Environmental Product Declarations With HPF-Based LCA Scaling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for generating Environmental Product Declarations (EPDs) face challenges such as data uncertainty, resource intensity, expertise requirements, susceptibility to errors, and the need for accurate consideration of multiple environmental impact categories, particularly in electronic products, which are prone to rapid technological change and require mass production.
Innovation Solution
A computer-implemented method for generating EPDs using Homogeneous Product Families (HPFs) that involves defining a HPF, querying a product database for parameters, selecting representative members, conducting LCAs, determining multiparameter linear regression scaling functions, and associating a reference product to generate EPDs on-demand, ensuring accuracy and reproducibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a simple linear regression approach is used to scale EPD results for product portfolios, then the process is simplified and faster, but accuracy deteriorates because product structure complexities and configurations are not well represented
Solution Approach 1:
The patent transitions from single-parameter linear scaling to multi-parameter non-linear regression models that incorporate multiple product characteristics (weight, dimensions, material composition, power ratings). This dimensional expansion allows the model to capture complex product structure variations while maintaining computational efficiency through automated database queries and algorithmic processing.
Solution Approach 2:
The patent changes the scaling approach from simple linear relationships to non-linear regression models with multiple parameters. By incorporating product-specific parameters (weight, volume, material types, power consumption) into the regression equations, the system achieves higher accuracy without proportionally increasing computational burden, as parameters are retrieved automatically from product databases.
2Measurement precision
If LCAs are conducted for each individual product to ensure accuracy, then measurement precision is improved, but resource consumption and time requirements worsen
Solution Approach 1:
The patent segments the product portfolio into homogeneous product families (HPFs) based on shared characteristics (product type, technology platform, manufacturing process). Within each HPF, a representative product undergoes full LCA analysis, while other products are scaled using regression models. This segmentation reduces the number of full LCAs required while maintaining accuracy for all products through the scaling relationships established within each homogeneous group.
Solution Approach 2:
The patent performs preliminary LCA analysis on representative products from each homogeneous product family before scaling to individual products. By conducting the resource-intensive LCA work once per HPF rather than per product, the system prepares accurate baseline data that can be efficiently scaled to generate EPDs for entire product portfolios, significantly reducing total resource consumption.
3Productivity
If scaling parameters are used to generate EPDs for all members of an HPF, then productivity is improved, but measurement precision deteriorates because other environmental impact categories are affected differently by individual product characteristics
Solution Approach 1:
The patent applies different scaling parameters and regression models to different environmental impact categories based on their specific sensitivities to product characteristics. For example, climate change impacts may scale primarily with weight and material composition, while resource use impacts may scale with power consumption and operational lifetime. This localized approach ensures each impact category is scaled using the most appropriate parameters, maintaining accuracy across diverse environmental dimensions.
Solution Approach 2:
The patent creates a universal scaling framework that handles multiple environmental impact categories simultaneously through a integrated regression model system. The same multi-parameter regression infrastructure serves all impact categories (climate change, resource use, toxicity, etc.), with each category utilizing its specific set of relevant parameters. This universal approach enables mass EPD generation while maintaining category-specific accuracy through appropriate parameter selection for each environmental dimension.
Data Source
AI summary
A method and system for the mass production of Environmental Product Declarations for products is provided. The EPD relies on the production of a Life Cycle Assessment using a scaling approach based on representative products.