, when the alarm prediction condition is satisfied.