Carriage Motion Diagnosis for Predictive Maintenance in Image Forming
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Solution Overview
Problem
Existing image forming systems fail to predict maintenance needs accurately, leading to unplanned downtime due to unforeseen operational abnormalities.
Innovation Solution
An image forming system equipped with a controller that analyzes time series data of carriage velocity and operation amounts to identify an index value, determining the service life and predicting system failure through changes in this index value over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If system maintenance is performed based on known techniques, then the system can be continuously used, but the downtime occurs or is prolonged because the failure time cannot be predicted
Solution Approach 1:
The system performs preliminary diagnosis by analyzing vibration signals and calculating diagnosis values before actual failure occurs. The controller continuously monitors the carriage moving mechanism and predicts future failures by comparing current diagnosis values against threshold values, enabling maintenance to be performed in advance rather than reacting to actual failures.
Solution Approach 2:
The system implements a feedback mechanism where the controller receives encoder signals from the carriage, calculates diagnosis values based on vibration analysis, compares these values against threshold values, and provides feedback about the system's health status. This closed-loop feedback enables continuous monitoring and prediction of component degradation.
2Measurement precision
If frequency analysis is performed in real time to diagnose failures, then operational abnormalities can be detected, but the exact failure time prediction is not achieved
Solution Approach 1:
The system calculates diagnosis values from vibration signals and compares them against threshold values in advance to predict future failures. By performing this analysis continuously before failure occurs, the system not only detects operational abnormalities but also provides specific predictions about when components will fail, transforming reactive detection into proactive prediction.
Data Source
AI summary
An image forming system including: a head; a carriage moving mechanism including a carriage, a motor, and a transmission; a motor driver; an encoder; and a controller is provided. The controller is configured to: identify, regarding a certain period being each of the plurality of periods, an index value regarding abnormality of the image forming system based on time series data of a moving velocity, a physical amount related to the moving velocity, or an operation amount observed in a moving control of the carriage in the certain period; and determine an end of a service life of the image forming system or a remaining amount of the service life of the image forming system based on a change of the index value over the plurality of periods.