Colorant Usage Prediction via Linear and Non-Linear Functions
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Solution Overview
Problem
Current printing technologies lack accurate prediction methods for colorant usage in printing devices, leading to premature or delayed replacement, which can result in poorly printed images or device shutdown due to lack of colorant, and inefficient management of spare colorants.
Innovation Solution
A prediction server that uses a combination of linear and non-linear functions, based on historical colorant usage rates, to estimate colorant usage in printing devices, providing a confidence interval for the prediction, and incorporating device information, maintenance events, and data from similar devices to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If colorant replacement is performed based on fixed schedules or simple thresholds, then device operation is simplified, but prediction accuracy deteriorates leading to premature or delayed replacement
Solution Approach 1:
The system transforms the prediction approach from fixed thresholds to dynamic parameter-based prediction using linear and non-linear functions that adapt to individual device characteristics, usage patterns, and environmental factors, thereby improving accuracy while maintaining operational simplicity
Solution Approach 2:
The patent replaces simple threshold-based mechanical decision systems with a computational prediction system that uses mathematical functions (linear and non-linear) to calculate colorant usage rates, enabling more accurate predictions without significantly increasing operational complexity
2Reliability
If colorant is replaced frequently to ensure availability, then device reliability is improved, but loss of substance increases due to premature replacement
Solution Approach 1:
The system performs preliminary prediction of colorant depletion timing using usage rate functions, allowing proactive scheduling of replacements at the optimal moment rather than relying on frequent preventive replacement, thus reducing waste while ensuring availability
Solution Approach 2:
The prediction system continuously monitors actual colorant usage against predicted usage rates, providing feedback that refines future predictions and enables increasingly accurate timing of replacements, reducing both waste and reliability risks
3Measurement precision
If detailed monitoring and complex prediction models are implemented, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The prediction system is segmented into modular components: data collection modules, linear function calculation modules, non-linear function calculation modules, and output generation modules. This segmentation allows complex functionality to be implemented through simple, independent components that can be managed and maintained separately
Solution Approach 2:
The patent introduces intermediary computational layers (linear functions and non-linear functions) that process raw usage data and transform it into meaningful predictions, acting as mediators between simple data collection and complex decision-making, thereby managing overall system complexity
4Measurement precision
If colorant usage is monitored continuously with high precision, then prediction accuracy is improved, but loss of time increases due to data processing
Solution Approach 1:
The system implements partial monitoring by focusing on key usage parameters rather than complete continuous monitoring, and uses incremental updates to prediction functions, performing calculations only when necessary to maintain accuracy without excessive processing overhead
Data Source
AI summary
Methods and apparatus for predicting colorant usage by printing devices are provided. A prediction server can receive a request to predict colorant usage for a first printing device. The prediction server can determine first plurality of functions to predict colorant usage for the first printing device. The first plurality of functions can include at least one linear function and at least one non-linear function. The first plurality of functions can be based on colorant-usage rates indicating historical rates of change in colorant used by the first printing device. The prediction server can determine a prediction of colorant usage for the first printing device using the first plurality of functions. The prediction server can provide an output involving the prediction of colorant usage for the first printing device, where the prediction of colorant usage can include a confidence interval related to the prediction.