Preferential Defect Marking on Moving Web Material
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Solution Overview
Problem
Automated inspection systems face challenges in processing high-speed data from moving webs, particularly in detecting anomalies that may become defects during multiple manufacturing operations, making it difficult to determine suitable product grades and causing unnecessary material wastage.
Innovation Solution
An automated inspection system that identifies anomalies on moving webs and associates unique marks with each potential product grade, allowing for precise marking of defects, enabling converters to determine suitable product uses and optimizing material utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high-speed data acquisition is used to inspect moving webs, then inspection speed is improved, but data processing complexity increases
Solution Approach 1:
The inspection system performs preliminary classification of anomalies into product-specific defect categories during the inspection process itself. This preliminary action allows the system to pre-determine which anomalies are defects for which products, eliminating the need for complex post-inspection analysis and enabling straightforward material utilization decisions.
Solution Approach 2:
The system segments the web material into different utilization categories based on anomaly characteristics and product requirements. By dividing the web into segments with different defect classifications, the system simplifies processing by treating each segment according to its specific category rather than analyzing the entire web uniformly.
2Adaptability or versatility
If multiple unit operations are performed on a single web roll, then product versatility is improved, but defect detection accuracy deteriorates
Solution Approach 1:
The inspection system performs preliminary classification of each anomaly into product-specific defect categories before the web undergoes multiple unit operations. This preliminary classification creates a reference guide that remains valid throughout subsequent processing steps, allowing accurate defect determination regardless of how many operations the web undergoes.
Solution Approach 2:
The system adds a new dimension of classification by categorizing anomalies not just by their physical characteristics but by their potential impact on different product grades. This multi-dimensional classification approach enables the system to maintain accurate defect detection across multiple product transformations without requiring re-inspection at each stage.
3Reliability
If conservative defect rejection is applied to ensure quality, then product reliability is improved, but material waste increases
Solution Approach 1:
The system applies local quality assessment by determining which specific anomalies are defects for which specific products, rather than applying uniform rejection criteria. This allows regions of the web to be utilized for products where their quality is acceptable, while only rejecting material that would be defective for any intended use, thereby minimizing waste while maintaining reliability.
Solution Approach 2:
The system changes the parameters of defect determination by evaluating anomalies in the context of multiple product specifications. Instead of using fixed rejection thresholds, the system adjusts acceptance criteria based on the specific product requirements, allowing the same web region to be acceptable for some products but not others, thus optimizing material utilization while ensuring product reliability.
Data Source
AI summary
A system for preferentially marking defects on a web is described. The system includes a web of material to be converted into individual sheets of a plurality of different grade levels, a database storing anomaly data of anomalies on the web, wherein an anomaly is a potential defect in at least one of the plurality of different grade levels, a marker that associates a unique mark with at least one of the grade levels, and a controller to retrieve the anomaly data from the database and to signal the marker as to where to make a mark, wherein the marker applies the mark associated with at least one of the grade levels for which the anomaly may cause a defect. The system may provide advantages, such as that a converter of various products from a single web roll may determine which regions of the web satisfy each grade level.