Cloud Ink Usage Prediction via Probabilistic Models
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Solution Overview
Problem
Estimating ink usage for print tasks is challenging due to unclear ink-drop volumes and changing ink consumption during printing, making it difficult to accurately measure and manage ink costs, which affects print activity efficiency and profitability.
Innovation Solution
A central management unit in a cloud environment monitors user print activities and employs user account plans, such as prepaid and postpaid models, to regulate ink usage, predict ink requirements, and manage ink supplies through data analytics and probabilistic models, ensuring accurate ink ordering and cost management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If ink usage is estimated using fixed cost models, then cost management is simplified, but measurement precision deteriorates due to unclear ink-drop volumes and changing ink consumption
Solution Approach 1:
The patent replaces physical measurement mechanisms (ink volume measurement) with information processing mechanisms (data collection, analysis, and prediction algorithms). The system collects print task information, printer characteristics, and historical data, then uses probabilistic models to predict ink usage, substituting direct physical measurement with computational estimation.
Solution Approach 2:
The patent introduces an intermediary prediction model that acts as a mediator between the printing system and cost management. This model translates complex ink consumption patterns into predictable cost estimates, bridging the gap between variable physical ink usage and stable cost accounting.
2Measurement precision
If detailed monitoring of ink consumption is implemented, then measurement precision improves, but device complexity increases due to interface requirements
Solution Approach 1:
The patent extracts the measurement and prediction functionality from the printer hardware itself and relocates it to a separate information processing system. The printer only needs to provide basic operational data, while the complex analysis and prediction are performed externally, reducing the interface burden on the printing device.
Solution Approach 2:
The patent creates a universal prediction system that can handle multiple types of print tasks, printer models, and ink consumption patterns through a single integrated approach. The system processes various input data types (print task specifications, printer characteristics, historical data) and provides comprehensive ink usage predictions across different scenarios.
3Manufacturing precision
If probabilistic models and data analytics are used to predict ink requirements, then manufacturing precision improves for ink ordering, but loss of time increases due to data processing requirements
Solution Approach 1:
The patent performs preliminary data collection and analysis by maintaining historical print task data, printer characteristics, and ink consumption patterns in advance. This pre-processed data is readily available when prediction is needed, reducing the time required for real-time ink usage estimation while maintaining high accuracy.
Solution Approach 2:
The patent transforms the prediction approach from real-time calculation to probabilistic estimation based on historical parameter patterns. By analyzing past data to establish statistical relationships between print task parameters and ink consumption, the system achieves accurate predictions without requiring complex real-time computations.
Data Source
AI summary
Enabling web management of print usage for a user(s) and/or printer device(s). A central management unit can interact with a plurality of accounts (e.g., prepaid accounts; and/or postpaid accounts), which are associated with users and/or printers—to predict printing activities and regulate printer supplies.