0%
0%
throughput increase in 3 months
Introduction
Even high-performing lines eventually plateau. At Grundfos Serbia, a manual assembly line that had already gone through eight kaizens, tighter 5S, flow optimisation, and several redesign workshops still struggled to break through its efficiency ceiling. Operators were skilled. Processes were stable. MES was in place. But the numbers weren’t moving anymore and cost pressure was rising.
Despite clean MES dashboards and consistent output tracking, the real inefficiencies stayed hidden: micro-stops, missed steps, idle pockets, slowdowns too small or too frequent to record manually. This case study shows traditional tools could only reveal the tip of the Continuous Improvement iceberg.
Challenge
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Solution
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Results
What happened next became one of the most compelling examples of AI-driven process visibility in modern manufacturing.
Once the team could see clearly, they could act decisively.
This downloadable case study dives into the before-and-after reality of Grundfos’ transformation: what the team tried, why traditional tools weren’t enough, what AI exposed instantly, and how these insights translated into real, measurable improvements in productivity, quality, and labour allocation.
See the full breakdown of insights, visual analytics, AI-detected bottlenecks, and the exact steps the Grundfos team took to unlock 11 percent more throughput.
Questions
answered.
What is Almetra and how is it different from a camera or video analytics system?
What kinds of factories and production environments does Almetra work in?
How long does deployment take — and what does implementation look like?
How does Almetra handle data privacy and worker concerns?
Does Almetra replace our existing MES, ERP, or PLC systems?
What outcomes can we realistically expect — and how quickly?
Is Almetra only useful for improving existing lines — or can it help with new products and ramp-ups?
What does the path from pilot to full deployment look like?
System status · OperationaL
v 2026.5
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