Multivariable Control for Reel Building in Web Manufacturing

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Solution Overview

Problem

Existing methods for controlling reel building and roll runnability in moving web manufacturing, particularly for highly calendered papers, face challenges in selecting appropriate control variables due to complexities such as air entrapment and mass variations, which traditional caliper or reel diameter measurements alone cannot adequately address.

Innovation Solution

A method involving the determination of cross-directional property profiles, generation of nominal response models, and multivariable control targets to adjust actuators, incorporating measurements of reel diameter, caliper, hardness, moisture, tension, and weight, to minimize errors and optimize reel building processes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional caliper or reel diameter measurements are used for control, then the control system is simple, but it cannot adequately distinguish between irregularities caused by air entrapment and mass variations

Engineering Contradiction:
Improveability to distinguish air entrapment from mass variationsVSAvoidcontrol system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent combines multiple measurement variables (reel diameter, caliper, hardness, moisture, tension, weight) into a unified multivariable control system. This merging of measurements enables the system to distinguish between air entrapment and mass variations by analyzing the combined information from all sensors, resolving the limitation of traditional single-variable control.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The control system is designed to handle multiple measurement types and control objectives simultaneously. The multivariable control algorithm processes diverse inputs (diameter, caliper, hardness, moisture, tension, weight) and generates coordinated control actions for multiple actuators, making the system universally applicable to various reel building issues.

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Manufacturing precision

If multiple control variables are used to address different problems (air entrapment vs mass variations), then the control accuracy improves, but the device complexity increases significantly

Engineering Contradiction:
Improvereel building control accuracyVSAvoidmultivariable control system complexity
Core Design Contradiction:
Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent implements a feedback-based multivariable control system that continuously monitors multiple variables (reel diameter, caliper, hardness, moisture, tension, weight) and adjusts actuator positions accordingly. The control algorithm processes feedback from all sensors and generates coordinated control actions, enabling precise reel building while managing system complexity through systematic feedback processing.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The control system dynamically adjusts multiple parameters simultaneously based on real-time measurements. By changing actuator positions, reel speed, and other process parameters in a coordinated manner, the system achieves precise control of reel building characteristics while managing the complexity through integrated parameter adjustment.

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP2297618B1Method and apparatus for reel building and roll runnability in moving web manufacturing
Publication Date: 2019.12.11 VALMET AUTOMATION INC
  • EP2297618B1 patent drawingFigure 1
  • EP2297618B1 patent drawingFigure 2
  • EP2297618B1 patent drawingFigure 3

AI summary

A method and apparatus are set forth for controlling an actuator in a moving web manufacturing process, comprising measuring a plurality of actuator profiles and in response generating nominal response models thereof; generating a muttivariable profile prediction based on the nominal response models; generating a multivariate control target based at least one of the actuator profiles; and adjusting control of the actuator by minimizing error between the multivariate control target and said multivariate profile prediction.