Image Forming Apparatus Error Cause Specification via State Change Detection
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Solution Overview
Problem
High-productivity and high-performance image forming apparatuses face challenges in quickly identifying the causal part of an error, leading to prolonged downtime, especially for low-skill operators, as existing systems rely on operators to presume error causes based on operation and action information.
Innovation Solution
An image forming apparatus equipped with causal part candidates, associated components with detectable state changes, detectors, memory for storing state changes, and processors to detect errors and specify the error-causing part using time and stored information, allowing for rapid identification of error causes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If operation information and action information are stored to specify the job that caused an error, then error tracking capability is improved, but the ability to quickly identify the causal part for low-skill operators deteriorates
Solution Approach 1:
The patent introduces an intermediary component (the error specifying device) that mediates between the stored operation/action information and the operator. This device automatically analyzes the stored information, compares it with error patterns, and directly outputs the causal part identification, eliminating the need for operators to manually presume error causes while preserving comprehensive error tracking capabilities
Solution Approach 2:
The system performs self-service by automatically analyzing stored operation and action information to identify error causal parts without requiring operator intervention for the analysis process. The apparatus uses its own stored data to diagnose errors, reducing dependency on operator skill levels while maintaining detailed error tracking
2Productivity
If the number of parts is increased to achieve high-productivity and high-performance capabilities, then apparatus performance is improved, but the risk of error occurrence and complexity of error identification increase
Solution Approach 1:
The patent segments the error identification process into distinct automated steps: detecting state changes of individual components, storing these states with timing information, comparing against error patterns, and identifying causal parts. This segmentation allows the system to handle complex multi-component errors systematically without increasing operator burden, enabling high-performance apparatus with many parts to be diagnosed efficiently
Solution Approach 2:
The system implements feedback by continuously monitoring the state changes of various components and using this feedback information to automatically identify error causal parts. The stored state change information serves as feedback that is analyzed to determine which component caused the error, allowing the complex apparatus to self-diagnose without proportionally increasing identification complexity
Data Source
AI summary
An image forming apparatus that is capable of specifying a causal part of an error on the basis of an occurred phenomenon even for a low-skill operator. Causal part candidates are candidates of parts of the apparatus that can cause an error in the apparatus. An associated component is relevant to one of the causal part candidates and a state change thereof is detectable. A detector detects the state change of the associated component. A memory stores the state change of the associated component detected by the detector in association with detected time. A processor executes a function for detecting the error and a function for specifying an error causing part that is the part causing the error from among the causal part candidates based on time at which the error is detected and information stored in the memory.