Image Forming Apparatus Conveyance Failure Prediction by Sheet Thickness
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Solution Overview
Problem
Existing image forming apparatuses lack effective methods for predicting the failure timing of sheet conveyance mechanisms, particularly due to variations in sheet thickness and environmental conditions, leading to potential operational failures.
Innovation Solution
The apparatus incorporates a sheet sensor to detect thickness and a conveyance time sensor to track conveyance time, using this data to predict failure timing by storing information in a storage medium and adjusting parameters based on environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sheet conveyance mechanism is used to convey sheets, then productivity is improved, but reliability deteriorates due to potential failure over time
Solution Approach 1:
The system performs preliminary failure prediction by continuously monitoring conveyance time and sheet thickness data, calculating predicted failure timing before actual failure occurs. This allows maintenance to be scheduled in advance, preventing unexpected failures while maintaining high productivity.
Solution Approach 2:
The system implements feedback by continuously acquiring conveyance time information from sheet sensors and sheet thickness information, comparing these against predicted failure timing, and adjusting maintenance schedules accordingly. This closed-loop feedback enables dynamic reliability management.
2Device complexity
If failure prediction is performed without considering sheet thickness, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system applies local quality by categorizing sheets into different thickness groups (first thickness group and second thickness group) and performing separate failure predictions for each group. This allows the prediction algorithm to account for thickness-specific characteristics without requiring complex universal modeling.
Solution Approach 2:
The system changes the parameter of sheet thickness classification to improve prediction accuracy. By using sheet thickness as a discrete parameter to divide prediction scenarios, the system achieves better precision while maintaining manageable complexity through parameter-based segmentation rather than continuous variable modeling.
3Reliability
If conveyance time information is stored for each sheet thickness, then reliability is improved through accurate prediction, but device complexity increases
Solution Approach 1:
The system segments conveyance time data storage by creating separate storage areas for different sheet thickness groups. This segmentation simplifies data management compared to storing all possible variations, as it divides the complex data structure into manageable, thickness-specific categories that are easier to process and analyze.
Data Source
AI summary
An image forming apparatus includes a conveyance mechanism, a sheet sensor, a sheet thickness sensor, and circuitry. The conveyance mechanism conveys a sheet. The sheet sensor detects the sheet conveyed by the conveyance mechanism at a predetermined position on a conveyance path. The sheet thickness sensor detects sheet thickness information indicating a thickness of the sheet. The circuitry acquires conveyance time information indicating a conveyance time taken to convey the sheet in a predetermined section on the conveyance path, according to a detection result of the sheet by the sheet sensor. The circuitry stores the conveyance time information for each thickness of the sheet in a storage medium, and predicts a failure timing of the conveyance mechanism at the predetermined position for each thickness of the sheet, based on the conveyance time information stored in the storage medium and an accumulative number of sheets conveyed by the conveyance mechanism.