Veneer Sorting Simulation for Defect Threshold Adjustment
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Solution Overview
Problem
The existing veneer sorting systems require repetitive adjustments of determination parameters to achieve optimal sorting of veneers into quality ranks, leading to inefficiencies and increased time in manufacturing plywood, as the grades assigned to veneers vary significantly based on strict or loose condition values for defect detection.
Innovation Solution
A veneer sorting control device that acquires and analyzes image data of veneers to detect defects, determines quality ranks based on set conditions, and totalsizes the sorting results to display on a screen, allowing for adjustments to be made on a computer rather than through sequential sorting and reconfirmation of actual veneers, thereby streamlining the adjustment process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If strict condition values are set for determination parameters, then the number of veneers sorted into high-quality grade decreases, but the sorting precision and quality control improve
Solution Approach 1:
The system dynamically adjusts determination parameters based on log information and sorting results. The control device modifies condition values for defect detection in real-time, allowing the sorting criteria to adapt rather than remain fixed. This enables the system to maintain high detection precision while optimizing the distribution of veneers across quality grades for better productivity.
Solution Approach 2:
The invention changes the determination parameters (condition values for defect detection) based on log characteristics and sorting outcomes. By adjusting these parameters dynamically, the system can shift between strict and loose detection criteria as needed, resolving the contradiction between maintaining high quality standards and maximizing the number of usable high-grade veneers.
2Productivity
If loose condition values are set for determination parameters, then the number of veneers sorted into high-quality grade increases, but the sorting precision and quality control deteriorate
Solution Approach 1:
The system uses dynamic adjustment of determination parameters based on feedback from sorting results and log information. When loose condition values are needed to increase high-quality grade output, the system temporarily relaxes criteria while maintaining overall quality control through continuous monitoring and adjustment, preventing deterioration of sorting precision.
Solution Approach 2:
The control device modifies determination parameters based on the desired balance between productivity and quality. By changing condition values adaptively, the system can increase the number of high-quality veneers when needed while ensuring that defect detection precision is maintained through compensatory adjustments in other parameters.
3Reliability
If repetitive adjustment of determination parameters is performed to achieve optimal sorting, then the quality management improves, but the time required for sorting increases
Solution Approach 1:
The system performs preliminary sorting based on initial determination parameters before final quality assessment. By conducting a preliminary classification and then making targeted adjustments only where needed, the system reduces the need for repetitive full-scale adjustments, thereby maintaining reliable quality management while minimizing time loss.
Solution Approach 2:
The control device implements feedback mechanisms where sorting results are automatically analyzed and used to adjust determination parameters. This closed-loop system reduces manual repetitive adjustments by automatically learning from sorting outcomes, improving quality management efficiency while reducing the time required for parameter optimization.
4Measurement precision
If manual sorting and reconfirmation of actual veneers is performed, then the accuracy of sorting results is verified, but the manufacturing efficiency decreases
Solution Approach 1:
The system creates digital copies (image data) of veneers for analysis and sorting determination. By working with high-resolution images and automated image processing rather than requiring physical manual inspection of each veneer, the system maintains sorting accuracy while dramatically improving manufacturing efficiency. The digital copying and analysis replace time-consuming manual verification.
Solution Approach 2:
The invention replaces manual mechanical inspection with automated image processing and computer-based analysis. The system uses optical imaging and algorithmic defect detection to verify sorting results, substituting human manual verification with automated systems that provide equivalent or superior accuracy while significantly reducing time requirements and improving overall manufacturing efficiency.
Data Source
AI summary
Provided is a veneer sorting control device including: a sorting condition setting unit 11 that sets sorting conditions for each of a plurality of kinds of defects so as to sort a veneer into a plurality of quality ranks; a defect detection unit 13 that detects the plurality of kinds of defects with respect to each of a plurality of pieces of veneer image data acquired from an image storage unit 100; a quality rank sorting unit 14 that sorts a plurality of the veneers into a plurality of quality ranks in correspondence with the sorting conditions which are set and defect detection states; a first totalization unit 15 that totalizes the number or a number ratio of the veneers in the plurality of quality ranks which are sorted; and a display control unit 17 that displays the totalization result on a screen. The number of the veneers sorted into the plurality of quality ranks can be confirmed by a simulation using the veneer image data stored in the image storage unit 100.