Feedstock Demand Allocation for Co-Product Mass Balance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current chemical production processes face challenges in accurately allocating feedstock demand to co-products with different characteristics, leading to inaccurate environmental impact assessments and inefficient resource management.
Innovation Solution
A computer-implemented method and system that calculates feedstock demand for multiple chemical products by receiving input material and process data, identifying process steps producing co-products, and using steering logic to adjust feedstock demands based on deviation values, ensuring accurate allocation of sustainable feedstock demand and environmental attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional feedstock allocation systems are used, then the calculation process is simple, but the accuracy of feedstock demand allocation to co-products deteriorates
Solution Approach 1:
The patent segments the feedstock demand calculation into multiple components: mass fraction feedstock demand, energy fraction feedstock demand, and substitution feedstock demand. Each component addresses specific aspects of co-product allocation, allowing for precise differentiation of feedstock consumption across products with varying characteristics while maintaining systematic organization through modular calculation approaches.
Solution Approach 2:
The patent introduces multiple parameters to enhance allocation accuracy including deviation values that compare mass-based and energy-based allocations, target values that define acceptable deviation thresholds, and substitution factors that adjust feedstock demand based on co-product characteristics. These parameter changes enable dynamic adaptation of allocation methods to specific process conditions and product properties.
2Measurement precision
If co-products with different characteristics are allocated using uniform methods, then the allocation process is efficient, but the accuracy of environmental impact assessment deteriorates
Solution Approach 1:
The patent applies local quality by differentiating allocation methods based on specific co-product characteristics. Each co-product receives customized feedstock demand calculation considering its unique properties such as mass fraction, energy content, and substitution requirements. This localized approach ensures that environmental impact assessments accurately reflect the specific characteristics of each product rather than applying blanket allocation methods.
Solution Approach 2:
The patent introduces dynamic adjustment mechanisms through deviation value calculations and substitution logic. The system dynamically selects and adjusts allocation parameters based on real-time comparisons between mass-based and energy-based feedstock demands, allowing the allocation process to adapt to varying process conditions and co-product characteristics while maintaining operational efficiency.
3Manufacturing precision
If substitution logic is applied to adjust feedstock demand, then the accuracy of feedstock allocation improves, but the calculation complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-calculating mass fraction feedstock demand and energy fraction feedstock demand before applying substitution logic. The system预先 determines deviation values and compares them against target values to decide whether substitution is necessary. This preliminary structuring of calculations reduces the complexity of the substitution logic itself by preparing all necessary parameters in advance.
Solution Approach 2:
The patent employs feedback mechanisms where deviation values provide information about the difference between mass-based and energy-based allocation approaches. This feedback drives the substitution logic to adjust feedstock demand calculations when deviations exceed target thresholds, creating a self-correcting system that automatically refines allocation precision based on calculated discrepancies without requiring complex external intervention.
Data Source
AI summary
Disclosed are computer-implemented systems and methods for an automated determination of a mass balance feedstock demand for chemical products produced in a chemical production process of a production plant.