Spray Nozzles Visual Inspection: A Step-by-Step Guide

The Problem: Manufacturing Challenges

Spray nozzles are mission-critical for dosing, coating, cleaning, and cooling, yet they degrade with use. Even slight wear or damage distorts flow, wastes material, and hurts product quality.

• Orifice Erosion: Enlarged or misshapen openings from wear that increase flow and distort pattern.
• Corrosion/Pitting: Material loss on tips and seats that alters droplet size and angle.
• Clogging/Debris: Partial or full blockage causing streaks, jets, or incomplete coverage.
• Cracks/Impact Damage: Chips and deformations from mishandling or cleaning that skew distribution.

Human vision fatigues quickly under glare, repetition, and small tolerances, leading to inconsistent decisions and escapes.

The Solution: Automated Visual Inspection

Machine vision makes nozzle inspection objective. High-resolution images capture the tip, orifice, seat, and filter screen so small erosion, nicks, and deposits are detectable beyond human acuity.

Deep Learning learns the difference between acceptable manufacturing variation and true defects. It flags poor pattern indicators and physical damage consistently, enabling proactive maintenance and optimized spray system performance.

Step 1: Imaging Setup

Click Configure Imaging. Place the object in view. Adjust Camera Settings for a clear image and click Save.

Position each spray nozzle so the orifice, tip face, seat, and any screens are visible. Ensure the part is fully within the frame before saving. Good lighting contrast is essential to highlight the internal geometry of the orifice.

Step 2: Image Alignment

Navigate to Template Image. Capture a Template, add a + Rectangle region, and set the Rotation Range to 20 degrees.

This normalizes minor part rotation so downstream inspections stay anchored to the same geometry on every nozzle. This is crucial for nozzles on conveyors where orientation might shift slightly.

Step 3: Inspection Region Selection

Navigate to Inspection Setup. Rename Inspection Types. Click + Add Inspection Region. Resize the yellow box over the defect area and click Save.

Draw the yellow box over critical areas such as the orifice edge, tip face, seating surface, and spray exit where wear, clogging, or cracks appear.

Step 4: Labeling Data

Label images as Good or Bad to train the recipe.

Use a human-in-the-loop review to confirm borderline cases so the model learns real-world tolerances and avoids false rejects. This is particularly important for distinguishing between minor cosmetic marks and functional damage.

Step 5: Creating Rules

Set pass/fail logic based on Inspection Types.

Define which regions must pass to accept the nozzle, and combine region outcomes into the final decision to match your quality standard. For example, a nozzle might pass if the housing is scratched but must fail immediately if the orifice is eroded.

Key Outcomes & ROI

• Reduced Waste: Less over-application from worn nozzles and fewer reworks from poor coverage.
• Higher Throughput: Faster, consistent decisions without slowdowns from manual checks.
• Lower Maintenance Costs: Early detection of wear and damage prevents unplanned downtime and secondary failures.