Component-Specific Consumption Data Simulation for Sustainability
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Solution Overview
Problem
Current industrial monitoring systems lack a comprehensive view of sustainability factors, particularly at the component level, leading to inaccurate estimates and inefficiencies in energy use and emissions management, which can result in increased expenses and operational bottlenecks.
Innovation Solution
A simulation tool that associates discrete consumption data with precise consumption points in a system, allowing for dynamic modeling and optimization of component-specific sustainability factors, enabling more accurate forecasting and decision-making by attributing consumption and sustainability data to specific processes or components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-level energy and byproduct totals are monitored, then sustainability factors can be tracked, but comprehensive component-level understanding is lost
Solution Approach 1:
The patent segments the facility into discrete consumption points, each representing specific components or processes. This segmentation enables component-level monitoring of energy and material consumption while maintaining manageable system complexity through modular data collection and aggregation structures.
Solution Approach 2:
The patent adds a spatial dimension to monitoring by geocoding consumption points within the facility. This dimensional approach allows comprehensive component-level tracking without proportionally increasing complexity, as the structured spatial framework enables efficient data organization and analysis.
2Measurement precision
If seasonal historical data is used for forecasting, then future quantities can be estimated, but accuracy is compromised
Solution Approach 1:
The patent implements preliminary action by continuously collecting and storing consumption data at discrete points before forecasting is needed. This ongoing data collection establishes a robust historical foundation that improves forecasting accuracy while reducing the time needed for future predictions, as the data infrastructure is already in place.
3Loss of information
If top-down facility perspective is used, then overall consumption is visible, but source-specific expenditures cannot be distinguished
Solution Approach 1:
The patent segments facility consumption into discrete consumption points associated with specific components, processes, or equipment. This segmentation preserves source-specific information while maintaining overall facility visibility, enabling informed decision-making about individual components without sacrificing the big picture view.
Solution Approach 2:
The patent implements feedback mechanisms that provide both top-down facility-wide consumption summaries and bottom-up component-specific details. This multi-level feedback structure eliminates information loss about sources while improving productivity by enabling decisions at appropriate levels of granularity.
Data Source
AI summary
Methods and apparatuses are provided for simulating components and processes using discrete, variable-granularity, component-specific data relating to energy consumption or other sustainability factors. Simulations can be analyzed and optimized to facilitate forecasting of sustainability factors and determine advantageous modifications to the components or processes.