Normalized Environmental Impact Models for Manufacturing Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for collaborative environmental impact optimization of manufacturing processes are inefficient due to the iterative and experience-based nature of decision-making, which complicates the quantification and reduction of environmental impacts across supply chains.
Innovation Solution
A computer-implemented method and apparatus that utilize normalized environmental impact calculation models to optimize manufacturing processes by connecting input data from chemical products to describe functional relationships between environmental impact metrics and product properties, enabling collaborative optimization without revealing proprietary data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If iterative decision-making using human expertise is used to optimize manufacturing processes, then specialized knowledge and experience can be applied, but the process becomes time-consuming and complex, making environmental impact quantification difficult
Solution Approach 1:
The patent replaces manual iterative decision-making with automated machine learning models. The system uses trained models to predict environmental impacts and optimize manufacturing processes automatically, eliminating the need for repeated human expert interventions while maintaining decision quality through data-driven predictions.
Solution Approach 2:
The system transforms qualitative expert judgments into quantitative parameters by training machine learning models on historical data. This converts the iterative decision process into a direct parameter prediction problem, where the model outputs optimized process parameters directly without time-consuming iterative discussions.
2Object-generated harmful factors
If collaborative optimization across supply chains is implemented, then environmental impacts can be reduced, but data privacy and anti-trust regulations create barriers to information sharing
Solution Approach 1:
The patent introduces a neutral third-party platform that facilitates collaborative optimization without direct data sharing between companies. The system acts as an intermediary that enables environmental impact assessment and optimization while keeping proprietary data within each company's secure environment, thus resolving the conflict between collaboration needs and data privacy requirements.
3Object-generated harmful factors
If environmental impact metrics are quantified and optimized, then sustainability can be improved, but the complexity of quantifying and certifying environmental product information increases
Solution Approach 1:
The system enables companies to self-assess and self-optimize their environmental impacts using automated machine learning models. Instead of requiring complex external certification processes, the system provides transparent, auditable predictions that companies can use independently, reducing the complexity of environmental quantification while maintaining reliability through model transparency and data provenance tracking.
Data Source
AI summary
A computer-implemented method for collaborative environmental impact optimization of manufacturing processes, the method comprising the steps of: receiving, by at least one processor and via a communication interface, first input data relating to at least one chemical product comprising environmental impact metrics data related to environmental impact metrics and product property data related to chemical or physical properties of the at least one chemical product; and second input data relating to at least one chemical product comprising environmental impact metrics data related to environmental impact metrics and product property data related to chemical or physical properties of the at least one chemical product; determining a first normalized environmental impact calculation model for the first input data, the first normalized environmental impact calculation model describing a functional relationship between the environmental impact metrics data and the product property data; and determining a second normalized environmental impact calculation model for the second input data, the second normalized environmental impact calculation model describing a functional relationship between the environmental impact metrics data and the product property data; connecting the first normalized environmental impact calculation model and the second normalized environmental impact calculation model to a connected normalized environmental impact calculation model; and providing, by the at least one processor, output data of the connected normalized environmental impact calculation model over a variable value range, and based on the output data optimizing the manufacturing processes.