Dynamic Multi-Component Product Formulation Control
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Solution Overview
Problem
Existing product production methods rely on guesswork and limited data, leading to inefficiencies in raw material utilization, inconsistent product attribute profiles, and suboptimal decision-making, particularly due to reliance on a small number of experts and outdated demand forecasting.
Innovation Solution
A method and system that adjust the ratios and amounts of product components in real-time based on data processing and consumer intelligence to maintain a target product attribute profile, minimizing deviations and optimizing raw material usage while linking consumer demand with manufacturing supply.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional demand forecasting and production planning methods are used, then production decisions can be made with limited data and expert judgment, but manufacturing efficiency is reduced and raw material waste increases
Solution Approach 1:
The system implements continuous feedback loops where product attribute data from production is fed back to the optimization module, which adjusts component ratios in real-time. This closed-loop control enables dynamic optimization of production parameters, improving manufacturing efficiency while minimizing raw material waste through data-driven decision-making.
Solution Approach 2:
The optimization module dynamically changes production parameters (component ratios, amounts, and specifications) based on real-time data analysis. By continuously adjusting these parameters to optimize for both efficiency and material utilization, the system resolves the contradiction between manufacturing productivity and raw material waste reduction.
2Manufacturing precision
If fixed product formulations are used, then production processes are simple and consistent, but product attribute profile consistency cannot be maintained when component supply varies
Solution Approach 1:
The system transitions from static fixed formulations to dynamic adaptive formulations. The optimization module continuously adjusts component ratios and amounts based on real-time component attribute data, enabling the production process to adapt to supply variations while maintaining consistent product attribute profiles. This dynamic approach balances manufacturing precision with manageable process complexity.
Solution Approach 2:
The system enables self-adjusting production formulations through automated optimization. The optimization module autonomously determines optimal component combinations based on available component data, eliminating the need for manual formulation adjustments and reducing production process complexity while maintaining attribute consistency.
3Measurement precision
If expert judgment and rule of thumb are used for production decisions, then decision-making is simple and quick, but decision accuracy and optimization are reduced
Solution Approach 1:
The system replaces manual expert judgment with automated data processing and optimization algorithms. The optimization module rapidly analyzes component attribute data and calculates optimal formulations, providing decision accuracy superior to human experts while reducing decision-making time through automated computational processes.
Solution Approach 2:
The optimization module serves as an intermediary between raw component data and production decisions. It processes and interprets component attribute data, translating complex information into optimized formulation recommendations, thereby enhancing decision accuracy while maintaining quick response times through automated mediation.
4Loss of substance
If component ratios are adjusted to accommodate supply variations, then raw material utilization is optimized, but product attribute profile consistency may be compromised
Solution Approach 1:
The optimization module simultaneously optimizes multiple parameters (component ratios, amounts, and specifications) to achieve both improved raw material utilization and maintained product attribute consistency. By changing these parameters in coordinated fashion based on real-time data, the system resolves the contradiction between material efficiency and attribute precision.
Solution Approach 2:
The system applies different component ratios and specifications to different product batches or components based on their specific attributes and availability. This localized optimization allows each component to be utilized most efficiently while the overall formulation maintains consistent product attribute profiles through balanced composition adjustments.
Data Source
AI summary
There is provided a method of regulating the formulation of a multi-component product comprising a product attribute profile, the method comprising providing a first and second component of the product, each component having a component attribute profile; supplying to a product formulation zone the first component and the second component in a desired ratio and combining the first and second components together to provide the product or a precursor thereof to yield a target product attribute profile; responsive to a change or predicted change in at least one component attribute profile, supplying information concerning the attribute change to a data processing apparatus and calculating with respect to that change an adjustment in the ratio to reduce the deviation of one or more attributes of the product attribute profile from the target product attribute profile. A production system is also provided.