Recycled Fibre Line Control via Multivariable Predictive Optimization
Solution Overview
Problem
The quality of recycled fiber pulp produced in recycled fiber lines is inconsistent due to varying raw material quality and limited automation, leading to suboptimal chemical and mechanical processing, which affects the end product's quality and efficiency.
Innovation Solution
Implementing a method that measures fiber and ink characteristics and uses multivariable-based predictive calculations to optimize control variables for both pulping and dispersing subprocesses, enhancing mechanical and chemical processing to ensure homogeneous pulp quality and reduce chemical and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual control methods are used for recycled fiber line processes, then device complexity is reduced, but manufacturing precision and product quality deteriorate
Solution Approach 1:
The system changes control parameters dynamically based on measured fiber and ink characteristics. The controller adjusts mechanical processing parameters (screen speed, water flow rate) and chemical processing parameters (chemical dosage, concentration) in real-time to maintain consistent pulp quality despite varying raw material input
Solution Approach 2:
The patent replaces manual mechanical control with an automated control system that uses sensors to measure fiber and ink characteristics and automatically adjusts processing parameters. This substitution of manual operation with automated measurement and control systems resolves the contradiction between simplicity and precision
2Extent of automation
If conventional minimal automation is applied, then device complexity remains low, but productivity and process optimization deteriorate
Solution Approach 1:
The system implements continuous feedback by measuring fiber and ink characteristics throughout the process and using this information to automatically adjust processing parameters. This closed-loop feedback mechanism enables the automation to actually improve productivity by optimizing chemical and mechanical processing in real-time based on actual material conditions
Solution Approach 2:
The control system performs self-adjustment by automatically modifying processing parameters based on sensor measurements without requiring external intervention. The system serves itself by detecting material variations and autonomously optimizing its own operation to maintain high productivity
3Quantity of substance
If non-optimized chemical and mechanical processing is used, then processing cost is reduced, but manufacturing precision and end product quality deteriorate
Solution Approach 1:
The system dynamically adjusts chemical dosage and mechanical processing intensity based on measured material characteristics. By changing these parameters optimally rather than using fixed rates, the system achieves both reduced chemical consumption and improved pulp quality simultaneously
Solution Approach 2:
The control system applies chemical and mechanical processing only to the extent necessary for the given material quality. When raw material is already of good quality, less intensive processing is applied, reducing chemical consumption while maintaining adequate pulp quality
Data Source
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AI summary
Measuring devices (120, 122, 124, 126) measure at least one characteristic of the fibres of recycled fibre pulp and at least one characteristic of ink, and the measuring devices (120, 122, 124, 126) feed the measurement results to controllers (108, 109) of a pulping subprocess (100) and a dispersing subprocess (104), the controllers performing multivariable-based predictive calculation and optimization of control functions. The controllers (108, 109) of the pulping subprocess (100) and the dispersing subprocess (104) generate control variables (116, 118, 516) on the basis of the measurement results for mechanical and chemical processing of the recycled fibre pulp to be performed in the pulping subprocess (100) and the dispersing subprocess (104).