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Density and bottleneck analysis on packing lines: which station slows the line?At a fresh-produce packing plant, existing cameras measured unit counts, active working time and line density per station; bottleneck stations and hours were identified with data.
2026-10-12

At a plant sorting and boxing fresh vegetables, line capacity was the same on paper, yet end-of-day box counts differed widely between stations. Nobody knew which point was slowing the line. Hype Vision used the existing cameras covering the lines to measure how much each station processed and how actively it worked.

Product counting and bottleneck analysis at a boxing station
In short
Problem

Belt speed was set the same for the whole line, but product piled up at some stations while staff waited idle at others.

Solution

Each station was defined as a product area (ROI) in the camera view.

Result

Bottleneck stations and hours identified with data; Staffing re-planned according to station load; Line density and build-up monitored live

CamerasExisting IP cameras
AnalysisStation ROI + anonymous pose analysis
MeasuredCount · active time · density
OutputBottleneck report + heatmap
IdentityAnonymous (station-based)
ArchitectureOn-premise

Problem

Belt speed was set the same for the whole line, but product piled up at some stations while staff waited idle at others. Only the total box count was known at the end of the shift; where time was lost was invisible.

How we measured

Each station was defined as a product area (ROI) in the camera view. Products moving from the area into boxes are counted; anonymous pose analysis separates active working time from waiting. Product density on the belt is measured from the same image.

Product counting and bottleneck analysis at a boxing station
Boxing station — product area, counter and anonymous pose analysis
  • Products / boxes per station
  • Active work vs. idle waiting time
  • Product density and build-up on the belt
  • Hourly throughput curve and shift comparison

Finding the bottleneck

Placing every station's hourly throughput side by side clearly showed that certain stations and hours were holding up the rest of the line. Product build-up on the belt rose in the same time windows.

StationBoxes / hourActive timeBelt densityStatus
Boxing 14291%NormalBalanced
Boxing 22864%HighBottleneck
Boxing 33988%NormalBalanced

Results

Staffing and belt layout at the bottleneck stations were re-planned based on the data.

  • Bottleneck stations and hours identified with data
  • Staffing re-planned according to station load
  • Line density and build-up monitored live
  • Shift and day comparisons reported automatically
  • Station-based measurement without tracking individuals

Related solutions

Frequently asked questions

Are individual workers tracked?

No. Measurement is station-based; pose analysis only determines whether work is happening at the station, and nobody is identified.

Do we need new cameras?

Existing cameras that see the lines from above are usually enough; camera angles are reviewed during discovery.

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