MFP Simulation Device for Dynamic Parameter Optimization
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Solution Overview
Problem
Multi-function peripherals (MFPs) exhibit performance variability due to differences in user functions and data processing, making it difficult to determine optimal setting values that are common across multiple users, and existing technologies struggle to adapt the device settings to suit varying user environments effectively.
Innovation Solution
A simulation device and method that includes a simulator, a virtual execution controller, a parameter determinator, and a setter, which simulate an MFP's operation in a virtual environment, adjust parameters to meet admissibility conditions, and then apply these changes to the actual MFP to optimize its performance for the specific user environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the MFP uses fixed settings, then the device configuration is simple and easy to operate, but the performance cannot be sufficiently exhibited for different users with different functions and data processing needs
Solution Approach 1:
The patent applies preliminary action by pre-configuring multiple parameter sets corresponding to different usage environments (e.g., home use, office use, high-volume printing) before the user actually needs them. The controller pre-processes and stores optimized parameters for various scenarios, so when a user selects a specific usage type, the appropriate parameters are already prepared and can be applied immediately without complex real-time calculations or user adjustments.
Solution Approach 2:
The patent implements parameter changes by providing a plurality of parameter sets that can be selected based on different usage environments. Each parameter set contains optimized values for various device operations (printing speed, resolution, memory allocation, CPU core assignment) tailored to specific user needs. The controller dynamically switches between these parameter sets based on the selected usage type, enabling the same hardware to adapt its behavior to different operational requirements without physical modification.
2Measurement precision
If verification information is output for each processing step, then the user can identify problematic steps, but the user must manually determine setting values and cannot easily find optimal common settings for multiple users
Solution Approach 1:
The patent applies self-service by enabling the controller to automatically evaluate the effectiveness of each parameter set based on actual device performance data and user feedback. The system monitors operational metrics (printing speed, error rates, resource utilization) and automatically determines which parameter sets work best for different usage environments. This eliminates the need for users to manually analyze verification information and calculate optimal settings, as the system performs this optimization autonomously through automated evaluation and selection of the most effective parameter sets.
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring device performance metrics and user interactions with different parameter sets. The controller collects data on how well each parameter set performs in real-world conditions and uses this feedback to refine future parameter selections. This feedback loop allows the system to learn from actual usage patterns and automatically improve its ability to recommend or apply optimal settings for different user environments without requiring manual user analysis.
3Adaptability or versatility
If the MFP processes different types and amounts of data for different users, then the device can serve diverse user needs, but the performance varies significantly across different user environments
Solution Approach 1:
The patent applies segmentation by dividing the parameter configuration into multiple distinct parameter sets, each optimized for specific usage environments (e.g., low-volume home printing, high-volume office printing, color-intensive tasks, monochrome tasks). Each parameter set contains segmented configurations for different device components (CPU core assignments, memory allocation, buffer sizes, processing priorities). This segmentation allows the system to select the appropriate pre-configured parameter set based on the specific data type and volume requirements, ensuring consistent optimal performance for each usage scenario rather than relying on a single general-purpose configuration.
Data Source
AI summary
A simulation device includes: a simulator simulating an information processing device; a virtual execution controller executing a job identical to a job executed by the information processing device, while a parameter different from a parameter set in the information processing device, is set in a virtual device in which the simulator simulates the information processing device, by controlling the simulator, when the information processing device is out of a preset admissibility condition; a parameter determinator determining the parameter set in the virtual device, as a change parameter, when the virtual device while the virtual device executes the job, satisfies the admissibility condition; and a setter controlling the information processing device such that the determined change parameter is set in the information processing device, when an environment of the information processing device becomes identical to an environment when the information processing device is out of the admissibility condition.