1. Application Scenarios & Labeling Requirements

Define labeling objects (e.g., cartons, plastic bags) and positions (single/double-sided). A cosmetics company required precise side-labeling for flat bottles and chose a machine with dual-chain correction, achieving ±0.5mm accuracy.

2. Core Parameters: Precision vs. Speed

Balance accuracy (±0.3mm–±1mm) and speed (20–180 pieces/min). A pharmaceutical firm needed ±0.3mm accuracy for syringe labels and selected a vision-guided system.

3. Label & Material Compatibility

Support common materials (e.g., PET, PVC) and label sizes (15–150mm width). A logistics company handled diverse face sheets and chose a machine with multi-material recognition, reducing label changes by 70%.

4. Drive System & Control Technology

Servo motors offer faster response than stepper motors. An auto-parts manufacturer improved labeling yield from 92% to 98% by switching to servo-driven systems.

5. Sensor & Vision System Configuration

CCD vision systems identify barcodes and auto-correct positions. A 3C company reduced labeling errors by 40% with visual guidance.

6. Scalability & Integration

Ensure compatibility with coders and sorting lines. A medicine firm integrated a thermal transfer module for “labeling-coding” in one step, cutting labor by 30%.

7. Stability & Reliability

Prioritize machines with MTBF >2000 hours. A German SCHMIDT model ran continuously for 2000 hours without failure, while a budget alternative averaged 500-hour downtimes.

8. Ease of Operation & Maintenance

Touchscreens with preset parameters reduce training time. A food company cut product switch time from 30 to 10 minutes using 20 preset groups.

9. Brand Reputation & After-Sales

Choose suppliers with 24/7 support and spare parts inventory. A logistics firm received on-site repairs within 2 hours via a national service network.

10. Budget vs. Long-Term Cost

Avoid overspending on unused features. A startup saved 60% by upgrading a basic model with a coding module later, instead of buying a premium machine upfront.

Key Takeaway: Prioritize precision, stability, and scalability. Test machines under real-world conditions and calculate TCO (Total Cost of Ownership) over 5 years to make an informed decision.

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