See How a Pharma Manufacturer Found Hidden Bottlenecks

AI video analytics revealed contamination risks, manual interventions, and safety violations that traditional systems missed. This unlocked up to 40% potential reduction in downtime.

See It In Action

Challenge

Unexpected stoppages and contamination risk on a semi-automated bottling line

System Goal

Fully autonomous line with minimal operator intervention

Industry

Pharmaceutical Manufacturing

Environment

Cleanroom, high-throughput liquid packaging

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What Changed With Pacefactory?

Before

Manual restarts were common
Frequent cleanroom violations
Downtime blamed on wrong stations

After

Video showed root causes in real time
Safety and contamination risks flagged
Operators refocused on value-added work

Challenge

The Bottling Line Was Stalling and No One Knew Why

Sensors missed cascading delays caused by buffer imbalances

Operators stepped in constantly, increasing risk of contamination

Faults in labeling and filling appeared disconnected, masking root causes

Diagnosing the Real Problem with Bottleneck Analysis

Traditional machine monitoring systems rely heavily on sensor data, machine states, and manual operator input. While this gives visibility into what happened, it often fails to explain why, where it started, or how long it’s been building up across the line.

To uncover the hidden sources of inefficiency, Pacefactory deployed its Bottleneck Analysis capability - a structured approach designed to deliver rapid, end-to-end visibility of production flow.

1 Analyze the Entire Line to Spot Where Flow Breaks

Pacefactory began by capturing video footage across the full bottling line. The system tracked product flow, operator presence, and machine status indicators like signal lights. This allowed the team to detect where blockages, delays, or inconsistencies were occurring - identifying the precise stations that disrupted the line’s rhythm.

2 Zoom In on Problem Stations for Root Cause Diagnosis

Once the critical stations were identified, Pacefactory focused its analysis on those machines. By observing video footage frame-by-frame and correlating it with machine signal lights and operator actions, the system revealed the true causes of downtime - whether it was machine faults, lack of supply, downstream blockages, or unnecessary manual intervention.

3 Quantify Losses with Visual Evidence

Each type of downtime was quantified in terms of duration and frequency. Pacefactory tracks product count, flow speed, and machine status using stack light signals. When flow breaks occur - due to faults, starvation, or blockages - they’re visualized on the timeline.

What We Found

Visual Evidence. Real-Time Insight.

High downtime at filler (69%), with most linked to recurring machine faults

Labeler delays traced to upstream starvation—not internal issues

Bottle orientation bottlenecks often linked to downstream pileups

Operators entered clean zones without PPE during intervention events

High downtime at filler (69%), with most linked to recurring machine faults

Labeler delays traced to upstream starvation—not internal issues

Bottle orientation bottlenecks often linked to downstream pileups

Operators entered clean zones without PPE during intervention events

Up to 40% Downtime Reduction Opportunity Identified

54%

Orientation Station

downtime is due to downstream blockages.

52% 

Filler

downtime is tied to preventable machine faults at the filler station.

37% 

Labeller

downtime is caused by starvation due to delays at the filler.

Protects individual privacy

Works with existing cameras

Impact Across the Pillars

Efficiency Insights

Reduced downtime and increased throughput.

Achieved a 12% reduction in cycle time by eliminating unnecessary delays

Reduced manual handling by reassigning repetitive tasks to automation

Safety Insights

Fewer violations, safer floor behavior. 

Reduced PPE violations by 65% after automated video detection

Eliminated unauthorized entries in restricted zones through real-time alerts

Quality Insights 

More consistency, fewer defects. 

Achieved a 12% reduction in cycle time by eliminating unnecessary delays

Flagged unverified CIP cycles, resulting in improved audit scores

Insight Without Compromising Privacy

Pacefactory’s patented Ghosting Technology automatically anonymizes workers in video feeds while preserving key movements, timing, and interactions. You get data—without surveillance.

Pacefactory showed us exactly where and why our line was losing time - something we couldn’t see with traditional systems. The video insights helped us uncover root causes we had been guessing at for months

Operations Lead

Global Health Manufacturer

Want to See Bottlenecks Like This in Your Facility?

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See It In Action

Often works with your existing cameras. Fully on-premise for data control and compliance.

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