Sustainability Recommendation Platform for Industrial Process Adjustments
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Solution Overview
Problem
Enterprises face challenges in staying updated with rapidly changing sustainability best practices for industrial automation systems, making it difficult to improve their performance in tracked sustainability metrics such as energy consumption, emissions, and waste production.
Innovation Solution
A system and method that involves receiving operational data from industrial automation systems, modeling processes to identify adjustments that enhance sustainability metrics, and generating recommendations for implementing these adjustments, which can be automatically or manually executed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If enterprises attempt to improve sustainability metrics by implementing new practices, then sustainability performance improves, but the difficulty of staying updated with rapidly changing best practices increases
Solution Approach 1:
The patent introduces an intermediary system (sustainability management platform with AI/ML models) that mediates between the complex external sustainability best practices and the enterprise's internal operations. This intermediary automatically monitors, analyzes, and translates best practices into actionable recommendations, reducing the burden on enterprises to manually track and interpret rapidly changing sustainability standards while improving sustainability performance
2Reliability
If enterprises manually track and implement sustainability best practices, then sustainability metrics can be improved, but the time and resources required increase significantly
Solution Approach 1:
The system enables self-service by automatically monitoring sustainability metrics, analyzing operational data, and generating optimization recommendations without requiring continuous manual intervention. The AI/ML models continuously learn from new sustainability best practices and automatically apply them to the enterprise's context, freeing employees from manually tracking and implementing updates while maintaining improved sustainability performance
3Measurement precision
If comprehensive operational data is collected from industrial automation systems, then sustainability analysis accuracy improves, but data processing complexity and computational requirements increase
Solution Approach 1:
The patent segments the complex data processing task into multiple specialized AI/ML models that handle different aspects of sustainability analysis separately (e.g., energy consumption models, emissions models, waste management models). Each model processes specific types of operational data independently, then their results are integrated to provide comprehensive sustainability insights. This segmentation maintains high measurement precision while reducing overall system complexity through modular architecture
Data Source
AI summary
A system includes processing circuitry and a memory. The memory stores instructions that, when executed by the processing circuitry, cause the processing circuitry to receiving operational data captured from an industrial automation system performing an industrial automation process, model the industrial automation process based on the operational data, model one or more adjustments to the industrial automation process, identify that the modeling of the one or more adjustments to the industrial automation process indicates that the one or more adjustments to the industrial automation process improve one or more sustainability metrics for the industrial automation process, generate one or more sustainability recommendations to implement the one or more adjustments to the industrial automation process, and implement the one or more adjustments to the industrial automation process.