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Paper defect and image analysis

Defect and image data from web inspection systems can be provided to users in all needed locations of the process via intuitive user interfaces.

Methods for real-time full web, pulp, paper and paperboard analysis

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ABB Web Imaging System's (WIS) highly intuitive interfaces are informative and easy to use and have been designed based on end user input collected from our extensive installation base. The various interface designs provide timely data in the most useful form possible to support real time quality decisions and to expedite root cause analysis.

For example, the WIS formation analysis feature provides real-time size, shape and intensity analysis of formation floc and void contents by 16 size categories, which far exceeds the single formation index from similar solutions on the market. The quality classification is based on machine learning principles and allows formation change detection, which pinpoints areas where formation has changed drastically.

Easy visualization for quick decision making is key. Web Imaging Dirt Count using color coding to highlight high dirt count areas, clearly showing that dirt is not evenly distributed across the sheet and providing clear cutting parameters for rolls.

Industry’s easiest advanced classification tools

Defect maps
  • On-line dynamic map with defect details and classification results
  • Off-line archive map with roll/set overlay
ABB Smart Classifier
  • Self-sorting image gallery for intuitive classifier training
  • Quality classification is based on machine learning principles
Trending and profiling
  • Configurable trending and profiling
  • Possible integration with quality information from the whole mill

Latest advancements to ABB's Web Imaging System

Do more with quality data integration and analytics

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