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Case Study 08 — Image Analytics for Scrap & Downtime Reduction in Paper Manufacturing
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Case Study · 08

Image analytics for scrap and downtime reduction in paper manufacturing.

A 24/7 operational analytics solution that reduces scrap, downtime, and labor loss by making edge defects visible before they turn into full-sheet tears.

Industry Paper manufacturing
Focus Area Operational analytics & efficiency
Up to 20 tons/day scrap prevention
~200 minutes/week downtime savings
Payback period under 6 months
Project Context

Why was this project needed?

Defect detection systems are not just quality control tools but also critical instruments for production efficiency and cost reduction.

Needs & Challenges

Key challenges

Late-detected defects lead to significant scrap loss, unplanned downtime, and inefficient labor utilization.

Approach

How was it addressed?

The image analytics system was designed to address quality metrics and operational metrics together.

Solution Components

Implementation structure

Continuous defect tracking
Operational alarm framework
Real-time reporting
Scrap and downtime impact analysis
24/7 production-ready architecture
Value Delivered

Outcomes and impact

Line visibility increases, intervention becomes possible before major losses occur, and overall production performance is strengthened.

Related Areas of Expertise

Competencies applied in this project

Technology Data & Analytics Transformation

Let's discuss image analytics solutions focused on scrap and downtime reduction.

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