Case study

Optimization on Labeling and Triage Workstation

Optimization on Labeling and Triage Workstation

Company: Hugo Boss

Challenge

Ergonomic Risks in Labeling and Triage Workstation

The labeling and triage process in a textile factory posed serious ergonomic risks for workers, leading to long-term health issues, increased absenteeism, and reduced productivity.

How the problems were identified?

Using computer vision and AI-powered video analysis, the workstation recorded and analyzed worker movements to detect ergonomic risks in real-time. The AI identified:

 Repetitive wrist and elbow movements due to manual labeling

Improper wrist posture (excessive flexion) while handling labels

Frequent weight carrying (labeling machine handling) adding physical strain

Why This Was Critical to Solve?

The AI-generated analysis revealed that workers were at high risk of developing long-term musculoskeletal disorders. This led to:

 Higher rates of workplace injuries

Increased costs due to medical expenses and absenteeism

Lower efficiency and longer production cycles

Solution

AI-Generated

Improvements & Training

To mitigate these challenges, AI-powered Improvements were implemented, leading to a combination of technological innovation, operational restructuring, and worker training.

1

Automated Labeling Process

Replacing manual labeling with a sensor-based system. This eliminated repetitive wrist movements by automating the labeling process.

2

Eliminating the Old Labeling Machine

The manual labeling machine, identified as a key source of wrist strain, was removed, reducing unnecessary hand movements and strain.

3

Health Screening for New Hires

Pre-employment wrist health assessments to ensure that new employees had the physical capability to perform the job safely.

4

Ergonomic Training for Workers

Employees received AI-recommended training on proper wrist ergonomics and injury prevention, reducing risks in daily operations

Result

AI-Generated

Improvements & Trainings

To mitigate these challenges, AI-powered Improvement & Trainings were implemented, leading to a combination of technological innovation, operational restructuring, and worker training.

Key metrics

Workplace Injuries (Wrist & Elbow)

Number of Workers Needed for Operation

Manual Labeling Movements per Shif

Production Efficiency

Before AI Analysis

High, 12 incidents per year

2 workers per shift

1,200+ movements

70% efficiency rate

After AI Recommendations

Low, 2 incidents per year

1 worker per shift

0 movements (fully automated)

92% efficiency rate

Key metrics

Workplace Injuries (Wrist & Elbow)

Number of Workers Needed for Operation

Manual Labeling Movements per Shif

Medical Leave Due to Repetitive Strain Injuries

New Employee Hiring & Training Costs

Production Efficiency

Before AI Analysis

High

2

1000+

Frequent

Recurring

Moderate

After AI Recommendations

Reduced significantly

1

Eliminated

Reduced

Lowered

Improved

Are you struggling to identify and fix ergonomic risks in your facility?

Contact us today to learn how our AI-driven solutions can enhance workplace health, optimize efficiency, and reduce workforce injuries.

Make people healthier

Humanize

your workspace.

Let’s start creating better workplaces for a better world.

Crafted with

at 2025.

Make people healthier

Humanize

your workspace.

Let’s start creating better workplaces for a better world.

Crafted with

at 2025.