Oxidizing Agent Distribution in Pulp Bleaching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The delignification process in pulp bleaching cycles is complex and inconsistent, leading to variability in product quality and inefficiencies due to inconsistent chemical reactions and waste generation.
Innovation Solution
A method that involves obtaining incoming and target kappa values, generating a sequence kappa factor and a total equivalent chlorine (TEC) factor using a model, simulating scenarios for oxidizing agent dosages, determining a total consumption score for each scenario, selecting the scenario with the lowest consumption score, and applying the corresponding dosage targets during the pulp bleaching cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional chemical distribution methods are used in delignification, then the bleaching process can be performed, but product quality consistency deteriorates due to varying chemical reaction rates and inconsistent chemical consumption
Solution Approach 1:
The system implements a feedback mechanism by continuously monitoring chemical consumption in real-time during the bleaching process and using this data to adjust subsequent chemical dosing. The model learns from historical data and actual process outcomes to refine dosage recommendations, ensuring consistent product quality despite variations in raw material properties or process conditions.
Solution Approach 2:
The chemical distribution system transitions from static, pre-determined dosing schedules to dynamic, real-time adjustment based on actual process conditions. The model continuously adapts dosage recommendations based on current chemical consumption rates, pulp properties, and process stage, allowing the system to respond to changing conditions and maintain reaction consistency.
2Manufacturing precision
If higher amounts of oxidizing agents are applied to ensure adequate delignification, then the target kappa value can be achieved, but chemical consumption and waste increase
Solution Approach 1:
The system applies the principle of partial action by determining the minimum necessary chemical dosage required to achieve the target kappa value rather than applying excessive amounts. The model calculates precise dosing requirements based on real-time process data and historical learning, applying only the necessary amount of oxidizing agents needed for effective delignification without over-treatment.
Solution Approach 2:
The system dynamically adjusts chemical dosage parameters based on actual process conditions, pulp properties, and process stage. By changing the dosage parameter in real-time rather than using fixed high dosages, the system achieves target kappa values while minimizing chemical consumption and waste.
3Manufacturing precision
If multiple different chemicals are used at different processing stages to achieve desired characteristics, then product quality can be improved, but process complexity increases due to varying reaction rates and coordination requirements
Solution Approach 1:
The control system serves multiple functions: it monitors chemical consumption, tracks process stage, determines pulp properties, calculates optimal dosages, and controls distribution across multiple bleaching stages. This multi-functional model simplifies the overall process control architecture by consolidating what would otherwise require multiple separate control systems into a single integrated platform.
Solution Approach 2:
The system manages the complexity of multiple chemicals by dynamically adjusting their dosage parameters based on process stage, pulp properties, and real-time consumption data. Rather than requiring complex manual coordination of each chemical, the model automatically optimizes dosing parameters for all chemicals throughout the process, achieving desired product characteristics while simplifying control.
4Productivity
If real-time monitoring and simulation of multiple scenarios are implemented to optimize chemical dosing, then chemical consumption efficiency improves, but computational requirements and system complexity increase
Solution Approach 1:
The system performs preliminary computational work by pre-processing historical data and building predictive models that can quickly evaluate multiple dosing scenarios in real-time. By preparing the computational framework in advance and using pre-trained models, the system can rapidly simulate different dosing strategies without requiring heavy real-time computation, thus improving chemical efficiency while managing system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach optimizes the distribution of oxidizing agents, minimizing waste and achieving consistent product quality by identifying the most efficient chemical dosages and timing, thereby improving operational efficiency and reducing environmental impact.
Implementation Method 1
a combination of chemicals to achieve a desired bleaching response... different chemicals react differently, and the chemicals have varying reaction rates
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining and applying a distribution of oxidizing agents in delignification of a pulp bleaching cycle. The method obtains an incoming kappa value of an unbleached pulp slurry and a target kappa value expected for a bleached pulp slurry. A model generates a sequence kappa factor based on these values, and a total equivalent chlorine (TEC) factor from the sequence kappa factor and the incoming kappa value. Scenarios are simulated using the TEC factor, each scenario specifying a unique distribution of dosage targets for oxidizing agents and having a total consumption score for the oxidizing agents that is determined based on the dosage targets for the oxidizing agents. A scenario with the lowest total consumption score is selected, and the model applies the dosage targets of oxidizing agents for the selected scenario during the pulp bleaching cycle.