CO2 Emissions Estimation Using Dual Models for Printers
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Solution Overview
Problem
Existing CO2 emissions estimation systems for image forming apparatuses suffer from low accuracy due to the use of simplified models that do not account for varying job execution and setting conditions, leading to inaccurate CO2 emission estimates.
Innovation Solution
A CO2 emissions estimation system that employs a dual estimation model: a job execution date model for when a job is performed and a job non-execution date model for when no job is executed, utilizing multiple regression analysis and machine learning to incorporate job execution information and setting values, enhancing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single simplified estimation model is used for all conditions, then the device complexity is reduced and ease of operation is improved, but the measurement precision of CO2 emissions estimation deteriorates
Solution Approach 1:
The patent divides the estimation model into multiple segments: a first estimation model for job execution dates and a second estimation model for job non-execution dates. Each model is optimized for its specific condition, allowing high measurement precision for each segment while keeping individual model complexities manageable. This segmentation resolves the contradiction by achieving overall high accuracy through specialized sub-models rather than requiring one overly complex universal model.
2Measurement precision
If multiple estimation models are used to account for varying conditions, then the measurement precision of CO2 emissions estimation is improved, but the device complexity increases
Solution Approach 1:
The system dynamically selects between the first estimation model and the second estimation model based on whether it is a job execution date or a job non-execution date. This dynamic adaptation allows the system to automatically adjust to varying conditions without requiring manual intervention, thereby maintaining ease of operation while achieving high measurement precision through condition-specific models.
3Reliability
If simplified estimation models are used, then the ease of operation is improved and device complexity is reduced, but the reliability of emission calculations deteriorates
Solution Approach 1:
The patent segments the estimation system into two distinct models: one for job execution dates that accounts for power consumption during actual printing operations, and another for job non-execution dates that accounts for idle power consumption. This segmentation enables each model to be tailored to its specific operational context, significantly improving the reliability of emission calculations for each scenario while keeping the overall system manageable through clear structural division.
Data Source
AI summary
A CO2 emissions estimation system includes a control device including a processor and functioning, through the processor executing a CO2 emissions estimation program, as an emissions estimator. The emissions estimator determines an estimated value of CO2 emissions from an image forming apparatus, using an estimation model as a formula for estimating the emissions. When a number of sheets subjected to a particular job on the image forming apparatus in a specified period is 1 or more, the emissions estimator determines an estimated value of the emissions in the specified period using a first estimation model as the estimation model. When the number of sheets subjected to the particular job in the specified period falls short of 1, the emissions estimator determines an estimated value of the emissions in the specified period using as the estimation model a second estimation model different from the first estimation model.