Product Environmental Impact Evaluation Using Material Prediction Data
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Solution Overview
Problem
Existing emission simulation systems fail to accurately calculate the carbon dioxide emissions specific to individual products based on user-defined circumstances, lacking consideration for product-specific details.
Innovation Solution
An environmental impact evaluation system that includes a storage unit, prediction information generation unit, and environmental indicator calculation unit to generate and calculate environmental indicators based on product identification, material, and manufacturing information, allowing for personalized environmental impact assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If generic emission data from suppliers is used for all products, then the system complexity is reduced and ease of operation is improved, but the measurement precision of carbon dioxide emissions for individual products deteriorates
Solution Approach 1:
The patent segments the emission evaluation into two parts: generic supplier data for baseline estimation and product-specific customization data for precise calculation. This allows the system to maintain ease of operation through automated generic data processing while achieving high measurement precision by incorporating user-provided product-specific parameters such as material composition, manufacturing processes, and product lifespan.
Solution Approach 2:
The patent applies local quality by allowing different levels of data specificity for different products. Products can be evaluated using either generic supplier data alone or a combination of generic data and product-specific customization data. This enables the system to adapt the measurement precision to the specific needs of each product while maintaining overall operational simplicity.
2Measurement precision
If product-specific customization data is collected and processed, then the measurement precision of environmental impact evaluation is improved, but the device complexity and difficulty of detecting and measuring increase
Solution Approach 1:
The patent implements preliminary action by pre-establishing the generic emission data database from suppliers before product-specific evaluation is needed. This baseline data structure is prepared in advance, allowing the system to quickly process individual product evaluations by simply adding product-specific parameters without requiring complex system reconfiguration.
Solution Approach 2:
The patent introduces an intermediary calculation mechanism that combines generic supplier data with product-specific customization data. This intermediary processing layer integrates two different data sources with varying levels of specificity, enabling the system to achieve high measurement precision without requiring complete redesign of the evaluation architecture for each product.
3Reliability
If comprehensive product information is stored and processed, then the reliability of environmental impact evaluation is improved, but the quantity of information and data management complexity increase
Solution Approach 1:
The patent segments information storage into hierarchical levels: Level 1 contains generic emission data from suppliers applicable to all products, Level 2 contains product-specific customization data such as material composition and manufacturing processes, and Level 3 contains usage-specific data. This segmentation allows the system to manage large quantities of information systematically while ensuring reliability through multi-level data validation.
Solution Approach 2:
The patent creates a universal data framework that can handle both generic supplier data and product-specific customization data within a single evaluation system. This multi-functional data structure allows the same system architecture to process varying quantities of information depending on product complexity, maintaining reliability without proportionally increasing data management complexity.
Data Source
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AI summary
An environmental impact evaluation system 10 includes: a storage unit 110 that stores identification information for identifying the product, the identification information being associated with related information of the product corresponding to a user who uses the product, material information related to a material of the product, and manufacturing information related to manufacturing of the product; a prediction information generation unit 120 that generates prediction information including: material prediction information related to a material of the product generated in relation to manufacturing of the product corresponding to the identification information; and manufacturing prediction information related to the product, based on the material information and the manufacturing information; an environmental indicator calculation unit 130 that calculates a first environmental indicator, based on the prediction information including the material prediction information and the manufacturing prediction information; and an output unit 140 that outputs the calculated first environmental indicator.